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Speaker 1: When your old career gives you lemons throwing some ice

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mix in some vodka colored A podcast from the Mac

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of All Trade Studio in Fairport and driven by Victor

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Chrysler Dots. Gee Ram, It's Billified, the Bill Moran Podcast.

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Speaker 2: Hello and welcome. I jumped the gun. I usually wait

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till this point. Sorry, I'm all discombobulated today. It's been

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a day.

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Speaker 3: This should out the GM of the Jets.

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Speaker 2: Yeah, what happened there? Guessing a rod He's gone right,

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I got fired? He got fired? Yeah, I don't know. No,

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it's just one of the well again, that would be

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a thing like everybody praised you forgetting Aaron Rodgers and

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then he takes it out, taking you down like you're

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one of the twins hours. It's just terrible, bad analogy.

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I apologize, I'll allow it, but I'm just saying, like,

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that's how I feel today, Like I didn't know ship

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was going bad, but it was going bad, and it

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was out of my control and there was not a

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lot I could do about it.

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Speaker 3: It's just I love how they had to go to

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the bullpen for it too. What do you mean they

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had to go to the bullpen? We need to we

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needed Lefty from an East, the funny East.

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Speaker 2: I can't I should say what that is. Yeah, they

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couldn't get me, so they called his other father. They call,

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they called, and he wound up. Happened Jameson.

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Speaker 3: Yeah, it's good to know they already know that they

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if they can't get you the first Placesta should probably

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call Osma Conners and if you're not there, then Uncle

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Davie will come take care of it. Wasn't It wasn't

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that I wasn't there. I was doing that, but they

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probably assumed you were.

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Speaker 2: No, they didn't. I was. That's terrible that you would

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even say that.

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Speaker 3: Oh yeah, because I'm way off that one.

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Speaker 2: Just lots of things today. It's it's I feel bad

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because sometimes I think that what I think is over

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reaction and I don't really react to things. And it

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was even like last night, we talked about that weird

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situation in the studio on Thursday, and I'm listening to

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these guys and I'm like, well, you locked the door.

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Did you tell your kid to lock the door? And

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I go, No, I didn't do any of that because

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I just didn't think it was that big a deal.

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I don't know there's something in me that and I

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feel like I've been that way my whole life. Some

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things are serious and some things aren't. And when they're serious,

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I'll know, and when they're not, just a big bunch

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of bluster and everybody's just you know, blowing smoke out

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their rest. But I don't know.

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Speaker 3: Well, I was telling you that we had that situation

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in my neighborhood where they were looking for somebody. Yeah,

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and there's cops o over my neighborhood and come back

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and I'd beat and carry back.

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Speaker 2: Yeah.

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Speaker 3: So when she came in, I'm down. I'm down at

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my desk and I yelled up. I said, hey, close

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the garage door. She's like why, I go, Well, if

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there's somebody wander around the neighborhood, ire for not to

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have them in our house.

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Speaker 2: Yeah.

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Speaker 3: I don't want to be a hostage. Got shit to do.

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She's like, what are you scared? Like, No, I just

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don't want to be a hostage today.

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Speaker 2: I got not to do right exactly. And you're not overreacting.

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You're just saying shut the door and we'll go on

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with our lives.

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Speaker 3: We never, I mean, we never shot it during the

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day except in the very in the spring when the

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birds start.

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Speaker 2: We didn't even lock our doors when I was growing up.

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I mean, granted you lived in you lived in nineteen

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sixty one.

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Speaker 3: They're nineteen forty one, when there was nobody around sixty one.

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Close enough. Well, I read it flustered.

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Speaker 2: I read a story this morning with the headline two

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women arrested after stolen car chase crashed in Rochester, and

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I may get a few side glances for this, but

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I started thinking a lot. I believe women, I've said

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this on the podcast, and I do believe it, are

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more emotionally intelligent. I think they are better at reading situations,

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at reading rooms. I think that women just are better

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at all those things than men.

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Speaker 3: But clearly my majority there the stereotyper so they couldn't win.

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Well were the Asian women by the.

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Speaker 2: Chance, And because of this, because of that, right, thinking

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of that, that they're smarter in these emotionally intelligent areas

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stealing cars, I would think most women would find a

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way to quote unquote borrow a car from somebody and

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maybe not return, you know what I'm saying, like you know,

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go hey, you know, or talk their way into the

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car so this was this was a strange thing. So

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I started to think about women being you know, strong,

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they're talented. Martha Stewart, she's a corporate mogul. People love her.

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I mean I watched that documentary on her on Netflix.

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It's really interesting and it just shows who she is

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and even today, I mean, she's in her early eighties

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and she's still giving it her all and I think

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in an very impressive person. And last Friday, people were

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waiting for the Jake Paul Mike Tyson fight, and what

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you saw that was a really great fight was the

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two women, Katie Taylor and Amanda Serrano. As Katie was.

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I mean, Katie's a badass. Granted she head buttered, I

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get it, I understand, but you only lose a point

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for headbutting. I think if they want to outlaw headbutting,

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it should be three points because also over the eye,

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the blood getting in the eye is well, you can't

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see it. Didn't take any points from her. I thought

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they took one point.

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Speaker 3: I don't think they took any points on any of

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the head buds.

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Speaker 2: They should deduct up. I don't know, I just know

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headbutting is usually a point deduction. Whether or not that happened.

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I actually don't know. He's in a WBA WBC ibo

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like you know, weight and I think the other girl

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came up and wait to fight her. But that was

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a great fight. It went to full ten rounds. That's

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gotta be the best for a woman knowing they get

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to come up and wait. They just started going bond

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bombs on the couch. But you know, and then I

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started the w NBA used to be a joke like

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no one was there, who.

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Speaker 3: Except for the Caitlin.

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Speaker 2: Well, here's what I think, Kevin. I think the I

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think Katelyn shows you all the other great athletes are

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there because I mean, they start getting superstars, Like you know,

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when I say superstars, I mean stars coming out to

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see their games. People with influence. You've got well Spike Lee.

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But then I thought, I thought Tom Brady went to

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a game and some others. I did think along the

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way throughout the season. So I go, it's like they're

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getting eyes on their games, right. I hear people asking this,

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are we not ready for a female president? And I

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would say to the answer to that is because I

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heard that like a lot this week on news gas

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We're not ready for a female. They did some interview

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with Bill Clinton, and even Bill Clinton said, I don't

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know that we're not ready. I think Bill Clinton came

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short of because he's a Democrat, saying we just didn't

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put up the right person, you know. I mean that

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that's the only thing I can think of, look the

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majority of.

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Speaker 3: So you think that it's one of those things where

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it's it's a job that a man has always had. Yeah,

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and it's I just don't know that. I think people

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might not be ready. I mean, yes, obviously there's around

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the world there's prime ministers and people that run countries

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that are women, but not the free world.

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Speaker 2: I always think that you might be right. I'm thinking,

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I'm not trying to make it. In a second, well,

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they are trying to make people think. They are trying

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to make it a sexist thing. And that's what I'm

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saying here. So if we have all this, the w

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n b A, the fights, everything's rising up, all these things,

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why not crimes. I would not normally associate women with

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violent crimes like stealing cars and things, which would be

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a little bit more violent crime. Then then I don't know,

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stealing something out of all the I mean sh having

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a stake in in in your person walking out the

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door not not the same.

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Speaker 3: You know it will be the best because I guarantee

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would be the very easiest crime to do to steal

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a car would be to get Doug in the uber.

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All you'd need is in habits and a six pack

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in mibbits and you'd be able to take his car

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over in a second.

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Speaker 2: But the rest rate for women has increased forty one

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percent since nineteen eighty. The proportion of women arrested for

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violent crimes has more than doubled, reaching twenty one percent

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in twenty twenty. In contrast, the arrest rate for men

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was thirty five percent lower in twenty nineteen than it

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was in nineteen.

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Speaker 3: Yeah, that's reversing because the guys are still trying to

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get the hell away from women. Well, I go now

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they're going into jail and trying to get the hell out.

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Speaker 2: I'm not sure to want to hear the naga. I'm

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not sure what all that means. But you're doing you're

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doing better than men in the arrest rate, right, you're

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getting more percentage wise, you're up, men are down. And

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I know these percentages are based on different size pools

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because I still think, like I went and looked for

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another stat of all the arrest in twenty nineteen, and

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that's when the last dat is from city. Two point

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five percent of those arrests were men. So you can't

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say that.

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Speaker 3: But but it's also it's also a lot of things

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two with women are are starting to do more and

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more things. Yeah, you're on the past, and that sample

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sizes is greater because you're at zero.

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Speaker 2: Yes, you're at zero, all of a sudden you hit.

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Now you're hit, but now, but look better. Fight Friday

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night was the women absolutely entertaining w NBA games. They're

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reffing in the NFL, they're reffing in the NBA, there

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refing in Major League Baseball and the NHL. There are

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assistant coaches in the NHL. And then I did not

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know that I knew the assistant coach, and I knew

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that there's a female GM, which to me makes perfect sense.

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So why not?

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Speaker 3: And I think there's one good la your brazen came

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into baseball too, Yes, yeah there is, and not with

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like one of the shittier teams when I think one

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of the bigger name teams, not like the Yankees and

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Red Sox.

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Speaker 2: But I thought that it was the Upper Marlins, is

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what I thought. But that might have been a while ago.

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Who knows. Look the idea that there's I can't. I

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don't get it. I actually do believe that women overall

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are just i'll call it more emotionally intelligent, maybe overall intelligent.

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But all that stuff to me is funny. So when

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I see the crime rates, I go, I guess that

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makes sense.

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Speaker 3: Well that's why those those the crime rates were so

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high at the point, because a lot of that that

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white color crime all you know, aunt mars bazzling.

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Speaker 2: Yeah, not violent, but no, but they want to be

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smart crime. Back in the day, Well, what do we

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always say when we hear somebody in bazzling? We always go,

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I'm a middle aged white woman. Always she's been picking

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from the pilfering from the troth for a couple of

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months or a couple of years. Who knows, You've me

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find out there's fifty thousand dollars gone, twenty to five

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thousand dollars gone. Who knows it is? Uh? But so

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I was trying to look to see and I couldn't

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find it any more. Modern day crimes right now today,

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But it was eighteen nineteen year old girls and I'm

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going a high speed chase involving the police. I'm not

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I'm sorry, right, eight times out of ten, I'm not

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picking a no. Ten out of ten, I'm not picking

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a woman to be behind the wheel.

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Speaker 3: And I think I think younger girls are trying to

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starting to be a little bit more brash too, yeah,

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and not taking ship and just being like, you know what,

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fuck it, I'm going to do it too.

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Speaker 2: I don't know, You're probably right. I don't know. It's

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it's very strange world we're living in right now. Everything

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just seems to be a little all over the place,

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and I don't know what to think of it. But

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I saw that way.

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Speaker 3: It's an entertaining show. Yeah, just watch the news. Jo

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entertained well.

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Speaker 2: In a way, and it's always bad, right, It's like,

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can we get something because there's a number of people

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that are doing good stuff that don't get any recognition,

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and it's all the people doing bad stuff that we

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got to hear about all the all the worst shit.

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And I always wonder, like, you know, could and then

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the news tries they do their good news section or

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the Yeah.

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Speaker 3: But that's that's extra sports and it's their already I've

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already started dishes exactly.

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Speaker 2: And I go, what what do we We need to

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focus a little bit more on that stuff. But you know,

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take take these these car thefts and make them working

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in a garage or something. Maybe they'll know some uh

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how to hot wire a car. Maybe maybe you'll find

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the cure to uh stopping the Kia boys or whatever.

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What's going on? I don't know. I'm getting text again.

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All right, So tonight we're gonna have a couple of

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guys who are I would say, I don't want to

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say AI experts, but they have a company and there's

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a lot of I think trepidation maybe the word around AI.

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You know things that you know, will it be possible

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in the future to have a job, what's gonna happen

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with certain things? Well, what industries are going to be gone?

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What can we do? You know? All these different things?

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Uh just kind of the is AI biased on what

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it's being fed to gain its knowledge? Uh? There are

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people who think that there's a lack of transparency. We'll

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find out from Cody Brendan and Brendan Fraser Brendan Fraser

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is a the actor. That's when I was, well, yeah,

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he is, well this is spelled a little differently in

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the Fraser. But these guys are going to come in

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and we'll talk to my eyes stuff because it is interesting.

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And I wound up talking to a virologist today. Hell's

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a virologist. A virologist is somebody who studies viruses and

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what they do to the human body and how to

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counteract them. And this guy from the University of Rochester

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was saying, and this is interesting, and credit Stephanie id

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who has been on this show for a couple of

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years now, and she has said every time where she

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wants people to be tested for sexually transmitted diseases. And

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I think that I either roll my eyes or give

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a sigh. Come on. And this guy said today that

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about ten to fifteen percent of the population has HIV

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and doesn't know it. So I'm going, what, it's kind

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of like COVID, where people were they didn't know they

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had it, you know when it was really going like

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some people did not exhibit symptoms, but they were, so

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they were spreading it.

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Speaker 3: So we found the real reason Dad lost the way

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He's one of the fifteen percent, because clearly I don't.

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Speaker 2: So this guy is he They have patented a test

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that you that they hope to eventually get into drug

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stores and things, where you prick your finger and test

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your blood and it does the test and much like

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the home COVID test, you'll find out if you have

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AIDS or not or right not. Let me rephrase that

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v HIV. I don't want to say AIDS because that's

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not correct. I don't want to say that.

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Speaker 3: But so now we've got we've got the genealogy. You

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can figure out where you're from. Yep, you can take

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a dump in a box.

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Speaker 2: You can take a dump in a box and figure

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out I've got coll and can you got it?

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Speaker 3: Now you can prick your finger and see if you get.

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Speaker 2: Never lean to go to the hospital again for a test. Yeah,

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how wild would that be? Like I said, I go, wow,

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I hope this actually happens. And he said, this should

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make everybody reconsider condoms, both male and female, don't you know,

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think about condoms? And he goes part of the spread

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of this part of this that we're seeing. I think

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he's I thought, he said, I'm going to say a

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stat here and maybe I'm wrong. I have not double checked.

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This is sixty percent of something? No, such a smartest

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nice I think it was thirty five percent increase over

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the number of years, which, when you look at it, okay,

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not that that big. I mean I think yesterday, by

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the way, I may have misspoken. I think when I

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said that the uh Jake paulm like Tyson fight, I said,

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Jake Pauling hit twenty eight percent. I think most boxers

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on average hit thirty five connect with thirty five percent

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of their punches. Overall, elite boxers will hit forty percent.

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He was twenty eight, but I was trying to shit them.

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Speaker 3: But hey, thirty five is almost half a sixty nine,

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So yes, it is.

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Speaker 2: That's very true. That's true. But I mean, you know,

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he was pretty close in his percentage. But yeah, I

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was surprised at the number of people. And he said

329
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that a lot of it has to do with hookup apps, right,

330
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You've got Tinder and things. People will hook up, have

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a one night stand and never think about that person

332
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again and maybe have an STD and either not realize

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it or ignore the symptoms. I mean, look, we can

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say all the time, hey, we've had, you know, how

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could you not know? Right? There are times where we

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look at somebody and go, how could you not know

337
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that you have something like this? How? Right? We think

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of all the symptoms. We've had people sit here on

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the podcast at this table and tell us about things

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that they've been living with that they thought were ABC

341
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or D before they found out it was E, F

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and G. Right. You know, like Laura for example, Right,

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she thought that she was just tired working too much,

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you know, stress maybe with the kids.

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Speaker 3: And also when you go to the doctor, cancer and

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tour is usually not the first thing. Especially you wouldn't

347
00:17:12,759 --> 00:17:14,839
go to it's a pinch nerve, or it's this, or

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it's that. And then when it continues, then they start

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looking at other things and that's you know, it's usually

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down the road where you're getting that, oh you got

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a tumor?

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Speaker 2: Yes, And I think a lot. I think many times

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when you present as a healthy adult, right, it comes

354
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in with no priors that all of a sudden. I mean,

355
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Laura told us she was gaining weight. I couldn't tell,

356
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but she said, you know, she knows her body. And

357
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she started to play her boyfriend for eating cheesy fries

358
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and garbage plates, and she would have some of that

359
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when he was around. Right, she thought it was that

360
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and it wasn't. It turned out that she had a

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medical condition that thankfully has been dealt with and all.

362
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But you know, how long did she go? Right? How

363
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long did she go before? She didn't know? So that's

364
00:17:58,359 --> 00:18:01,160
the only thing I would say is uh, the virologist

365
00:18:01,240 --> 00:18:03,119
kind of taught me. Today's like, you may want to

366
00:18:03,160 --> 00:18:06,160
pay attention to things. Wrap it up if you're if

367
00:18:06,200 --> 00:18:10,160
you're going on the app, well, all those dumb sayings

368
00:18:10,160 --> 00:18:12,319
that we used to do and we thought were funny,

369
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no glove, no love, all the dumb well, yeah, what

370
00:18:17,000 --> 00:18:20,480
was it? Uh, don't be dumber? Put a Robert. No,

371
00:18:20,640 --> 00:18:23,000
it wasn't. There was something, but there was all these

372
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different sayings that we used to say and we think

373
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they were so cool. And there was like a list

374
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of them, like Kevin's gonna find it on the internet

375
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because some tool put it up there. But if you

376
00:18:31,799 --> 00:18:35,039
are single or even in you know what, you know,

377
00:18:35,079 --> 00:18:39,200
what I'm seeing more and more of is open relationships.

378
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I'm reading more about. We had a woman on the

379
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podcast who has an open marriage and she likes to

380
00:18:44,720 --> 00:18:47,519
go on dates with somebody else because she doesn't have

381
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to talk about her kids and they're kind of get

382
00:18:50,039 --> 00:18:52,680
down to the nitty gritty of life with her husband.

383
00:18:52,799 --> 00:18:54,079
What do you found them?

384
00:18:54,279 --> 00:18:58,079
Speaker 3: Cover your stump before you hump, before you attacker, Wrap

385
00:18:58,119 --> 00:18:58,640
your whacker.

386
00:19:01,880 --> 00:19:03,559
Speaker 2: We should get a teach hope be a loaner.

387
00:19:03,680 --> 00:19:04,480
Speaker 3: Cover your boner.

388
00:19:04,720 --> 00:19:09,519
Speaker 2: We should get that's my favorite.

389
00:19:09,720 --> 00:19:11,920
Speaker 3: If you're not going to second go home and whack it.

390
00:19:13,079 --> 00:19:15,880
Speaker 2: I think that we should get his bilified T shirt

391
00:19:15,920 --> 00:19:18,359
with all those on the back and see if people

392
00:19:18,400 --> 00:19:21,680
will actually wear it. But it makes you realize that

393
00:19:21,759 --> 00:19:27,960
we've become pretty lax, right And I would think there's

394
00:19:27,960 --> 00:19:30,839
a cure for ags. There's not. They have ways of

395
00:19:31,000 --> 00:19:34,480
managing it, but it never goes away. You have it forever.

396
00:19:34,599 --> 00:19:37,599
So Magic Johnson who's gone on to have a long

397
00:19:37,680 --> 00:19:42,400
life with HIV has had it managed. But boy, you

398
00:19:42,519 --> 00:19:44,599
hope to be that lucky, right, you know you hope

399
00:19:44,640 --> 00:19:46,440
to be that lucky. All Right, we'll take a moment

400
00:19:46,559 --> 00:19:50,839
and we'll get ready for the AI guys Cody Brendan

401
00:19:51,000 --> 00:19:53,960
and Brendan Fraser coming in right after this.

402
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Speaker 3: Wrap it and foiled for your checker oil.

403
00:19:56,119 --> 00:20:00,000
Speaker 2: Mack of all trades has the perfect gift for the holiday,

404
00:20:01,119 --> 00:20:04,559
getting the to do list done right? Wouldn't that be

405
00:20:04,559 --> 00:20:07,759
great for your spouse, maybe helping him out, maybe getting

406
00:20:07,799 --> 00:20:10,000
her off your back, I don't know, maybe getting him

407
00:20:10,039 --> 00:20:12,640
off your back or her off I don't whatever. But

408
00:20:12,759 --> 00:20:14,400
just think how many times have you walked into your

409
00:20:14,400 --> 00:20:18,400
own home and God, God, I just wish I could

410
00:20:18,400 --> 00:20:21,599
get this room painted. Or I don't know how that

411
00:20:21,720 --> 00:20:24,599
wall mysteriously got a hole in it, but I wish

412
00:20:24,599 --> 00:20:26,839
I could get it fixed, Or I wish I could

413
00:20:26,960 --> 00:20:30,960
just get this bathroom renovated. I'm so tired of whatever.

414
00:20:31,559 --> 00:20:34,359
Mac can make all that happen. What a great look.

415
00:20:34,400 --> 00:20:36,440
It's a it's a gift for both of you, But

416
00:20:36,480 --> 00:20:39,160
think about that. It would just doesn't when your house

417
00:20:39,519 --> 00:20:43,400
is the way you want it, organize, clean, looking the

418
00:20:43,400 --> 00:20:47,039
way you like, don't you just feel better? Yeah? Well,

419
00:20:47,319 --> 00:20:50,480
so it's an ongoing gift. It's a gift for the

420
00:20:50,640 --> 00:20:54,559
entire family. Mac of All Trades five A five two

421
00:20:54,640 --> 00:20:56,960
zero two ninety two eighteen. That's five eight five two

422
00:20:57,039 --> 00:20:59,480
zero two ninety two eighteen for Mac of All Trades.

423
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You can see all the work they do on their

424
00:21:01,240 --> 00:21:04,400
website is fantastic. It's called Mac of All Trades dot net.

425
00:21:04,440 --> 00:21:07,440
That's Mac of all Trades dot net. Give the gift,

426
00:21:07,880 --> 00:21:10,799
give the gift of getting it done. I like that

427
00:21:11,039 --> 00:21:13,640
Mac of all Trades getting it done. Maybe that should

428
00:21:13,640 --> 00:21:16,079
become their slogan, Mac of all Trades giving you a

429
00:21:16,119 --> 00:21:19,960
gift this holiday season of getting it done five eight

430
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five two zero two ninety two eighteen and online at

431
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macaf all trades dot net. Feeling achy Tired of popping

432
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433
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434
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435
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436
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437
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438
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439
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440
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dot com. They'll even deliver to your door. MJ Dispensary

441
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nine hundred Jefferson Road and Henrietta. They've got what you

442
00:21:59,240 --> 00:22:16,200
need to live better and maybe smile a little more too. Actually,

443
00:22:16,200 --> 00:22:20,279
nobody knows this song. Oh wait, thought it was Sticks

444
00:22:20,279 --> 00:22:21,759
for a second. Oh you got it?

445
00:22:21,799 --> 00:22:22,680
Speaker 3: Is it, mister Roboti?

446
00:22:22,720 --> 00:22:26,279
Speaker 2: If he nailed it? Yeah, I know my eighties. This

447
00:22:26,319 --> 00:22:30,559
is eighties rock, eighties AI rock. Right, it's about the future,

448
00:22:31,680 --> 00:22:36,440
all right, mister Roboto. Nobody got that Rogotto. I don't

449
00:22:36,440 --> 00:22:36,960
know what it was.

450
00:22:41,200 --> 00:22:43,480
Speaker 3: I don't know what I got, bust out.

451
00:23:01,160 --> 00:23:03,640
Speaker 2: I think the B side of this was snowblind by

452
00:23:04,240 --> 00:23:06,119
last One.

453
00:23:06,200 --> 00:23:08,839
Speaker 3: Buddy's favorite Stick song is snow Blinds.

454
00:23:09,160 --> 00:23:15,839
Speaker 2: It is absolutely that maybe Chap this is when we

455
00:23:15,880 --> 00:23:18,079
would fear Japan and all the things that are going

456
00:23:18,079 --> 00:23:22,160
on my AI. I have said many times, Uh, you

457
00:23:22,160 --> 00:23:24,319
can't put that genie back in the bottle, So find

458
00:23:24,319 --> 00:23:28,200
a way to embrace it. Things like chat GPT. If

459
00:23:28,240 --> 00:23:31,000
you have the ideas, it can polish up your writing,

460
00:23:31,440 --> 00:23:34,839
it can help you create something of a calendar. I

461
00:23:34,880 --> 00:23:36,839
think it probably can do way more than I'm even

462
00:23:37,000 --> 00:23:40,400
thinking about. There's many AI things. What we what we

463
00:23:40,400 --> 00:23:44,559
should play with tonight is the AI songwriting software that

464
00:23:44,680 --> 00:23:46,759
you give it prompts up to two hundred characters and

465
00:23:46,799 --> 00:23:49,000
I'll write a song within thirty seconds.

466
00:23:48,759 --> 00:23:50,559
Speaker 3: Or the ones that we can get some nice interviews

467
00:23:50,599 --> 00:23:52,119
from like Tiger Woods.

468
00:23:51,799 --> 00:23:54,000
Speaker 2: Or yeah, you get the voices and all that kind

469
00:23:54,000 --> 00:23:57,920
of stuff, which is a little scary, but uh, Cody

470
00:23:57,960 --> 00:24:02,720
Brendan and Brendan Fraser, the actor who was in many movies. No,

471
00:24:02,920 --> 00:24:04,680
do you get that a lot because spelled differently the

472
00:24:04,720 --> 00:24:05,319
last name.

473
00:24:05,279 --> 00:24:06,599
Speaker 4: All the time, all the time.

474
00:24:07,279 --> 00:24:10,640
Speaker 2: But you guys are AI. So let's start with here,

475
00:24:11,079 --> 00:24:14,240
what what is your company? What are you guys doing

476
00:24:14,279 --> 00:24:16,720
with AI? And then we'll ask all the scary questions

477
00:24:16,720 --> 00:24:17,000
about it.

478
00:24:17,240 --> 00:24:20,200
Speaker 5: That's great questions, lots of them. So we are Rock

479
00:24:20,240 --> 00:24:25,359
AI obviously Rochester AI. We basically take AI at all

480
00:24:25,440 --> 00:24:27,640
levels and we try to implement it. We're kind of

481
00:24:27,640 --> 00:24:32,759
like glorified AI consultants, but we understand AI very well.

482
00:24:33,079 --> 00:24:34,799
Speaker 6: So businesses that need.

483
00:24:34,720 --> 00:24:38,279
Speaker 5: Specific needs, we're taking AI models and training them for

484
00:24:38,359 --> 00:24:39,440
exactly what they need.

485
00:24:40,039 --> 00:24:42,559
Speaker 2: So it's give me an example of what like when

486
00:24:42,880 --> 00:24:45,680
you say that, like, what what kind of business are

487
00:24:45,680 --> 00:24:48,359
we talking about? Let's say it's honestly software writing.

488
00:24:49,000 --> 00:24:51,000
Speaker 6: Yeah, there's a lot of software writer.

489
00:24:51,079 --> 00:24:53,119
Speaker 5: You can use tools to help you write software, but

490
00:24:53,160 --> 00:24:56,799
more specifically, we're building tools to help automate you know,

491
00:24:56,920 --> 00:25:02,319
data analytics or other factors thatusinesses need. You know, they

492
00:25:02,640 --> 00:25:06,000
take their CRM and we design a product that's going

493
00:25:06,039 --> 00:25:11,359
to implement with the API and essentially make their flow,

494
00:25:11,880 --> 00:25:13,920
you know, one hundred percent more efficient.

495
00:25:14,160 --> 00:25:17,759
Speaker 2: Okay, So, and how do people find you guys?

496
00:25:18,359 --> 00:25:21,839
Speaker 5: Well, right now, we're kind of new, So we've been

497
00:25:22,079 --> 00:25:24,279
we've been getting a lot of traction. We actually have

498
00:25:24,559 --> 00:25:27,000
some events coming up that we'll get to eventually. But

499
00:25:27,799 --> 00:25:30,440
we have a LinkedIn page, we have a page on

500
00:25:30,480 --> 00:25:33,240
Facebook right now. It's been a lot of word of mouth.

501
00:25:33,240 --> 00:25:34,279
You know, we know a lot of people. I know

502
00:25:34,319 --> 00:25:37,319
a lot of people. So we've been talking with countless

503
00:25:37,319 --> 00:25:41,079
companies in Rochester just kind of seeing what their needs are,

504
00:25:41,160 --> 00:25:43,200
teaching them about AI, you know, how to bring them

505
00:25:43,200 --> 00:25:46,839
to the next level, how to use it, how to

506
00:25:47,279 --> 00:25:50,319
you know, use an enterprise model and not put secure

507
00:25:50,400 --> 00:25:54,680
data right right right right shouldn't really be but you

508
00:25:54,720 --> 00:25:58,559
know that's I'm more of the business guy. My business partner,

509
00:25:58,559 --> 00:26:00,519
Brendan here, he's he's the I spot last he was

510
00:26:00,519 --> 00:26:02,799
actually the first name detector of marketing and AI in

511
00:26:02,839 --> 00:26:03,839
the country about two yars ago.

512
00:26:03,920 --> 00:26:05,599
Speaker 2: Wait a second, how with with whom?

513
00:26:06,359 --> 00:26:10,000
Speaker 4: Uh so? I work with a group perching organization.

514
00:26:10,559 --> 00:26:12,880
Speaker 2: But get right in that micro front Uh.

515
00:26:13,000 --> 00:26:17,079
Speaker 4: Yeah. So I was fortunate enough to be the company

516
00:26:17,079 --> 00:26:20,519
that kind of took me my word of like AI

517
00:26:20,640 --> 00:26:23,480
is huge. We need to be the frontier of this,

518
00:26:23,759 --> 00:26:26,240
like we need to implement it in all stages of

519
00:26:26,240 --> 00:26:29,039
our business, make our employees more efficient, because if we don't,

520
00:26:29,079 --> 00:26:31,240
the competition is gonna gonna do it first and then

521
00:26:31,240 --> 00:26:34,079
beat us. And they took that as seriously as they

522
00:26:34,119 --> 00:26:36,200
should have, and we were able to make.

523
00:26:36,039 --> 00:26:38,720
Speaker 2: Our what what is your do you love AI? Yeah?

524
00:26:38,960 --> 00:26:39,279
You do.

525
00:26:39,400 --> 00:26:42,200
Speaker 4: The day it came out, my life changed it just

526
00:26:42,960 --> 00:26:45,359
I got to use it, see what it was capable of.

527
00:26:45,960 --> 00:26:48,640
At the time, I was the head of marketing for

528
00:26:49,000 --> 00:26:54,240
a different company than what I'm with now. But marketing

529
00:26:54,279 --> 00:26:57,480
and AI at the beginning especially, yeah, went hand in

530
00:26:57,519 --> 00:26:59,680
hand so well because I could just say, hey, write

531
00:26:59,680 --> 00:27:02,319
a blow post on this topic and it would just

532
00:27:02,319 --> 00:27:05,720
do it instantaneously. And this is before everybody is doing that,

533
00:27:05,759 --> 00:27:08,680
like obviously every kind of marketing department and do something

534
00:27:08,839 --> 00:27:09,160
doing that.

535
00:27:09,319 --> 00:27:09,559
Speaker 2: Yeah.

536
00:27:09,599 --> 00:27:11,680
Speaker 4: Now, so it's not as effective as it was then,

537
00:27:11,720 --> 00:27:14,960
but when the day came out, groundbreaking. You could have

538
00:27:15,599 --> 00:27:18,440
six months worth of stuff done in a weekend. Whereas

539
00:27:18,480 --> 00:27:22,200
before you need an entire team drafting, writing and taking

540
00:27:22,240 --> 00:27:24,720
all this time just to pull out, you know, six

541
00:27:24,759 --> 00:27:27,680
months worth of blog posts. And that's just one example.

542
00:27:27,680 --> 00:27:28,960
You can create entire social.

543
00:27:28,799 --> 00:27:31,839
Speaker 2: Media campaigns right calendars, everything.

544
00:27:31,680 --> 00:27:35,559
Speaker 4: Calendar's campaigns, literally you name it. It was amazing at it.

545
00:27:35,680 --> 00:27:38,880
Speaker 2: So what do you say to people that are somewhat

546
00:27:39,119 --> 00:27:42,240
hesitant or scared? And we hear about like jobs are

547
00:27:42,240 --> 00:27:44,400
going to go away or this is gonna go away,

548
00:27:44,440 --> 00:27:48,440
and I often think I don't know that jobs are

549
00:27:48,480 --> 00:27:50,519
going to go away because I still think like the

550
00:27:50,559 --> 00:27:55,799
ideas are there. I read something where Ben Affleck, who

551
00:27:55,799 --> 00:27:58,839
I've always thought was a really bright guy. Don't forget

552
00:27:58,960 --> 00:28:01,519
he was twenty five years old when he wrote you know,

553
00:28:01,559 --> 00:28:06,319
Goodwill Hunting, or co wrote Goodwill Hunting and won the

554
00:28:06,359 --> 00:28:10,759
Oscar for Best Screenplay. He was at the Delivering Alpha

555
00:28:10,799 --> 00:28:14,720
twenty twenty four in I think it's their investors summit,

556
00:28:14,880 --> 00:28:17,839
whatever it was, and he was saying that, you know,

557
00:28:18,440 --> 00:28:21,480
when it comes to acting and things, it's not going

558
00:28:21,559 --> 00:28:23,559
to be replaced by AI because it doesn't have the

559
00:28:23,599 --> 00:28:26,519
emotional intelligence and it doesn't have the emotion to get

560
00:28:26,519 --> 00:28:32,640
that it can write you an excellent imitative Elizabethan play,

561
00:28:32,720 --> 00:28:35,759
but it can't be Shakespeare was kind of his point,

562
00:28:36,359 --> 00:28:40,640
and I just thought it. I go, you take the

563
00:28:40,799 --> 00:28:43,960
laborerst jobs, right, the things of editing and that sort

564
00:28:44,000 --> 00:28:47,640
of stuff. AI can shorten that for people and shorten

565
00:28:47,680 --> 00:28:50,599
the time. People keep saying, well, eventually we're going to

566
00:28:50,599 --> 00:28:53,839
see the first AI movie, no actors know anybody. It's

567
00:28:53,839 --> 00:28:58,079
going to be an entire AI story. AI think maybe maybe,

568
00:28:58,160 --> 00:29:00,079
but I don't think it'll do as well as something

569
00:29:00,119 --> 00:29:03,519
with real people. But it could help punch up a script.

570
00:29:03,799 --> 00:29:05,039
You may. I mean, there are guys and.

571
00:29:05,119 --> 00:29:06,680
Speaker 3: We kind of see that with Avatar, though.

572
00:29:07,599 --> 00:29:11,839
Speaker 2: Uh in terms of what it was like AI. Yes,

573
00:29:12,160 --> 00:29:15,200
I see what you're saying. But when I'm talking about

574
00:29:15,200 --> 00:29:17,839
like an entire different movie, like let's say any movie

575
00:29:18,079 --> 00:29:19,920
was like even Fight Club, all of a sudden you

576
00:29:19,920 --> 00:29:22,680
have AI actors and things is you just can't really

577
00:29:22,720 --> 00:29:25,319
replace that. But I go, boy, guys who are punch

578
00:29:25,400 --> 00:29:28,759
up writers. We may lose those guys. You may lose them.

579
00:29:28,960 --> 00:29:31,039
Speaker 5: That really helps them focus, you know, And that's where

580
00:29:31,079 --> 00:29:33,279
we take our pride in what we do because our

581
00:29:33,319 --> 00:29:36,960
whole goal behind you know, implementing AI and a business

582
00:29:36,960 --> 00:29:40,039
as efficiency right. Yeah, so we know, based off of

583
00:29:40,079 --> 00:29:42,920
many scales, like the Ruter scale, we're going to save

584
00:29:43,200 --> 00:29:46,000
an individual employee anywhere from four to twelve hours of

585
00:29:46,039 --> 00:29:47,519
productivity per week.

586
00:29:47,799 --> 00:29:48,359
Speaker 2: Yeah.

587
00:29:48,400 --> 00:29:50,200
Speaker 5: So you know what can you do with that time?

588
00:29:50,519 --> 00:29:53,359
You can actually focus on what's important. You can focus

589
00:29:53,400 --> 00:29:58,200
on what's next, So play video games, yeah, or video games.

590
00:29:58,000 --> 00:29:58,559
Speaker 2: You know what I mean.

591
00:29:58,680 --> 00:30:03,160
Speaker 3: You can't work the thirty two hour yeah.

592
00:30:02,240 --> 00:30:05,279
Speaker 5: But yeah if they utilize half that time appropriately. Now

593
00:30:05,319 --> 00:30:07,759
you're thinking, you know, bigger businesses that we talked to,

594
00:30:07,839 --> 00:30:11,200
we're talking about four or five two one thousand hours

595
00:30:11,240 --> 00:30:13,599
a week. You know, what is a business going to

596
00:30:13,640 --> 00:30:15,279
do with that time? You know, they could, you know,

597
00:30:15,359 --> 00:30:17,400
think outside the box. They can take themselves to the

598
00:30:17,400 --> 00:30:19,960
next level. But they already have a team. Nobody needs

599
00:30:20,000 --> 00:30:22,400
to get fired. You're just going to redirect you know,

600
00:30:22,720 --> 00:30:24,279
people in the right direction, and you're gonna be able

601
00:30:24,279 --> 00:30:25,160
to accomplish a lot more.

602
00:30:25,680 --> 00:30:31,440
Speaker 2: Well, what about like the biased AI. People fear that

603
00:30:31,799 --> 00:30:36,000
what AI is fed is what creates its knowledge. So

604
00:30:36,079 --> 00:30:38,759
now we could have biased AI. Do you what do

605
00:30:38,799 --> 00:30:40,119
you say to that kind of stuff?

606
00:30:40,240 --> 00:30:42,039
Speaker 4: So, I mean, you could take AI and say this

607
00:30:42,160 --> 00:30:44,279
bias all day long, But I mean, so is the internet, right,

608
00:30:44,319 --> 00:30:46,799
they could google something, it's whoever has the best SEO

609
00:30:46,920 --> 00:30:52,920
score is top. So whatever trend or whatever message they're

610
00:30:52,920 --> 00:30:53,480
trying to push.

611
00:30:53,519 --> 00:30:56,200
Speaker 2: How about things like lack of transparency would be another

612
00:30:56,200 --> 00:30:58,599
one that they've heard with AI, And I don't know exactly.

613
00:30:58,799 --> 00:31:01,480
Lack of transparencies come like a new buzzword to me,

614
00:31:01,599 --> 00:31:02,960
and I know what it means and we all do

615
00:31:03,079 --> 00:31:04,839
when I know, what people are saying is that you're

616
00:31:04,839 --> 00:31:07,359
not being authentic. You're kind of giving it, you know,

617
00:31:07,440 --> 00:31:09,759
holding one hand behind your back with something in it

618
00:31:09,759 --> 00:31:14,680
that I'm not aware of. But uh, I guess it

619
00:31:15,319 --> 00:31:19,160
kind of how companies using AI impacts them.

620
00:31:19,440 --> 00:31:21,319
Speaker 4: So, I mean, it depends on how you use it really.

621
00:31:21,440 --> 00:31:23,880
You know, you could have the YouTube channels that have

622
00:31:24,000 --> 00:31:27,240
their AI scripts with AI editing and like the person

623
00:31:27,279 --> 00:31:29,640
presses a button and then does that, but honestly, it's

624
00:31:29,720 --> 00:31:32,000
low quality. It's it's not going to stand out from

625
00:31:32,000 --> 00:31:34,960
the croub because, like you said earlier, yeah, it's a

626
00:31:35,000 --> 00:31:36,920
cookie cutter, right, you're not going to get that creative

627
00:31:36,960 --> 00:31:39,440
spark and people are gravitating more towards the human element

628
00:31:39,480 --> 00:31:42,960
of things. Now, you take that editing and say, okay,

629
00:31:43,000 --> 00:31:45,799
cool that this person that a one man YouTube show

630
00:31:46,799 --> 00:31:48,720
wants to create a script, has an idea of what

631
00:31:48,720 --> 00:31:50,960
he wants, but doesn't want to like spend hours and

632
00:31:50,960 --> 00:31:52,839
hours brainstorming. He wants to start with something and then

633
00:31:52,880 --> 00:31:54,799
build off of that mold it to what he wants.

634
00:31:55,319 --> 00:31:57,599
Like that just takes a huge amount of like work

635
00:31:57,640 --> 00:32:01,039
out of the early stages of that. So bias is

636
00:32:01,119 --> 00:32:03,839
what you make of it, and you can use AI

637
00:32:03,960 --> 00:32:07,000
as far as you want, but it's not going to

638
00:32:07,039 --> 00:32:09,319
go too far as in one direction or the other.

639
00:32:09,400 --> 00:32:11,440
I I've been using AI NonStop for that since the

640
00:32:11,480 --> 00:32:12,079
day came out.

641
00:32:12,599 --> 00:32:16,000
Speaker 2: And what do you what are you using all of them?

642
00:32:16,400 --> 00:32:18,039
All of them? What do you have a favorite?

643
00:32:18,160 --> 00:32:20,279
Speaker 4: So right now I will say the chat GPT is

644
00:32:20,319 --> 00:32:24,480
the favorite to talk about. Everybody knows that name. Claude

645
00:32:24,799 --> 00:32:28,240
is definitely superior to chat GPT in almost every single

646
00:32:28,240 --> 00:32:31,279
way except for at the enterprise level. So if you're

647
00:32:31,319 --> 00:32:33,640
not a big business paying big bucks for a higher

648
00:32:33,759 --> 00:32:37,759
level of chat GPT, Claude will be by far better

649
00:32:37,799 --> 00:32:38,839
for the average person.

650
00:32:39,200 --> 00:32:41,240
Speaker 2: Claude Yeah c l A U d E.

651
00:32:41,519 --> 00:32:42,200
Speaker 4: That's right, yep.

652
00:32:42,720 --> 00:32:44,319
Speaker 2: What does Claude do the same things?

653
00:32:44,400 --> 00:32:46,480
Speaker 4: It's it's almost the same exact thing as chat GPT,

654
00:32:46,640 --> 00:32:49,559
but the way it's trained, uh, and the and the

655
00:32:49,680 --> 00:32:53,200
writing style and the outputs that it gives are just

656
00:32:53,599 --> 00:32:57,160
on average higher quality than chatchpt.

657
00:32:57,680 --> 00:32:57,799
Speaker 7: Uh.

658
00:32:57,839 --> 00:33:00,240
Speaker 4: It's also much better at coding in my experience. And

659
00:33:00,400 --> 00:33:04,799
so a huge, huge, huge benefit of AI is coding.

660
00:33:04,920 --> 00:33:08,039
For anybody has coding, it's a very time consuming task. Yeah,

661
00:33:08,079 --> 00:33:11,640
even if you're great at it, this could code instantly

662
00:33:11,680 --> 00:33:14,240
for you. And maybe it's not perfect, but somebody's already

663
00:33:14,240 --> 00:33:15,119
good at coding.

664
00:33:15,079 --> 00:33:15,839
Speaker 2: You can pick it up.

665
00:33:15,960 --> 00:33:16,920
Speaker 6: Can oh I take it?

666
00:33:17,039 --> 00:33:17,279
Speaker 2: Yeah.

667
00:33:17,519 --> 00:33:20,079
Speaker 4: It's as if you had a an intern do it

668
00:33:20,119 --> 00:33:20,880
for you, all.

669
00:33:20,799 --> 00:33:23,000
Speaker 2: Right, right, right right, and then we just check check

670
00:33:23,079 --> 00:33:24,640
the work exactly. Yeah.

671
00:33:24,759 --> 00:33:29,400
Speaker 5: I literally built an app when one preview came out.

672
00:33:29,599 --> 00:33:31,599
I don't have any coding experience, and I built a

673
00:33:31,640 --> 00:33:34,759
working app. And it's really what it comes down to

674
00:33:34,880 --> 00:33:36,599
is just how you prompt it, right. You have to

675
00:33:36,599 --> 00:33:39,880
be good at prompt engineering. Yeah, So how you ask

676
00:33:39,960 --> 00:33:42,799
your questions and how you set the guidelines and the

677
00:33:42,799 --> 00:33:44,359
guard rails for what you're going to get out.

678
00:33:44,519 --> 00:33:46,759
Speaker 2: So, so saying let's say we wanted to build an

679
00:33:46,759 --> 00:33:49,720
app for this podcast, Yeah, what would we what would

680
00:33:49,759 --> 00:33:51,680
be the prompts? What would you say?

681
00:33:51,920 --> 00:33:53,839
Speaker 5: Well, first, obviously you have to if you don't many

682
00:33:53,839 --> 00:33:59,119
have experience, you have to by asking questions like how

683
00:33:59,160 --> 00:34:00,480
am I going to do that? It's like how am

684
00:34:00,480 --> 00:34:01,799
I going to build an app? It's going to tell

685
00:34:01,839 --> 00:34:06,519
you what programs to build it on? What like are

686
00:34:06,559 --> 00:34:08,519
you gonna use Electron? Are you gonna use JavaScript? What

687
00:34:08,599 --> 00:34:11,599
type of code are you going to actually use? So

688
00:34:11,800 --> 00:34:13,400
you can kind of teach yourself a little bit in

689
00:34:13,400 --> 00:34:15,519
the beginning, and then you can just dive right into it.

690
00:34:15,599 --> 00:34:17,719
You know, I obviously I don't know anything about coding,

691
00:34:17,719 --> 00:34:19,039
so I don't remember half of what.

692
00:34:19,000 --> 00:34:20,960
Speaker 6: It told me, but we did it together.

693
00:34:21,960 --> 00:34:24,719
Speaker 5: So I just basically set the guidelines on this is

694
00:34:24,800 --> 00:34:26,559
the type of app I want to build, What is

695
00:34:26,599 --> 00:34:29,199
the best platform I should put this on? At some

696
00:34:29,280 --> 00:34:32,079
point I want this to be on an iOS system,

697
00:34:32,119 --> 00:34:33,800
and at some point I want it to be on

698
00:34:33,840 --> 00:34:37,239
an Android system. So it basically gave me all the

699
00:34:37,280 --> 00:34:40,119
inputs that I need for This is your base work.

700
00:34:40,159 --> 00:34:41,639
This is where you're going to build it. These are

701
00:34:41,719 --> 00:34:43,400
dig you are going to use, and then you can start

702
00:34:43,440 --> 00:34:46,880
actually building code and plugging and playing and then at

703
00:34:46,920 --> 00:34:50,039
a certain point, like it's it's not perfect right, so

704
00:34:50,400 --> 00:34:53,159
you might get something that's not right. But I literally

705
00:34:53,159 --> 00:34:55,239
copied and pasted what wasn't right, put it back in

706
00:34:55,360 --> 00:34:56,440
and said why isn't this right?

707
00:34:57,000 --> 00:34:58,880
Speaker 6: And it shot, this is your mistake.

708
00:34:59,079 --> 00:35:03,480
Speaker 2: Try this Wow, and it actually built you the app

709
00:35:03,280 --> 00:35:04,880
a day and a half.

710
00:35:04,960 --> 00:35:05,840
Speaker 6: Yeah it works.

711
00:35:06,079 --> 00:35:08,920
Speaker 2: Yeah really Yeah, So on like a weekend, you could

712
00:35:08,920 --> 00:35:09,679
build an app.

713
00:35:10,079 --> 00:35:12,760
Speaker 8: Something that would take a team at least a week.

714
00:35:12,960 --> 00:35:16,400
Speaker 2: Okay, me a week. But but but you Drink.

715
00:35:17,000 --> 00:35:18,840
Speaker 5: Is just a base app with a you know, I

716
00:35:18,880 --> 00:35:20,880
would I can't really get in this specifically app.

717
00:35:20,719 --> 00:35:25,920
Speaker 2: Because it's but don't cost like ten grand if I

718
00:35:26,000 --> 00:35:27,440
hired somebody.

719
00:35:27,639 --> 00:35:30,920
Speaker 4: So for maybe an easier example than the one we're

720
00:35:30,960 --> 00:35:35,840
working on ourselves. When chat ChiPT first came on, I

721
00:35:36,000 --> 00:35:38,480
was interested to see if I could code an Android app,

722
00:35:38,840 --> 00:35:42,000
and I decided to recreate Flatbybird. And a lot of

723
00:35:42,000 --> 00:35:44,159
people have done this now I've seen you can find

724
00:35:44,239 --> 00:35:47,039
videos on a YouTube of just creating flatby Bird with

725
00:35:47,079 --> 00:35:49,480
AI and then saying I want to code flappy bird.

726
00:35:49,480 --> 00:35:50,519
I want to make that app and put on the

727
00:35:50,519 --> 00:35:53,079
App Store and it does it and then sometimes it'll

728
00:35:53,079 --> 00:35:54,920
just bounce up and down and the screen won't go

729
00:35:54,960 --> 00:35:57,280
to the side and whatever, and then you say, okay,

730
00:35:57,320 --> 00:35:58,960
this isn't working, and then it fixes it, and then

731
00:35:59,199 --> 00:36:00,639
you keep going back and forth until you have a

732
00:36:00,639 --> 00:36:04,119
functional app. And that was right at the beginning, and

733
00:36:04,159 --> 00:36:06,920
it's been a few years now and it's only gotten

734
00:36:07,400 --> 00:36:10,400
exponentially better. So, yeah, the apps that people can make,

735
00:36:10,519 --> 00:36:12,639
like I saw one that this guy made, but.

736
00:36:12,639 --> 00:36:15,280
Speaker 2: That does sound scary? Does it not a little bit?

737
00:36:15,679 --> 00:36:18,039
Speaker 4: In my opinion, it's fascinating and it also gives it

738
00:36:18,079 --> 00:36:20,920
is fascinating that people like, there's this guy who was

739
00:36:20,960 --> 00:36:23,760
finding it frustrating that he couldn't just like type in

740
00:36:23,960 --> 00:36:26,400
I ate this and how many calories did I have

741
00:36:26,480 --> 00:36:29,079
and all this, So he created an app with AI

742
00:36:29,280 --> 00:36:33,159
like an actual website, but it was an application as well,

743
00:36:33,159 --> 00:36:36,119
like a web app, and you could just type in

744
00:36:36,840 --> 00:36:39,280
exactly what you ate that day, and then it pulled

745
00:36:39,320 --> 00:36:43,440
all of the foods, yeah, restaurant, and then says, okay,

746
00:36:43,519 --> 00:36:45,440
here's what like your ask me to calories for the day.

747
00:36:45,440 --> 00:36:47,280
And he just did that in a weekend because he

748
00:36:47,320 --> 00:36:49,960
felt like it couldn't find something that did that as

749
00:36:50,000 --> 00:36:50,880
well as he wanted it to.

750
00:36:51,199 --> 00:36:54,320
Speaker 2: You know, what Kevin. I always say that what the.

751
00:36:54,400 --> 00:36:57,559
Speaker 3: Barrier to entry, It's gone, right, it's lower.

752
00:36:57,679 --> 00:37:00,039
Speaker 4: I mean now it's the creative mind. And yeah, and

753
00:37:00,159 --> 00:37:03,840
AI can support that creative mind, yes, if you're using

754
00:37:03,880 --> 00:37:07,480
it right or it could be abused. And people can.

755
00:37:07,159 --> 00:37:09,880
Speaker 2: Talk to me about a big concern, a big thing

756
00:37:09,920 --> 00:37:15,000
that people talk about today, cybersecurity. Do we worry about cybersecurity?

757
00:37:15,000 --> 00:37:15,400
With AI?

758
00:37:16,199 --> 00:37:20,320
Speaker 5: In getting I mean, honestly, it takes everything to the

759
00:37:20,360 --> 00:37:24,079
next level, right, So you know, I own another business,

760
00:37:24,480 --> 00:37:26,239
which is one of the reasons that all this started.

761
00:37:26,280 --> 00:37:29,199
Speaker 8: We went to a big conference in August called AI.

762
00:37:29,039 --> 00:37:31,760
Speaker 2: Four also a bunch of nerds.

763
00:37:31,800 --> 00:37:34,760
Speaker 5: Oh, exactly about five thousand nerds. Wow, exact, it was

764
00:37:34,760 --> 00:37:37,519
actually five thousand of the top companies in the world.

765
00:37:37,639 --> 00:37:41,480
Wonder there was some pretty awesome girls there.

766
00:37:43,639 --> 00:37:47,880
Speaker 8: And they're smart. But cybersecurity.

767
00:37:47,960 --> 00:37:51,679
Speaker 5: I specifically went for cybersecurity to see what type of

768
00:37:51,679 --> 00:37:55,880
programs we could utilize. We do government contracting, so we

769
00:37:55,960 --> 00:37:58,199
do a lot of data analytics and intel. So from

770
00:37:58,239 --> 00:38:00,840
a cybersecurity standpoint, we were looking at ways to automate

771
00:38:00,880 --> 00:38:04,159
cybersecurity and use AI to you know, kind of cut

772
00:38:04,159 --> 00:38:07,559
the middleman out without getting really into it. And there

773
00:38:07,559 --> 00:38:11,599
are multiple companies that are dedicated to specifically that that

774
00:38:11,719 --> 00:38:14,239
already have contracts with the government that actually handle a

775
00:38:14,280 --> 00:38:15,519
lot of our cybersecurity.

776
00:38:16,000 --> 00:38:17,760
Speaker 6: So as you use it for.

777
00:38:17,679 --> 00:38:21,119
Speaker 5: Cybersecurity and pen testing ways or you know, just standard

778
00:38:21,320 --> 00:38:25,039
you know, operations, you can use it for a good

779
00:38:25,039 --> 00:38:27,559
and bad. So at this point, you know the good

780
00:38:27,559 --> 00:38:28,480
and the bad also grow.

781
00:38:28,599 --> 00:38:31,159
Speaker 2: Well, we can be good and bad. There's always that.

782
00:38:31,239 --> 00:38:34,519
I always joke if somebody would use their powers for

783
00:38:34,800 --> 00:38:37,719
good instead of evil, right like the guy who came

784
00:38:37,800 --> 00:38:40,199
up to the skimmer at the gas station, that was

785
00:38:40,280 --> 00:38:42,440
an easy task to do. No, I think you got

786
00:38:42,480 --> 00:38:44,159
a lot of work to get it that small to

787
00:38:44,199 --> 00:38:45,360
go in the thing, you know what I mean?

788
00:38:45,880 --> 00:38:48,760
Speaker 3: You know, I don't know if you talk about people

789
00:38:48,760 --> 00:38:51,440
putting out nonsense like we love nonsense, what kind of

790
00:38:51,480 --> 00:38:52,719
nonsense are people putting out?

791
00:38:52,800 --> 00:38:56,079
Speaker 4: Well, you could just have a generate like a buzzword

792
00:38:56,280 --> 00:39:00,639
heavy article, but make it seo like for a particular

793
00:39:01,039 --> 00:39:03,440
keyword or key phrase, so that when people google itt,

794
00:39:03,440 --> 00:39:06,679
this article shows up pretty high up Google's.

795
00:39:06,840 --> 00:39:09,079
Speaker 2: That's we need to put on billified.

796
00:39:09,199 --> 00:39:13,000
Speaker 4: Well, I mean, I mean, look at journalism these days, right,

797
00:39:13,000 --> 00:39:13,760
like people, Now.

798
00:39:13,880 --> 00:39:15,840
Speaker 2: Dare you I understand.

799
00:39:15,880 --> 00:39:17,639
Speaker 4: I know you're saying there's a lot of there's a

800
00:39:17,639 --> 00:39:19,760
lot of bad and there's some good, and it's it's

801
00:39:19,760 --> 00:39:21,599
harder to find the good these days. In my opinion,

802
00:39:22,000 --> 00:39:23,679
it's a lot. It's pretty easy to find an article

803
00:39:23,679 --> 00:39:25,119
that you can almost tells written.

804
00:39:24,840 --> 00:39:29,000
Speaker 2: By a So how does somebody use AI, Let's say

805
00:39:29,679 --> 00:39:34,679
an individual who Another popular thing we hear about nowadays

806
00:39:35,360 --> 00:39:37,960
is side hustle? Right, do we not? Right?

807
00:39:38,360 --> 00:39:40,679
Speaker 4: That's the whole category by itself.

808
00:39:40,719 --> 00:39:43,599
Speaker 2: It's a whole category by itself. But can AI help you?

809
00:39:44,039 --> 00:39:48,239
There's uh, I'll get fed ads on Instagram for is

810
00:39:48,320 --> 00:39:52,480
a cursive course of c O U R S I V.

811
00:39:52,760 --> 00:39:53,280
Speaker 6: I've seen it?

812
00:39:53,320 --> 00:39:55,320
Speaker 8: Have you seen this I do with AI on Facebook

813
00:39:55,360 --> 00:39:56,760
so much? Yeah, as all the time.

814
00:39:56,800 --> 00:39:59,000
Speaker 2: It's they give you like you got to master all

815
00:39:59,000 --> 00:39:59,800
these different.

816
00:39:59,519 --> 00:40:02,679
Speaker 8: Thirty different at different day and you're going to do.

817
00:40:02,679 --> 00:40:07,480
Speaker 2: This yes, And I go, okay, obviously maybe maybe I'm

818
00:40:07,480 --> 00:40:08,400
not putting the time in.

819
00:40:08,480 --> 00:40:10,519
Speaker 5: Maybe And that's their take on it, and you know that,

820
00:40:10,639 --> 00:40:13,320
and that's kind of you know, from a business aspect,

821
00:40:13,360 --> 00:40:15,519
why what we really do and what we specialize in,

822
00:40:15,559 --> 00:40:17,760
you know, chat, TBT, claude and using it that.

823
00:40:17,920 --> 00:40:18,599
Speaker 6: That's one thing.

824
00:40:18,639 --> 00:40:21,599
Speaker 5: But when you start to actually get into l MS

825
00:40:21,639 --> 00:40:25,920
and things that you know, manage your calendars or magic

826
00:40:25,960 --> 00:40:26,920
cell spreadsheets.

827
00:40:27,000 --> 00:40:29,800
Speaker 3: Wait what he said calendar about four times? You should

828
00:40:29,800 --> 00:40:31,840
start taking some interest in that too, there, pumpkin, I.

829
00:40:31,760 --> 00:40:33,639
Speaker 2: Have my calendar. I was looking at my calendar.

830
00:40:33,639 --> 00:40:35,440
Speaker 5: Do they have a great partner out of Armenia that

831
00:40:35,480 --> 00:40:37,119
could help you out with your calendar? Out of it

832
00:40:37,199 --> 00:40:41,360
a bit Armenia, the Project Management Artificial Intelligence.

833
00:40:41,599 --> 00:40:45,920
Speaker 2: We're all around the world, your global global global what

834
00:40:46,039 --> 00:40:49,039
is so what is the name of the company? Your company?

835
00:40:49,239 --> 00:40:50,400
Speaker 6: Our company is rock AI.

836
00:40:50,639 --> 00:40:53,599
Speaker 2: Rock AI already forgive me, I was drinking before this,

837
00:40:55,000 --> 00:40:58,760
but the rock AI and what do you what are

838
00:40:58,760 --> 00:40:59,440
you offering?

839
00:40:59,679 --> 00:41:05,119
Speaker 5: So we're offering consultation services to businesses, you know, helping

840
00:41:05,159 --> 00:41:07,559
them understand what they might need, what products are on

841
00:41:07,599 --> 00:41:08,039
the market.

842
00:41:08,119 --> 00:41:11,599
Speaker 2: Yeah, because you could spend hours trying to test things

843
00:41:11,719 --> 00:41:14,119
that aren't going to work for you. Find the experts

844
00:41:14,119 --> 00:41:15,920
that actually know exactly.

845
00:41:15,599 --> 00:41:17,440
Speaker 6: And if there's nothing off the shelf.

846
00:41:17,800 --> 00:41:20,199
Speaker 5: That's where we get a little bit deeper into it

847
00:41:20,239 --> 00:41:24,440
and we actually build a custom model for their needs.

848
00:41:24,800 --> 00:41:27,079
So you know, we can actually train our own data.

849
00:41:27,199 --> 00:41:29,320
You know, I'm working on when I own an HVAC company.

850
00:41:29,559 --> 00:41:33,760
So right now I'm actually making a program trained off

851
00:41:33,800 --> 00:41:39,039
of industry specific data to help technicians diagnose problems that

852
00:41:39,079 --> 00:41:42,239
they have right right, So you know, if you have

853
00:41:42,320 --> 00:41:45,480
data that's pertinent to your industry, you can train everything

854
00:41:45,519 --> 00:41:48,119
off of it and make whatever type of app you'd

855
00:41:48,199 --> 00:41:50,960
like or implement it behind an app that you are

856
00:41:51,000 --> 00:41:53,800
to use to give it that much more power and

857
00:41:54,159 --> 00:41:54,519
give you.

858
00:41:54,440 --> 00:41:55,559
Speaker 6: That much more of a resource.

859
00:41:55,599 --> 00:41:57,440
Speaker 5: So if you have a question, say I'm working on

860
00:41:57,480 --> 00:42:01,320
this product, help it's doing this. It's giving an error code,

861
00:42:01,800 --> 00:42:05,760
and you can use these resources that we trained, you know, PDFs, data,

862
00:42:05,920 --> 00:42:08,800
raw data, and it'll instantly find it and instantly give

863
00:42:08,800 --> 00:42:09,400
you an answer.

864
00:42:09,920 --> 00:42:12,360
Speaker 2: And this would be chat, chipeach or claude. I could

865
00:42:12,360 --> 00:42:13,079
put that into.

866
00:42:13,320 --> 00:42:15,599
Speaker 5: No, this is actually something custom to you. So it's

867
00:42:15,599 --> 00:42:16,559
a program that we build.

868
00:42:16,559 --> 00:42:17,840
Speaker 2: We have you guys built.

869
00:42:17,880 --> 00:42:19,880
Speaker 6: Yeah, we actually build out forgive me, this.

870
00:42:19,960 --> 00:42:25,079
Speaker 3: Is your dad forty years but now he's getting it's

871
00:42:25,119 --> 00:42:27,079
not gonna be good enough construction that's going to be

872
00:42:27,280 --> 00:42:28,679
right right exactly.

873
00:42:29,679 --> 00:42:36,199
Speaker 4: So another good point. Ye yeah, another aspect of uh

874
00:42:36,639 --> 00:42:40,000
like actual like business owners like that we talked to

875
00:42:40,440 --> 00:42:43,559
A huge thing that they say is I don't even

876
00:42:43,599 --> 00:42:46,800
know where to begin. They're almost intimidated by it. And

877
00:42:47,519 --> 00:42:53,320
we have partners like in every single sector of artificial intelligence,

878
00:42:53,320 --> 00:42:56,519
so we're like, we can go into a business and say, hey, like, okay,

879
00:42:56,599 --> 00:42:58,280
how do you run what is your day to day

880
00:42:58,320 --> 00:43:03,599
in every department, marketing operation, in sales, you know, finance, whatever, Okay,

881
00:43:03,599 --> 00:43:05,880
what their day to day goes like this? Okay, so

882
00:43:05,920 --> 00:43:09,159
we can cut down their time by this. Maybe there's

883
00:43:09,159 --> 00:43:12,320
some open positions that they may not necessarily need because

884
00:43:12,360 --> 00:43:14,199
they can make their employees be able to do more

885
00:43:14,480 --> 00:43:17,039
with less work. And this kind of circles back to

886
00:43:17,119 --> 00:43:19,719
a question you asked earlier of is this going to

887
00:43:19,760 --> 00:43:21,679
start like taking away jobs? I don't think it's going

888
00:43:21,719 --> 00:43:23,960
to take away jobs. No, it's going to make it.

889
00:43:24,000 --> 00:43:28,199
Speaker 2: Adapt or die. I mean, it's unfortunate, but we went

890
00:43:28,320 --> 00:43:34,159
from the industrial era right to technology, so jobs this happened, and.

891
00:43:34,280 --> 00:43:36,360
Speaker 4: Analytics jobs are going to start going away.

892
00:43:36,599 --> 00:43:38,800
Speaker 2: You own an h v a C company, of course

893
00:43:39,840 --> 00:43:41,880
you got to have somebody to get in there and

894
00:43:42,039 --> 00:43:43,679
actiously diagnose what's happening.

895
00:43:44,000 --> 00:43:44,199
Speaker 6: Yeah.

896
00:43:44,239 --> 00:43:52,480
Speaker 5: Well yeah, if AI ruins everything, then I'll be fine, right, exactly. No,

897
00:43:53,000 --> 00:43:56,360
but there even and we have already talked with trade

898
00:43:56,360 --> 00:43:59,800
businesses and you know, we can still help them. You know,

899
00:43:59,840 --> 00:44:01,280
we can help them in the field, and we can

900
00:44:01,320 --> 00:44:04,599
help them obviously in the office. So you know, AI

901
00:44:04,760 --> 00:44:07,599
is just going to become something. You know, especially in

902
00:44:07,599 --> 00:44:08,559
the next few years.

903
00:44:08,880 --> 00:44:10,239
Speaker 6: You can have an AI department.

904
00:44:10,280 --> 00:44:15,840
Speaker 2: Okay, so you could. They're gonna have an AI department. Wow. Wait,

905
00:44:16,000 --> 00:44:18,400
that's something I've never heard said. Have you heard that set?

906
00:44:18,559 --> 00:44:21,360
I've not heard that set? An AI department? What would

907
00:44:21,400 --> 00:44:22,280
be an AI department?

908
00:44:22,320 --> 00:44:24,719
Speaker 4: Go ahead, it's really just going to be like a

909
00:44:24,760 --> 00:44:28,159
company wide efficiency center and always making sure you're at

910
00:44:28,199 --> 00:44:30,800
the top because it's going to start getting really competitive.

911
00:44:30,800 --> 00:44:32,400
And that's honestly why we do what we do is

912
00:44:32,440 --> 00:44:34,519
because we want to bring Rochester back up because when

913
00:44:34,519 --> 00:44:36,880
we came back from AI four, we realize there's a

914
00:44:36,880 --> 00:44:38,480
lot of tools out there that we know about that

915
00:44:38,639 --> 00:44:40,960
nobody here knows about, and we want to start bringing

916
00:44:40,960 --> 00:44:42,119
the city up to that level.

917
00:44:42,559 --> 00:44:45,760
Speaker 2: Are you originally from Rochester? Yeah? Okay, And did you

918
00:44:45,760 --> 00:44:49,320
go to Fairport High School? Fairport High School? Yeah?

919
00:44:49,360 --> 00:44:51,320
Speaker 4: God, terrible, I know, yeah.

920
00:44:51,320 --> 00:44:55,480
Speaker 2: And then and then the Red Raiders and then after that, where.

921
00:44:56,800 --> 00:44:59,159
Speaker 4: I've I've stayed here, yeah.

922
00:44:58,840 --> 00:45:02,880
Speaker 2: The college here or no college yeah, MCC And then

923
00:45:03,039 --> 00:45:04,480
uh and what did you do the same thing?

924
00:45:04,960 --> 00:45:07,000
Speaker 5: I grew up in Geneva. I went to the sales

925
00:45:07,039 --> 00:45:08,400
before unfortunately closed.

926
00:45:08,639 --> 00:45:08,880
Speaker 2: Yeah.

927
00:45:09,679 --> 00:45:12,480
Speaker 5: And then yeah, I've just been hustling my entire life.

928
00:45:12,679 --> 00:45:13,880
Never really needed college.

929
00:45:14,000 --> 00:45:15,159
Speaker 2: Yes, you know, right, you.

930
00:45:15,079 --> 00:45:17,360
Speaker 5: Train yourself on, you read a book, right, Yeah, you

931
00:45:17,360 --> 00:45:18,920
have a problem, you read a book, you take a course.

932
00:45:18,960 --> 00:45:20,719
You know, smart accounting is an issue. You can take a

933
00:45:20,840 --> 00:45:25,320
Cornell course whatever you need. Yeah, college is really unnecessary

934
00:45:25,400 --> 00:45:28,360
unless you're going for a pH d. And you know,

935
00:45:28,400 --> 00:45:31,440
being a doctor, you know to be to be quite honest,

936
00:45:31,639 --> 00:45:35,400
So I just submersed myself and you know, I've loved

937
00:45:35,440 --> 00:45:36,559
tech my entire life.

938
00:45:36,719 --> 00:45:38,599
Speaker 6: So this type of stuff has just been so.

939
00:45:38,840 --> 00:45:41,800
Speaker 5: Incredible to be able to work with hands on and

940
00:45:41,840 --> 00:45:44,800
then obviously meeting Brendan and diving to this AI has

941
00:45:44,840 --> 00:45:45,360
just been.

942
00:45:45,599 --> 00:45:48,840
Speaker 2: Yeah, so cool. AI rock and you'll go in and

943
00:45:48,880 --> 00:45:52,119
help people just be more efficient and use AI. So

944
00:45:52,199 --> 00:45:54,920
you can have AI do invoices for you. You could

945
00:45:54,960 --> 00:45:55,760
have them. Yeah.

946
00:45:55,800 --> 00:45:58,519
Speaker 5: So actually one of my one of my friends, even

947
00:45:58,639 --> 00:45:59,880
the government is using it.

948
00:45:59,800 --> 00:46:01,440
Speaker 6: Like like police officers.

949
00:46:01,920 --> 00:46:06,800
Speaker 5: They're actually utilizing their their camera system to write all

950
00:46:06,840 --> 00:46:09,039
of their reports. Now, oh yeah, so if you have

951
00:46:09,039 --> 00:46:12,000
a traffic stop transcrit it's one hundred percent transcripted and

952
00:46:12,039 --> 00:46:15,039
the report has filled out, you'll just have to basically

953
00:46:15,039 --> 00:46:17,039
make sure the eyes are got and the teaser crossed.

954
00:46:17,039 --> 00:46:20,559
Speaker 2: It's funny because I will do videos right. And one

955
00:46:20,599 --> 00:46:23,280
of the big things now for social media is some

956
00:46:23,360 --> 00:46:25,119
people are at work, so they're not going to have

957
00:46:25,159 --> 00:46:29,400
the volume on, but they want to read the captions.

958
00:46:29,400 --> 00:46:31,880
So you have the AI captions done, but you got

959
00:46:31,920 --> 00:46:33,920
to catch the AI. You got to go back through

960
00:46:34,039 --> 00:46:38,400
and read them because they're probably I'm going to say,

961
00:46:38,440 --> 00:46:42,440
over ninety percent correct, but there's some word or somebody

962
00:46:42,559 --> 00:46:43,760
slurred something or.

963
00:46:45,000 --> 00:46:47,039
Speaker 4: What I would recommend for you. And this is like

964
00:46:47,039 --> 00:46:49,400
an easy, quick little fix. You can run the You

965
00:46:49,440 --> 00:46:52,119
take the entire caption list and then run it through

966
00:46:52,199 --> 00:46:54,519
like claud or something, and then say any words that's

967
00:46:54,519 --> 00:46:56,880
the amount of place, replace it with one that they

968
00:46:56,920 --> 00:46:58,159
most likely meant instead.

969
00:46:58,639 --> 00:47:01,199
Speaker 2: Really yeah, all right, well, but this is all part

970
00:47:01,199 --> 00:47:03,480
of one like editing system like a cap cut or

971
00:47:03,519 --> 00:47:04,760
something like that. You know what I mean, it's already

972
00:47:04,760 --> 00:47:07,599
built in, but that's a good Yeah, so they can

973
00:47:07,639 --> 00:47:10,840
do all of that. Yeah, and that's again why clot

974
00:47:10,880 --> 00:47:11,800
over chat ept.

975
00:47:12,119 --> 00:47:14,480
Speaker 4: It's just it's a little smarter for the average user.

976
00:47:14,559 --> 00:47:18,400
Speaker 2: It is, but the chat cheapt became sort of the Kleenex.

977
00:47:18,000 --> 00:47:20,880
Speaker 4: Of it was honest and it's all about being first,

978
00:47:21,280 --> 00:47:26,039
it is. So Yeah, there's a huge UH name brand

979
00:47:26,039 --> 00:47:26,599
around chatch.

980
00:47:27,159 --> 00:47:29,800
Speaker 6: But builders are obviously they're they're quite large.

981
00:47:29,920 --> 00:47:33,079
Speaker 2: I know people who will not send a text without

982
00:47:33,159 --> 00:47:37,159
first putting it in chat cheapat and talking it like

983
00:47:37,199 --> 00:47:38,880
you know, they don't even type, they're just talking to

984
00:47:38,880 --> 00:47:41,800
the wrong Hey, write me a friendly text message that

985
00:47:41,880 --> 00:47:44,559
says blah blah blah blah blah and then boom and

986
00:47:44,599 --> 00:47:46,800
it comes out and it actually comes out. I've tried

987
00:47:46,800 --> 00:47:50,079
it myself. It comes out better than what you've said,

988
00:47:50,119 --> 00:47:54,320
you know what I mean? Or friends exactly why? Because

989
00:47:54,360 --> 00:47:56,320
it won't let me it's cleaned it up.

990
00:47:56,639 --> 00:47:57,320
Speaker 6: You gotta be nice.

991
00:47:57,400 --> 00:47:58,159
Speaker 2: But I'll be back.

992
00:47:58,440 --> 00:48:02,320
Speaker 4: The business that I work with, the UH, we implemented

993
00:48:02,360 --> 00:48:04,639
AI in all levels and one of them that has

994
00:48:04,760 --> 00:48:10,000
had the best like feedback is it scripts. AI responses

995
00:48:10,039 --> 00:48:14,599
based off of the thread that it's in, and you

996
00:48:14,639 --> 00:48:16,280
can choose the tone, you can choose, the length, you

997
00:48:16,280 --> 00:48:18,480
can choose whatever you want. So I remember there was

998
00:48:18,519 --> 00:48:20,880
this one situation where there was a heated customer with

999
00:48:20,960 --> 00:48:23,840
a different department, and the guy, who is not known

1000
00:48:23,880 --> 00:48:28,239
for being very well written, I guess we'll say, just

1001
00:48:28,360 --> 00:48:30,880
use an artificial intelligence response, and it had the most

1002
00:48:30,880 --> 00:48:33,719
perfect response you can you can imagine, and it kind

1003
00:48:33,719 --> 00:48:36,639
of calmed down the situation, whereas if he was on

1004
00:48:36,679 --> 00:48:38,519
his own, it wouldn't have had that same effect.

1005
00:48:38,519 --> 00:48:40,679
Speaker 2: But don't we see the what's what's what's the ad for?

1006
00:48:40,840 --> 00:48:44,159
Because everybody's has their own AI now right? I think

1007
00:48:44,199 --> 00:48:48,840
that I think Microsoft has one and everybody's are they

1008
00:48:48,880 --> 00:48:51,559
pilot or something? And then Apple has.

1009
00:48:51,440 --> 00:48:54,679
Speaker 8: One, so really it's out, but it's not like out completely.

1010
00:48:54,960 --> 00:48:56,800
Speaker 2: But have you seen the ads for the Apple one?

1011
00:48:57,159 --> 00:48:59,039
Speaker 9: Or the guy's like, hey, I think we need to

1012
00:48:59,079 --> 00:49:02,880
circle back on this thing. He's some jamoke at work

1013
00:49:02,960 --> 00:49:05,079
right his feet are up, And then then the boss

1014
00:49:05,119 --> 00:49:07,119
gets the text message or the email and he goes,

1015
00:49:08,360 --> 00:49:10,719
Joe wrote this, and he's like looking up because it

1016
00:49:11,320 --> 00:49:12,880
cleans it up, it polishes it.

1017
00:49:13,159 --> 00:49:15,599
Speaker 2: And I'll tell you, like I do. I mean, I

1018
00:49:15,760 --> 00:49:19,519
I think with kids in school and things. We have

1019
00:49:19,639 --> 00:49:23,199
forgotten how to spell, We have forgotten how to punctuate things.

1020
00:49:23,360 --> 00:49:26,760
So when you get something that's perfectly punctuated grammatically correct,

1021
00:49:27,400 --> 00:49:30,920
you know absolutely something's up. But that's the way the

1022
00:49:30,960 --> 00:49:32,960
world's going. So do we punish that.

1023
00:49:33,760 --> 00:49:36,440
Speaker 8: Or do well, no, because that's.

1024
00:49:35,920 --> 00:49:38,679
Speaker 2: That's that's that's my point is I almost feel like smarter,

1025
00:49:38,840 --> 00:49:42,440
not harder. Yes, And I feel like in the education system,

1026
00:49:42,639 --> 00:49:45,960
I understand that you want, but if it's really about

1027
00:49:46,079 --> 00:49:49,239
ideas and taking those ideas and putting them in a

1028
00:49:49,320 --> 00:49:51,960
succinct form that everybody can understand or is a little

1029
00:49:52,000 --> 00:49:56,800
more polished, you know. Sometimes Uh, I don't want to

1030
00:49:56,840 --> 00:50:00,920
say Brendan's a geek, but oh no, no, But like

1031
00:50:01,079 --> 00:50:04,079
you may speak a certain way that doesn't connect with somebody,

1032
00:50:04,119 --> 00:50:05,960
but AI can make it better, and I'm sure you'd

1033
00:50:05,960 --> 00:50:08,000
be fine. I'm just using it as a joke.

1034
00:50:08,199 --> 00:50:09,400
Speaker 6: I'm as a translator.

1035
00:50:09,599 --> 00:50:11,360
Speaker 4: Yeah, that's why I keep him wrong.

1036
00:50:11,480 --> 00:50:13,559
Speaker 2: Oh yeah, yeah, I don't. I certainly didn't mean anything

1037
00:50:13,599 --> 00:50:17,239
by that, But my point being that, you know, like sometimes.

1038
00:50:17,360 --> 00:50:21,199
Speaker 5: And honestly, you know that's going to unfortunately happen. You know,

1039
00:50:21,320 --> 00:50:24,960
people aren't going to spell whatever, but what they can

1040
00:50:25,039 --> 00:50:27,719
do is harness their brain in other ways. Yes, So

1041
00:50:27,800 --> 00:50:30,559
if you can take an offload, obviously you have to

1042
00:50:30,599 --> 00:50:32,960
have some common sense and street smart yes, but if

1043
00:50:32,960 --> 00:50:35,559
you can take an offload off of your brain, you know,

1044
00:50:36,039 --> 00:50:39,920
and just be able to think freely, the possibility is

1045
00:50:39,920 --> 00:50:41,920
around this, and you might see a lot of creativity

1046
00:50:41,920 --> 00:50:44,719
out of people that you normally wouldn't using products like that.

1047
00:50:45,000 --> 00:50:47,199
Speaker 3: Yeah, but can you reverse it too, because like sometimes

1048
00:50:47,199 --> 00:50:48,800
you work with some really stupid people.

1049
00:50:48,880 --> 00:50:51,880
Speaker 2: Yeah, oh yeah for you, and you're.

1050
00:50:51,719 --> 00:50:53,840
Speaker 3: Trying to explain them the most base way you can

1051
00:50:53,880 --> 00:50:56,159
think of, and it's still fifty feet over their head.

1052
00:50:56,199 --> 00:50:58,159
Speaker 4: In my experience, those are people end up not using

1053
00:50:58,159 --> 00:51:00,079
it anyway because they don't understand it.

1054
00:51:00,559 --> 00:51:02,440
Speaker 3: But I just want to make it so they understand

1055
00:51:02,480 --> 00:51:03,519
what the hell I'm talking about.

1056
00:51:03,679 --> 00:51:07,039
Speaker 4: Yeah, ask ask the AI. Then that's why I tell

1057
00:51:07,079 --> 00:51:10,639
people pretend like it's just Google and start talking to

1058
00:51:10,679 --> 00:51:13,599
it like it's a person. Right, then it'll give you

1059
00:51:13,639 --> 00:51:15,639
those answers and you can say, explain, like I'm five

1060
00:51:15,719 --> 00:51:16,199
years well.

1061
00:51:16,159 --> 00:51:19,000
Speaker 2: What are some of your favorite prompts to put into AI.

1062
00:51:19,639 --> 00:51:23,599
Let's say every day stuff. Let's say I I'll.

1063
00:51:22,960 --> 00:51:25,960
Speaker 4: Do I'll do one that so I'm kind of into fitness.

1064
00:51:26,840 --> 00:51:29,519
I was one hundred and seventy nine pounds and I was.

1065
00:51:29,519 --> 00:51:33,159
Speaker 2: Like, oh my god, you're overweight. Well yeah, and what

1066
00:51:33,440 --> 00:51:36,159
you are at one hundred and seventy nine Yeah, Jesus dude.

1067
00:51:36,519 --> 00:51:38,920
Speaker 4: So I was like, okay, I like to give me

1068
00:51:39,519 --> 00:51:42,000
a meal plan. So I put my my height, my weight,

1069
00:51:43,079 --> 00:51:45,519
the foods that I like, the exercise that I like doing,

1070
00:51:45,519 --> 00:51:47,199
the amount of time that I had to dedicate to

1071
00:51:47,239 --> 00:51:51,559
this every week, and it created a meal plan, a

1072
00:51:51,639 --> 00:51:54,360
workout regimen, and just an.

1073
00:51:54,199 --> 00:51:56,440
Speaker 2: Over just get a fucking girlfriend, got.

1074
00:51:57,880 --> 00:52:01,320
Speaker 3: Done.

1075
00:52:01,559 --> 00:52:05,599
Speaker 2: It's just wow, that terrible? How mean is it? See?

1076
00:52:05,719 --> 00:52:08,400
How do we get rid of bullies? No? But like

1077
00:52:08,480 --> 00:52:12,000
that's amazing, right, and it transformed you.

1078
00:52:12,000 --> 00:52:14,920
Speaker 4: No, I'm down to one fifty seven and it's just

1079
00:52:15,039 --> 00:52:17,719
using artificial intelligence, Like I need a personal trader. I

1080
00:52:17,719 --> 00:52:24,320
didn't need anything. But like that's just a practical way

1081
00:52:24,440 --> 00:52:25,559
anybody can use this.

1082
00:52:25,760 --> 00:52:28,360
Speaker 2: And you know, but they have to actually do it.

1083
00:52:28,360 --> 00:52:29,559
Speaker 6: They have to just you know what I mean.

1084
00:52:30,000 --> 00:52:32,199
Speaker 2: No, they have to read it and actually do it.

1085
00:52:32,280 --> 00:52:34,679
Then they got to follow it. That's the hard.

1086
00:52:34,480 --> 00:52:38,440
Speaker 4: Partwhere but I wanted it. If they want it, they

1087
00:52:38,440 --> 00:52:41,559
can follow a personal trainer can't make the person.

1088
00:52:41,440 --> 00:52:43,320
Speaker 2: No, because how many times have we gone to an

1089
00:52:43,400 --> 00:52:48,480
attritionist or or said if I only had someone to

1090
00:52:48,559 --> 00:52:50,599
show me the way? Now? You do?

1091
00:52:50,800 --> 00:52:51,119
Speaker 4: You do?

1092
00:52:51,239 --> 00:52:52,280
Speaker 2: You do? Yeah?

1093
00:52:52,800 --> 00:52:55,880
Speaker 4: One of my favorite ways to like talk about AI

1094
00:52:55,960 --> 00:52:57,800
to somebody that's like, I haven't even touched it yet,

1095
00:52:57,800 --> 00:53:00,800
I don't know where to begin. Imagine how somebody that

1096
00:53:01,000 --> 00:53:03,920
is better than ninety percent of the population in every

1097
00:53:03,960 --> 00:53:07,400
single category working for you to answer your questions to

1098
00:53:07,480 --> 00:53:11,480
make you a professional in any of those fields twenty

1099
00:53:11,519 --> 00:53:14,679
four to seven and for a decent model that gives

1100
00:53:14,719 --> 00:53:17,159
you like a lot of like back and forth conversation

1101
00:53:17,199 --> 00:53:19,480
without the limits because right now, a big thing with

1102
00:53:19,519 --> 00:53:21,599
the you know, Claude and chatchepet is you can only

1103
00:53:21,599 --> 00:53:23,199
prompt it so many times before it locks you out

1104
00:53:23,239 --> 00:53:25,360
for a few hours because really the amount of traffic

1105
00:53:25,400 --> 00:53:30,280
that they've got. And you can learn anything you want

1106
00:53:30,320 --> 00:53:32,800
to learn, and you can do anything you want to do.

1107
00:53:33,079 --> 00:53:36,519
I'm not a doctor, but there was a story a

1108
00:53:36,519 --> 00:53:38,920
couple of years ago, actually shortly after I came out.

1109
00:53:39,239 --> 00:53:43,119
This woman had a son who had been sick since

1110
00:53:43,119 --> 00:53:46,360
the day he was born, seeing hundreds of doctors and

1111
00:53:46,559 --> 00:53:48,719
nobody knew what was wrong with him. She put his

1112
00:53:48,800 --> 00:53:55,320
symptoms into chatchipt and it spat out a diagnosis. She

1113
00:53:55,440 --> 00:53:57,320
went to a doctor saying, I think my son has this.

1114
00:53:57,440 --> 00:54:02,559
It was right, and a huge talking point in the

1115
00:54:02,559 --> 00:54:06,599
healthcare field has been like doctor's bedside manner. AI wins.

1116
00:54:07,440 --> 00:54:11,199
Speaker 2: They did a blind over in bedside manner, which is

1117
00:54:11,480 --> 00:54:15,719
troubling because we would think that AI doesn't have feelings.

1118
00:54:16,400 --> 00:54:21,400
You have feelings in emotion, told the empathet, right, Okay, yeah, interesting,

1119
00:54:21,960 --> 00:54:22,480
it's scary.

1120
00:54:22,559 --> 00:54:24,559
Speaker 4: It's a it's a tool, and I hate you guys.

1121
00:54:24,639 --> 00:54:27,119
There's nothing, there's nothing to be scared of until we

1122
00:54:27,159 --> 00:54:28,880
hit a g I. And that's a whole other converce.

1123
00:54:28,960 --> 00:54:29,679
Speaker 2: What's a g I.

1124
00:54:29,800 --> 00:54:32,480
Speaker 4: It's pretty much where AI can teach itself because right

1125
00:54:32,519 --> 00:54:35,159
now AI is only as smart as the information it's fed,

1126
00:54:35,280 --> 00:54:36,519
so the smartest human.

1127
00:54:36,559 --> 00:54:38,960
Speaker 2: But isn't it pulling from everywhere on the Internet? Like

1128
00:54:39,400 --> 00:54:42,840
for years I said this, who put it in there?

1129
00:54:43,639 --> 00:54:46,599
And who put it in that that I can find

1130
00:54:46,760 --> 00:54:50,599
any bit of information I want on how to get

1131
00:54:50,599 --> 00:54:53,599
someplace on who put that in there? Well?

1132
00:54:53,760 --> 00:54:56,320
Speaker 4: And it's Internet, and it's that there are actually a

1133
00:54:56,320 --> 00:54:58,960
lot of checks and balances for how the giant ll

1134
00:54:59,039 --> 00:55:02,159
ms are being made right now? Is it all perfect?

1135
00:55:02,360 --> 00:55:05,480
I can't say they're all perfect, but I mean to

1136
00:55:05,599 --> 00:55:09,440
kind of put it back at you. How are people

1137
00:55:09,519 --> 00:55:13,239
being trained in colleges? How are doctors being college encyclopedias

1138
00:55:13,239 --> 00:55:13,639
on books?

1139
00:55:13,639 --> 00:55:16,119
Speaker 2: And yes, yes, yes, but I'm saying like somebody had

1140
00:55:16,159 --> 00:55:18,119
to take all that information and put it in there

1141
00:55:18,199 --> 00:55:20,280
and did that. That's a ton of work.

1142
00:55:20,519 --> 00:55:21,280
Speaker 6: That's what we have to do.

1143
00:55:21,320 --> 00:55:24,519
Speaker 5: And we know these you know we I'm the smaller

1144
00:55:24,559 --> 00:55:26,079
scale by the way, Like you know, if we're doing

1145
00:55:26,119 --> 00:55:28,199
it for an individual company, that's not like what open

1146
00:55:28,239 --> 00:55:30,840
AI for chat GPT has to do when they're training chap.

1147
00:55:31,159 --> 00:55:34,400
Speaker 2: Yes, okay, so you're taking and you're helping it designed

1148
00:55:34,400 --> 00:55:36,199
for a specific company where they're doing it.

1149
00:55:37,519 --> 00:55:40,719
Speaker 5: A mask maybe some manuals and pdaffs and we're just.

1150
00:55:40,840 --> 00:55:43,679
Speaker 2: Right give training with that, Give me a topic and

1151
00:55:43,719 --> 00:55:45,840
we'll have a I write a song and then we'll

1152
00:55:46,480 --> 00:55:48,639
are you using souno? Yes? Is that okay?

1153
00:55:48,840 --> 00:55:50,679
Speaker 4: That's fine? I have it too on my phone.

1154
00:55:50,760 --> 00:55:53,320
Speaker 2: Yeah. Do you write songs for fun?

1155
00:55:53,360 --> 00:55:53,559
Speaker 6: Yeah?

1156
00:55:53,599 --> 00:55:56,239
Speaker 2: Yeah, once in a while. Yeah. Yeah. Why do you

1157
00:55:56,280 --> 00:55:58,800
have you ever tried to pass off a Souno song

1158
00:55:59,000 --> 00:56:02,159
as one you created and done. Oh me, no no,

1159
00:56:02,519 --> 00:56:05,159
but like a love song for a musician you did

1160
00:56:05,280 --> 00:56:06,199
Greek do it?

1161
00:56:06,239 --> 00:56:08,480
Speaker 4: Said he could tell the difference between the AI song

1162
00:56:08,559 --> 00:56:10,599
and a real song. So I found a really obscure

1163
00:56:10,639 --> 00:56:13,159
real song, and then I created a song on Suno

1164
00:56:13,239 --> 00:56:14,920
and then played him side by side. He got it wrong.

1165
00:56:15,480 --> 00:56:19,880
Speaker 2: Wow, that's a little scary, because sometimes it does. You

1166
00:56:19,920 --> 00:56:22,519
can kind of tell, even in the voices and things.

1167
00:56:22,599 --> 00:56:24,000
But give me a topic and we'll have to write

1168
00:56:24,039 --> 00:56:24,360
a song.

1169
00:56:24,880 --> 00:56:26,360
Speaker 3: I just put in the chest sheep. Can you write

1170
00:56:26,400 --> 00:56:27,679
me a pickup line to pick up a girl at

1171
00:56:27,679 --> 00:56:27,960
a bar?

1172
00:56:28,159 --> 00:56:28,639
Speaker 2: And is it?

1173
00:56:28,639 --> 00:56:30,480
Speaker 3: It came back with are you this charming with everyone?

1174
00:56:30,599 --> 00:56:32,360
Or am I just getting the VIP treatment today?

1175
00:56:32,400 --> 00:56:34,079
Speaker 2: All right, we're gonna put that in. We're gonna use

1176
00:56:34,119 --> 00:56:36,639
your line, and we're gonna do that next right after this.

1177
00:56:36,760 --> 00:56:39,280
Got hurt on the job, I don't call Uncle Bob.

1178
00:56:39,360 --> 00:56:42,320
I mean he's got stories fawn off ladders, slipping on ice.

1179
00:56:42,400 --> 00:56:44,920
But trust me, you don't need a sudvice. You need

1180
00:56:45,159 --> 00:56:49,000
Connors and Ferris. At Connors and Ferris, they focus on workers,

1181
00:56:49,039 --> 00:56:52,679
comp social security, disability, and personal injury. They know the

1182
00:56:52,679 --> 00:56:54,760
ins and outs of workers comp. Like Uncle Bob knows

1183
00:56:54,760 --> 00:56:57,320
how to fall off a ladder, their team understands the

1184
00:56:57,320 --> 00:57:00,760
insurance companies, employers, in the legal system things Uncle Bob

1185
00:57:00,920 --> 00:57:04,280
really doesn't get. Let's face it, filing a claim can

1186
00:57:04,320 --> 00:57:06,679
be stressful, but at Connors and Ferris they'll fight for

1187
00:57:06,719 --> 00:57:09,320
your rights and the compensation you deserve so you can

1188
00:57:09,360 --> 00:57:12,440
actually sleep at night. No worry, no more, Uncle Bob.

1189
00:57:12,480 --> 00:57:16,360
Advice just called two six two COMP. That's two six

1190
00:57:16,559 --> 00:57:41,599
two co MP Connors and Ferris, your workers COMP attorneys.

1191
00:57:31,480 --> 00:57:38,920
Speaker 7: Do smile this the glow herbeat, sing to them.

1192
00:57:39,800 --> 00:57:44,119
Speaker 10: No, are you this sharming with everyone you meet?

1193
00:57:46,039 --> 00:57:47,480
Speaker 2: Am I just feeling?

1194
00:57:50,960 --> 00:57:51,280
Speaker 10: Are you?

1195
00:57:51,719 --> 00:57:57,559
Speaker 2: I'm right now? This sounds like buddy, it's freaky because

1196
00:57:59,079 --> 00:58:03,679
likes series called he excuse and it's in the morning.

1197
00:58:03,840 --> 00:58:06,840
It's not a r B like this. Am I getting

1198
00:58:07,239 --> 00:58:13,519
just kidd The R tree? The VI P tree is long,

1199
00:58:13,760 --> 00:58:17,599
close magnetic. All right? Now they give you two versions?

1200
00:58:18,360 --> 00:58:18,800
What is this?

1201
00:58:18,920 --> 00:58:20,480
Speaker 11: So called food?

1202
00:58:20,599 --> 00:58:20,679
Speaker 12: No?

1203
00:58:20,840 --> 00:58:21,760
Speaker 2: Shoot, I have you met that?

1204
00:58:21,840 --> 00:58:23,800
Speaker 4: I apologize?

1205
00:58:26,199 --> 00:58:30,320
Speaker 2: Kevin, not gonna give you the other one? Here's no,

1206
00:58:30,480 --> 00:58:31,440
I think I like this one better.

1207
00:58:31,440 --> 00:58:40,519
Speaker 3: Already got that Country Twain A little bit jelly Roll, Country.

1208
00:58:40,239 --> 00:58:45,800
Speaker 10: Twain bits the low your smiles clue heart gets into

1209
00:58:45,920 --> 00:58:49,920
the riddle, you know, are you this charming with everyone

1210
00:58:49,960 --> 00:58:54,760
you meet? Or am I just feeling? Are you this

1211
00:58:54,880 --> 00:58:56,400
charming with everyone?

1212
00:58:56,440 --> 00:58:57,159
Speaker 12: You're fine?

1213
00:58:57,960 --> 00:58:59,920
Speaker 10: Or a model on going your mind?

1214
00:59:00,079 --> 00:59:06,519
Speaker 2: I don't know. I might like, yeah, the voice, Yeah,

1215
00:59:06,599 --> 00:59:09,519
so what if you put it back in? Does itate

1216
00:59:09,599 --> 00:59:12,320
something different for you? Or and it's.

1217
00:59:12,199 --> 00:59:15,320
Speaker 4: Make a different request, make it better?

1218
00:59:15,480 --> 00:59:18,280
Speaker 2: Yeact like, just go for a vibe. You know.

1219
00:59:18,559 --> 00:59:20,960
Speaker 4: You can have it combine some weird things. I've used

1220
00:59:20,960 --> 00:59:21,800
this that before.

1221
00:59:21,599 --> 00:59:23,760
Speaker 2: Like what, so what do you have it combined? You

1222
00:59:23,960 --> 00:59:26,159
did Egyptian Rock? Yeah, it was cool.

1223
00:59:26,519 --> 00:59:29,039
Speaker 4: It's like chick it weird things, man, Okay, and it

1224
00:59:29,400 --> 00:59:32,159
comes up with some really unique things I've never heard of.

1225
00:59:32,159 --> 00:59:32,920
So I don't even know how.

1226
00:59:32,840 --> 00:59:35,440
Speaker 3: Do a cross between The Stones and jelly Roll?

1227
00:59:37,480 --> 00:59:41,119
Speaker 2: All right, the Rolling Stones, I'm typing this in real time,

1228
00:59:41,480 --> 00:59:45,960
the Rolling Stones and Jelly Roll. I have this problem

1229
00:59:46,000 --> 00:59:50,119
where it's a British dog whistle. I always say jelly

1230
00:59:50,199 --> 00:59:55,440
roll is a dog whistle for stupid. But okay, let's

1231
00:59:55,480 --> 01:00:00,519
see here we go, it's working. We'll see, I'm see

1232
01:00:00,519 --> 01:00:03,440
it's It's amazing what this can do but this is

1233
01:00:03,519 --> 01:00:08,079
great because uh, you're not paying BMI or as cap.

1234
01:00:08,199 --> 01:00:12,519
You could have jingles for your business. You could have right, I.

1235
01:00:12,440 --> 01:00:15,000
Speaker 4: Mean last I checked, they if you have the subscription

1236
01:00:15,079 --> 01:00:16,599
for Suno, which is a lot cheaper.

1237
01:00:16,360 --> 01:00:19,400
Speaker 2: Than most of the Yeah, but they give you free

1238
01:00:19,519 --> 01:00:20,239
can you could you.

1239
01:00:20,239 --> 01:00:22,679
Speaker 4: Not use the free Yeah, you could use it for you.

1240
01:00:23,000 --> 01:00:24,599
Speaker 2: Even even their free version.

1241
01:00:25,000 --> 01:00:26,440
Speaker 4: I'm not sure about the free Okay.

1242
01:00:26,519 --> 01:00:28,800
Speaker 3: I bet you could even just put in play Sammy

1243
01:00:28,840 --> 01:00:32,079
Hagger I can't drive fifty five? Would it would that pull?

1244
01:00:34,039 --> 01:00:36,960
Speaker 4: Well, it doesn't like existing people's names. It'll it'll give

1245
01:00:36,960 --> 01:00:38,960
you pushback on that because it's not trying to copy

1246
01:00:39,000 --> 01:00:39,960
anybody in particular.

1247
01:00:40,599 --> 01:00:42,280
Speaker 2: They want to avoid that. But you can get so

1248
01:00:42,320 --> 01:00:44,840
if we said something like the rolling I just wrote

1249
01:00:44,880 --> 01:00:46,599
in rolling stones and jelly roll would.

1250
01:00:46,360 --> 01:00:48,679
Speaker 4: Have pushed back, push back on that house.

1251
01:00:48,480 --> 01:00:49,480
Speaker 2: Just spinning and spinning.

1252
01:00:49,599 --> 01:00:51,599
Speaker 4: If you uh, if you go to like chat GPT

1253
01:00:51,880 --> 01:00:54,280
and then say how would you describe a mix of

1254
01:00:54,360 --> 01:00:56,840
rolling stones and jelly roll in in a way in

1255
01:00:56,880 --> 01:00:59,760
like two hundred characters or less, so that you can

1256
01:00:59,760 --> 01:01:02,519
then paste that prompted so you get look at this

1257
01:01:02,960 --> 01:01:04,519
so you can.

1258
01:01:04,079 --> 01:01:09,239
Speaker 2: Get crossing your ais. Wow, you're making the perfect AI storm.

1259
01:01:09,559 --> 01:01:12,880
It is amazing, and I think that a lot of people.

1260
01:01:13,679 --> 01:01:16,679
It's almost like a cheat code for life in a way.

1261
01:01:17,239 --> 01:01:19,480
But what do we talk about a lot in this country.

1262
01:01:19,840 --> 01:01:23,159
We work so many hours, right, we're always pursuing the dream.

1263
01:01:23,239 --> 01:01:26,119
There's not enough time. I think we are the most

1264
01:01:26,639 --> 01:01:30,760
time shortest consciousness society there is on the planet. Because

1265
01:01:30,880 --> 01:01:33,119
you go to Europe and then they're taking naps and

1266
01:01:33,159 --> 01:01:36,039
they shut down at two o'clock in the afternoon, don't right,

1267
01:01:36,199 --> 01:01:38,320
the sidewalks roll up, and then they come back at

1268
01:01:38,320 --> 01:01:40,599
seven o'clock at night and go to three in the morning.

1269
01:01:41,199 --> 01:01:45,199
It's just a different thing. You could have an easier life,

1270
01:01:45,320 --> 01:01:47,639
or get more done, or be more productive, or be

1271
01:01:47,719 --> 01:01:51,000
there for your family and still being able to run

1272
01:01:51,000 --> 01:01:53,119
your business, run your stuff by doing that.

1273
01:01:53,239 --> 01:01:53,679
Speaker 6: That's mention.

1274
01:01:53,800 --> 01:01:57,960
Speaker 4: When you're having AI take care of the lower skill,

1275
01:01:58,480 --> 01:02:01,480
higher time consuming tab that are just a drag on

1276
01:02:01,800 --> 01:02:03,719
your nine to five or whatever kind of job you have,

1277
01:02:05,119 --> 01:02:07,599
it's less energizing. But that when when AI takes that

1278
01:02:07,840 --> 01:02:09,280
part over and you get to focus on the part

1279
01:02:09,280 --> 01:02:11,719
that motivates, either the creative aspect of the job or

1280
01:02:12,039 --> 01:02:15,159
the the more you know human element of the of

1281
01:02:15,199 --> 01:02:19,639
the position. Then you get more done. The productivity skyrockets

1282
01:02:19,639 --> 01:02:21,079
because you're focusing on the part of the job that

1283
01:02:21,119 --> 01:02:22,960
you love, not the part of the job that nobody likes.

1284
01:02:23,039 --> 01:02:24,920
Speaker 2: No, right, all the shit that you hate that you

1285
01:02:25,000 --> 01:02:28,199
put off, you procrastinate on, and then starts to drag

1286
01:02:28,239 --> 01:02:31,599
you down, like accounting, And that's exactly what I'm thinking.

1287
01:02:32,400 --> 01:02:35,119
Speaker 6: We have partners that specialize in that.

1288
01:02:35,719 --> 01:02:38,400
Speaker 5: You know, it'll link directly with your quick books, and

1289
01:02:38,559 --> 01:02:41,159
you can set guardrails for how you're reporting and you're

1290
01:02:41,159 --> 01:02:45,519
reconciling as and it'll literally day in and day I'll

1291
01:02:45,519 --> 01:02:47,079
give you up to date piano.

1292
01:02:47,800 --> 01:02:49,960
Speaker 2: Well, they give you things too, like I mean, we

1293
01:02:50,000 --> 01:02:53,320
see I see training videos that are done with AI

1294
01:02:53,480 --> 01:02:56,800
actors now that I couldn't tell the difference. But what

1295
01:02:56,920 --> 01:03:02,199
about things like answering your phones? Yeah, I mean there are.

1296
01:03:02,440 --> 01:03:07,880
Speaker 5: There are programs that are specifically doing that. It's specifically

1297
01:03:07,920 --> 01:03:11,840
in the marketing world too. They do cold calls. You

1298
01:03:11,920 --> 01:03:14,599
can't tell the difference. It breathes, it takes a breath.

1299
01:03:15,079 --> 01:03:17,440
You know, you literally could not tell the difference.

1300
01:03:17,440 --> 01:03:19,679
Speaker 4: It's one of the downsides of AI. And you know,

1301
01:03:19,719 --> 01:03:21,719
then then we get the more spam calls because more

1302
01:03:21,719 --> 01:03:25,960
people figure out how to respect with marketing cold call campaigns,

1303
01:03:25,960 --> 01:03:28,559
and it's like that's not a good thing. Nobody likes.

1304
01:03:28,880 --> 01:03:30,679
Speaker 2: What do we need to worry about with AI because

1305
01:03:30,679 --> 01:03:35,880
we were you know, like you, Kevin brought it up right.

1306
01:03:35,960 --> 01:03:38,400
You can have something sound like Morgan Freeman. You could

1307
01:03:38,440 --> 01:03:41,840
have something sound like you know, the president somebody like.

1308
01:03:42,280 --> 01:03:46,039
Speaker 4: So for the average person, first and foremost, AI is

1309
01:03:46,079 --> 01:03:48,320
not going to take your job. Someone using AI is

1310
01:03:48,360 --> 01:03:51,199
going to take your job. So if you're not using it,

1311
01:03:51,679 --> 01:03:56,400
start using it. And then yeah, things like voice impersonation.

1312
01:03:56,639 --> 01:04:00,239
I've actually heard somebody get a call that sound. It's

1313
01:04:00,320 --> 01:04:03,400
like completely I think Joe Biden. It was a call

1314
01:04:03,440 --> 01:04:06,239
and then it was like don't vote for me or

1315
01:04:06,280 --> 01:04:06,800
something like that.

1316
01:04:06,960 --> 01:04:11,719
Speaker 2: This, yeah, this is terrible. It was Jesus Christ, like

1317
01:04:11,800 --> 01:04:14,280
we need any one of this ship. Thank god.

1318
01:04:14,320 --> 01:04:16,840
Speaker 4: It was over imagine making an a like that.

1319
01:04:17,079 --> 01:04:19,440
Speaker 2: Come on, all right, So I the Rolling Stones jelly

1320
01:04:19,559 --> 01:04:22,400
roll did not work, Kevin, but I put in a

1321
01:04:22,559 --> 01:04:26,559
blues vibe using the same pickup line here it is

1322
01:04:26,599 --> 01:04:27,760
a blues vibe.

1323
01:04:32,039 --> 01:04:35,679
Speaker 10: So you this song me with everyone you meet. Oh

1324
01:04:35,800 --> 01:04:40,440
I'm not just scardy. They in this dim little room

1325
01:04:40,519 --> 01:04:41,440
was shadows down.

1326
01:04:42,960 --> 01:04:49,000
Speaker 2: Let's see if this one does. Now I'm waiting to

1327
01:04:49,039 --> 01:04:51,079
hear Christapleton. When I hear this, I.

1328
01:04:51,039 --> 01:04:55,360
Speaker 13: Really am this jar with everyone.

1329
01:04:55,920 --> 01:04:59,599
Speaker 7: I'm not just kidding the uppy treatment.

1330
01:04:59,559 --> 01:05:02,239
Speaker 2: Just a woman scumbag.

1331
01:05:04,039 --> 01:05:10,440
Speaker 10: As whole promised it a second chance, your flow that honey.

1332
01:05:10,119 --> 01:05:10,679
Speaker 1: In the night.

1333
01:05:12,000 --> 01:05:17,519
Speaker 11: Every I mean, you gotta say, like if somebody started

1334
01:05:17,519 --> 01:05:22,519
playing this in a dim lit room at a bar, No,

1335
01:05:22,599 --> 01:05:22,840
I don't.

1336
01:05:22,920 --> 01:05:26,639
Speaker 2: I don't know that I could, or you know, could

1337
01:05:26,719 --> 01:05:30,360
you do? Could you do a whole night of originals

1338
01:05:30,400 --> 01:05:32,519
written by sonos and you just go out and play

1339
01:05:32,519 --> 01:05:33,119
them yourself?

1340
01:05:33,320 --> 01:05:39,079
Speaker 4: Someone somebody's already doing that. Oh yeah, you got people

1341
01:05:39,159 --> 01:05:41,800
in San Francisco. They're having this and then they go

1342
01:05:41,840 --> 01:05:43,840
out and like, okay, they just play the song. Ye

1343
01:05:44,039 --> 01:05:44,800
here to do it that way?

1344
01:05:44,920 --> 01:05:45,440
Speaker 2: Sure it is.

1345
01:05:45,719 --> 01:05:46,760
Speaker 3: It's almost like karaoke.

1346
01:05:47,719 --> 01:05:51,199
Speaker 4: Hey it's original, right, Yes, it is of songwriting. And

1347
01:05:51,199 --> 01:05:51,960
then they know that.

1348
01:05:52,000 --> 01:05:55,360
Speaker 2: Yeah, but songwriting. See see see here's the part that

1349
01:05:55,360 --> 01:05:59,400
that's different to me. And I always like because I

1350
01:05:59,440 --> 01:06:01,840
knew guys who did punch up writing, like any guys

1351
01:06:01,840 --> 01:06:04,800
who when the Oscars, right, when you write for the Oscars,

1352
01:06:05,199 --> 01:06:07,639
guys will just send out and the email in jokes

1353
01:06:07,719 --> 01:06:11,400
jay Leno. Jay Leno was great because anybody could fax

1354
01:06:11,400 --> 01:06:13,719
a joke and if you used your joke, you got

1355
01:06:13,840 --> 01:06:17,039
seventy five bucks like back in the day, right, So

1356
01:06:17,559 --> 01:06:19,480
there there were punch up writers and things. I go

1357
01:06:19,559 --> 01:06:21,320
for this kind of stuff. It would be great to

1358
01:06:21,440 --> 01:06:23,920
just punch it up, like, you know, can you make

1359
01:06:23,960 --> 01:06:26,519
this funnier? And maybe they can, maybe they can't. Are

1360
01:06:26,519 --> 01:06:29,239
there are there joke writing sites that you know about?

1361
01:06:29,480 --> 01:06:32,159
Speaker 4: Honestly, can be pretty funny. I haven't done it with Claude.

1362
01:06:32,639 --> 01:06:33,360
I'm not that funny.

1363
01:06:34,079 --> 01:06:40,960
Speaker 2: You know, I've seen your set and Claude, I need

1364
01:06:41,000 --> 01:06:45,400
to writers starting back and forth this I bet you could,

1365
01:06:45,639 --> 01:06:49,400
Like have you ever done that where like, let's be honest,

1366
01:06:49,719 --> 01:06:52,400
you know you got a little bit of a Clark

1367
01:06:52,480 --> 01:06:54,840
Kent vibe to you. I got it, you know, but

1368
01:06:55,320 --> 01:06:58,199
and and obviously but but a little nerdy. Have you

1369
01:06:58,320 --> 01:07:02,920
ever pitted chatchypt Versus Quaude on the same subject? Yeah?

1370
01:07:03,079 --> 01:07:06,000
I knew it all the time. Really, you have to.

1371
01:07:06,039 --> 01:07:07,280
Speaker 4: It's like it's like ab testing.

1372
01:07:07,119 --> 01:07:08,400
Speaker 2: To see which one's better. Yeah.

1373
01:07:08,440 --> 01:07:10,360
Speaker 4: Yeah, And if you're not up to date, because I

1374
01:07:10,400 --> 01:07:14,440
mean even day to day if one model is underburden

1375
01:07:14,760 --> 01:07:16,199
for how many people are using it. So if you're

1376
01:07:16,239 --> 01:07:20,119
using it like noon on a weekday, when millions of

1377
01:07:20,119 --> 01:07:24,360
people are using the platform, it's capacity is actually throttle

1378
01:07:24,360 --> 01:07:26,840
a little bit. It becomes less intelligent, okay. Or if

1379
01:07:26,880 --> 01:07:28,280
a new update is going to come out in the

1380
01:07:28,320 --> 01:07:33,119
back end of developers of whatever they do, architects have

1381
01:07:33,239 --> 01:07:36,239
actually changed the model that day. Some days it is

1382
01:07:36,360 --> 01:07:38,280
just dumb, and then you have to flip back to the.

1383
01:07:39,880 --> 01:07:43,679
Speaker 2: Intelligence, right really like you've burned out, right, You're burned

1384
01:07:43,679 --> 01:07:46,400
out that day. That's interesting that AI can sort of

1385
01:07:46,400 --> 01:07:47,039
be burned out.

1386
01:07:47,159 --> 01:07:50,760
Speaker 4: It can, yeah, And and what the prompt output is

1387
01:07:50,760 --> 01:07:52,519
even if you do it correctly, if you do everything right,

1388
01:07:52,679 --> 01:07:54,920
one day might be different the next day. And you

1389
01:07:55,000 --> 01:07:56,880
have to know, like what you're talking about and know

1390
01:07:56,920 --> 01:07:59,280
that what you're reading isn't necessarily okay, that that was

1391
01:07:59,320 --> 01:07:59,920
really dumb.

1392
01:07:59,760 --> 01:08:02,199
Speaker 3: Like that instead of a circling, I just chose a

1393
01:08:02,199 --> 01:08:06,039
picture without back smoking piking a cup of coffee.

1394
01:08:06,639 --> 01:08:07,920
Speaker 6: New cluster somewhere on fire.

1395
01:08:08,039 --> 01:08:11,000
Speaker 2: It's hysterical, it's funny. That would be really great to

1396
01:08:11,639 --> 01:08:16,800
gone fishing the uh. Okay, So do you ever go

1397
01:08:16,840 --> 01:08:21,279
and like talk to colleges and things or no, because

1398
01:08:21,279 --> 01:08:24,119
I would think places like l T are developing this

1399
01:08:24,960 --> 01:08:27,279
so or do they have kids who are We've.

1400
01:08:27,159 --> 01:08:30,359
Speaker 4: Had conversations and and like there are places that want

1401
01:08:30,439 --> 01:08:34,720
us to kind of speak and say, hey, like give

1402
01:08:34,800 --> 01:08:38,880
us an overview. But colleges in schools in general don't

1403
01:08:38,880 --> 01:08:41,560
really know how to use AI right now, because it does,

1404
01:08:41,680 --> 01:08:45,840
to your point earlier, represent a huge issue in the

1405
01:08:45,960 --> 01:08:48,520
education system. Right right, kids can just do their homework.

1406
01:08:48,560 --> 01:08:53,159
I can take a picture of anyone's hope mark upload

1407
01:08:53,199 --> 01:08:56,520
the picture to chat GBT or claude and then say,

1408
01:08:56,560 --> 01:08:58,880
solve every single problem on this, or do the creative

1409
01:08:58,880 --> 01:09:00,680
writing prompt on whatever kind of homework. It as if

1410
01:09:00,720 --> 01:09:02,479
it's a piece of paper and it's something that a

1411
01:09:02,560 --> 01:09:05,680
human can write or type, it can do it. Which

1412
01:09:05,800 --> 01:09:08,319
so in my opinion, like schools need to embrace that,

1413
01:09:08,720 --> 01:09:11,640
and then it needs to be more practical do things

1414
01:09:11,680 --> 01:09:14,840
in the classroom and take home tests and homework need

1415
01:09:14,880 --> 01:09:16,279
to be made up or even going into like.

1416
01:09:16,279 --> 01:09:19,840
Speaker 2: An well, see this is what I'm saying. I'm thinking

1417
01:09:19,840 --> 01:09:21,800
of a couple things as you're talking. To give you

1418
01:09:21,880 --> 01:09:27,960
an example. It's the people you have a doctor, a

1419
01:09:28,000 --> 01:09:31,039
regular doctor who's seeing patients isn't in the field doing

1420
01:09:31,039 --> 01:09:33,760
the research, right, So you got to be in the

1421
01:09:33,760 --> 01:09:37,279
field of chatch EPT. The teachers, the people that are

1422
01:09:37,319 --> 01:09:41,079
at the institutions are teaching, but they're not in the

1423
01:09:41,079 --> 01:09:43,920
field seeing what's happening. And then the closest thing I

1424
01:09:43,960 --> 01:09:46,399
can think to that was when my sister got lime disease.

1425
01:09:47,000 --> 01:09:49,840
She had she was a child, so still going to

1426
01:09:49,920 --> 01:09:52,800
a pediatrician. I say child, but she was probably like

1427
01:09:52,960 --> 01:09:56,520
sixteen seventeen. He his daughter got it, and he really

1428
01:09:56,680 --> 01:09:59,520
and he did research and found out that penicillin shots

1429
01:09:59,520 --> 01:10:02,000
in the rear end right really burned it off. And

1430
01:10:02,039 --> 01:10:05,119
then how to the rest of your life it's in you. Well,

1431
01:10:05,159 --> 01:10:07,720
it's sort of the same thing. If I'm in the college,

1432
01:10:07,800 --> 01:10:12,239
I'm not out practical application of CHAP GPT for whatever

1433
01:10:12,319 --> 01:10:15,680
business whatever's happening today, So I need somebody to come

1434
01:10:15,680 --> 01:10:18,439
in and show it. And that that's an interesting thing

1435
01:10:18,479 --> 01:10:23,479
because it's almost as though the technology has had gone

1436
01:10:23,560 --> 01:10:29,920
beyond our education system. Yeah, every way, shape and form,

1437
01:10:30,159 --> 01:10:32,800
and so the idea is like not to scare that away.

1438
01:10:32,800 --> 01:10:37,199
But I watched things because I've been substitute teaching in school,

1439
01:10:37,720 --> 01:10:40,560
and I will see things with kids, and I've heard

1440
01:10:40,560 --> 01:10:43,079
teachers say I can tell when you use chat GPT

1441
01:10:43,199 --> 01:10:47,279
because the punctuation and there are words that you are

1442
01:10:47,359 --> 01:10:49,880
certainly not in your vocabulary. But then there was a

1443
01:10:49,880 --> 01:10:52,000
piece of me that I thought, boy, I wish the

1444
01:10:52,079 --> 01:10:55,920
kid would read what they're writing, so then they could

1445
01:10:55,960 --> 01:10:59,279
absorb that and maybe out of curiosity, going to now,

1446
01:10:59,279 --> 01:11:01,840
look show me a fourteen I got a fourteen year

1447
01:11:01,840 --> 01:11:03,319
old boy. He just popped in and out of the studio.

1448
01:11:03,399 --> 01:11:05,600
You think he's doing that? Not a chance.

1449
01:11:05,960 --> 01:11:09,359
Speaker 4: So what if we turned school into while students were

1450
01:11:09,399 --> 01:11:11,359
in school? While they were in class, it was only

1451
01:11:11,399 --> 01:11:15,680
about reading and recomprehension and problem solving, yes, and less

1452
01:11:15,720 --> 01:11:18,600
about the writing about problems they don't care about because

1453
01:11:18,600 --> 01:11:19,399
AI can do those.

1454
01:11:19,520 --> 01:11:22,560
Speaker 2: Well, see that? Okay, So that that's a great thing.

1455
01:11:23,039 --> 01:11:26,039
And I've only been doing this for a few weeks,

1456
01:11:26,119 --> 01:11:28,399
and it's interesting to me. It was just something I

1457
01:11:29,279 --> 01:11:31,760
with a fourteen year old boy who hasn't lived with

1458
01:11:31,800 --> 01:11:33,159
me for four years, all of a sudden comes to

1459
01:11:33,159 --> 01:11:36,359
live with me. My grocery bill's gone up. Everything's gone up,

1460
01:11:36,399 --> 01:11:38,119
like I'm buying phones. I didn't know I had to

1461
01:11:38,119 --> 01:11:40,000
buy it's another three hundred dollars every day. He's a

1462
01:11:40,000 --> 01:11:43,399
three hundred dollars purchase somewhere. So I go, I got

1463
01:11:43,399 --> 01:11:45,520
to do something during the day, right, So I do

1464
01:11:45,640 --> 01:11:49,560
this with the substitute teaching, and I've really enjoyed it,

1465
01:11:49,680 --> 01:11:53,079
and I like the kids to high school kid, it's

1466
01:11:53,079 --> 01:11:56,359
just because they're to me. I really thought about this,

1467
01:11:56,479 --> 01:11:58,479
and I go, I think they can teach me something,

1468
01:11:59,119 --> 01:12:02,000
which I may sound dumb, but I really do. And

1469
01:12:02,239 --> 01:12:04,840
I'm watching them and I'm seeing how they interact with

1470
01:12:04,920 --> 01:12:08,399
things and how they're embracing the technology and how much

1471
01:12:08,439 --> 01:12:10,960
easier it is for them. Now. One of the things

1472
01:12:11,000 --> 01:12:13,439
you said, right, because a lot of the math stuff

1473
01:12:13,640 --> 01:12:17,039
in the I'll say the lower end of high school

1474
01:12:17,159 --> 01:12:21,119
ninth tenth grade right now would be algebra and finding

1475
01:12:21,159 --> 01:12:23,880
the slope intercept of things like if you're going to

1476
01:12:23,920 --> 01:12:26,600
build stairs, you probably need to know that rise run.

1477
01:12:26,680 --> 01:12:28,760
I've built stairs in my life. I've had to do

1478
01:12:28,880 --> 01:12:32,920
rise run chat GPT can do that. What these kids

1479
01:12:32,920 --> 01:12:34,760
will say is when am I ever going to use

1480
01:12:34,760 --> 01:12:38,520
this in my life? Fair question. My answer back is

1481
01:12:39,439 --> 01:12:41,760
knowledge for the sake of knowledge is great and it

1482
01:12:41,880 --> 01:12:45,399
helps you to think creatively, you know what I'm saying,

1483
01:12:45,560 --> 01:12:47,840
or critically I shouldn't say creatively, but critically you can

1484
01:12:47,880 --> 01:12:52,399
actually look in problem solve. These these same steps that

1485
01:12:52,439 --> 01:12:54,920
you're taking to problem solve can be used in many

1486
01:12:54,920 --> 01:12:58,600
different ways. Do we lose that with CHAT GPT, doing

1487
01:12:58,640 --> 01:13:01,319
that work for us or do we maybe grow in

1488
01:13:01,399 --> 01:13:04,479
other areas? I don't know the answer. I ask you expert.

1489
01:13:05,159 --> 01:13:07,600
Speaker 4: In my opinion, if you're using AI in the right way,

1490
01:13:07,640 --> 01:13:09,359
then it's just going to take us to the next level.

1491
01:13:09,359 --> 01:13:12,600
But we have to make sure that we're keeping that

1492
01:13:12,720 --> 01:13:16,439
human element of Okay, this is a tool, use the tool,

1493
01:13:16,520 --> 01:13:19,359
but then go beyond it, because I mean, look at

1494
01:13:19,640 --> 01:13:23,800
uh a few hundred years ago, like there wasn't like

1495
01:13:24,560 --> 01:13:29,039
anything like what we have now, and their processes were

1496
01:13:29,039 --> 01:13:32,439
a lot more manual, right, And the Industrial Revolution happened, Yes.

1497
01:13:32,319 --> 01:13:35,000
Speaker 2: Yes, yes, kept saying things kept evolving.

1498
01:13:34,680 --> 01:13:36,520
Speaker 4: Right, and they're like, oh no, this is the end

1499
01:13:36,800 --> 01:13:40,800
nobody's gonna have. But no, it just became what the

1500
01:13:40,880 --> 01:13:44,520
average worker, their day to day job became something different.

1501
01:13:44,520 --> 01:13:46,439
So maybe dad analytics, yes, those kind of jobs are

1502
01:13:46,439 --> 01:13:48,039
gonna start going away, but maybe.

1503
01:13:47,880 --> 01:13:50,800
Speaker 2: They tho't like them.

1504
01:13:50,920 --> 01:13:52,520
Speaker 4: But now we could take that and they get set

1505
01:13:52,520 --> 01:13:55,720
of A prompt engineer is a job, a job that

1506
01:13:55,760 --> 01:13:58,880
I could see actually like starting to replace that because

1507
01:13:58,880 --> 01:14:00,800
it's still low skill, it's not still a difficult thing

1508
01:14:00,840 --> 01:14:02,359
to do. But if you could, like if you take

1509
01:14:02,399 --> 01:14:04,279
somebody that doesn't know what they're doing in chat GPT

1510
01:14:04,800 --> 01:14:07,479
and give them a task or a question or anything

1511
01:14:07,560 --> 01:14:12,680
like that and say, okay, figure it out and they

1512
01:14:12,800 --> 01:14:14,439
just kind of talk to it and guess their way

1513
01:14:14,479 --> 01:14:17,000
through it, versus somebody who actually knows how to give

1514
01:14:17,119 --> 01:14:20,399
the context of the question, why they need the question,

1515
01:14:20,600 --> 01:14:22,840
what the goal needs to be, things like that over

1516
01:14:22,920 --> 01:14:29,239
explains it, they're gonna get a wildly better answer from program.

1517
01:14:29,640 --> 01:14:31,680
So you can then take that and put it into

1518
01:14:31,720 --> 01:14:33,840
any business and say, okay, we need to prompt engineer

1519
01:14:33,880 --> 01:14:36,000
and go into any task that we have, make sure

1520
01:14:36,000 --> 01:14:39,159
we're maximizing our AI prompting whatever you like.

1521
01:14:39,319 --> 01:14:40,199
Speaker 2: Have you interest.

1522
01:14:40,319 --> 01:14:43,000
Speaker 4: It's not a high end skill, but it's about the

1523
01:14:43,000 --> 01:14:45,039
same level as a data analytics.

1524
01:14:44,479 --> 01:14:45,199
Speaker 6: Like entry level.

1525
01:14:45,319 --> 01:14:48,399
Speaker 2: Yes, but something that again would be needed right to

1526
01:14:48,399 --> 01:14:50,600
give it. Yeah, a little more modern, Kevin, I'll give

1527
01:14:50,600 --> 01:14:52,960
you a funny story today. I wish I had chat

1528
01:14:53,039 --> 01:14:57,359
GPT to polish this answer so much like I'm telling

1529
01:14:57,399 --> 01:15:01,520
these guys in a math support like study hall, right,

1530
01:15:01,640 --> 01:15:03,840
these kids need a little more help with stuff. And

1531
01:15:03,880 --> 01:15:06,319
this one girl's like, she's complaining, when am I ever

1532
01:15:06,359 --> 01:15:08,359
gonna use this blah blah blah blah blah. And she

1533
01:15:08,399 --> 01:15:11,119
had a huge personality and she was funny and she

1534
01:15:11,239 --> 01:15:14,600
was personable, and she was chatty and talking to me

1535
01:15:14,680 --> 01:15:20,000
and just a nice kid. And I said, I go,

1536
01:15:20,960 --> 01:15:24,560
you can't have this bigger personality and not be smart.

1537
01:15:24,840 --> 01:15:27,720
And this other kid turns around and goes, wow, he

1538
01:15:27,880 --> 01:15:32,600
just low key called you stupid. And I went those

1539
01:15:32,640 --> 01:15:35,520
words never left my mouth. I go, I never said that.

1540
01:15:35,600 --> 01:15:38,319
I just said, you can't have all this like she

1541
01:15:38,399 --> 01:15:40,439
had a big vocabulary, and she was funny, and she

1542
01:15:40,520 --> 01:15:44,279
was really like just this personality just took up the room, right,

1543
01:15:44,319 --> 01:15:46,760
And I found it entertaining. I found everything about this

1544
01:15:46,840 --> 01:15:51,079
kid interesting. And I go, you can't be that this

1545
01:15:51,199 --> 01:15:54,079
bigger personality and not be smart. And he goes, you

1546
01:15:54,199 --> 01:15:56,079
low key called her stupid. I go, wow, I just

1547
01:15:56,119 --> 01:15:59,239
got chatchepd by a fourteen year old kid. That's awesome.

1548
01:15:59,359 --> 01:16:02,680
That's great. Well, guys, I find this really interesting and

1549
01:16:02,720 --> 01:16:07,479
I think that. Do you have a business card? God

1550
01:16:07,600 --> 01:16:08,079
damn it.

1551
01:16:09,039 --> 01:16:10,079
Speaker 4: We're digital guys, man.

1552
01:16:10,159 --> 01:16:12,800
Speaker 2: Oh, okay, you're digital guys. But is there a website

1553
01:16:12,840 --> 01:16:13,560
that people can go to?

1554
01:16:13,640 --> 01:16:17,439
Speaker 5: Yes week website which is at this time basic. We've

1555
01:16:17,439 --> 01:16:20,000
been wildly busy, Yes, reconstructing it.

1556
01:16:21,439 --> 01:16:23,039
Speaker 6: Yeah, rock AI dot us.

1557
01:16:24,399 --> 01:16:27,239
Speaker 5: We have a Facebook, we have a LinkedIn, and one

1558
01:16:27,279 --> 01:16:29,560
of the biggest things that we're working on right now

1559
01:16:29,640 --> 01:16:31,960
is we actually have an event coming up in December.

1560
01:16:32,560 --> 01:16:35,760
So December fourth at five thirty pm at Tony D's.

1561
01:16:36,039 --> 01:16:39,840
Speaker 2: Okay, that's a Sunday, right, No, No, that's a Wednesday.

1562
01:16:39,880 --> 01:16:43,039
I have jury duty that week December second, I get

1563
01:16:43,039 --> 01:16:43,880
called for jury duty.

1564
01:16:44,479 --> 01:16:48,119
Speaker 5: So we bought the back room to have an event

1565
01:16:48,239 --> 01:16:51,359
where we could bring business owners or really anybody that's

1566
01:16:51,399 --> 01:16:54,399
interested in AI. We're gonna put it on a four

1567
01:16:54,399 --> 01:16:56,960
hour event. I mean probably two hours of really talking.

1568
01:16:57,000 --> 01:17:00,359
It's a four hour event and questions and answers. You know,

1569
01:17:00,560 --> 01:17:02,560
we're going to have you know, some of our partners.

1570
01:17:02,600 --> 01:17:04,840
We're going to show what we do, how we can

1571
01:17:04,840 --> 01:17:07,039
help and kind of do a little bit more of this.

1572
01:17:07,640 --> 01:17:09,880
Speaker 2: Yeah, and I and it would be let's just say,

1573
01:17:09,960 --> 01:17:11,439
any business you run a gym.

1574
01:17:11,600 --> 01:17:12,880
Speaker 6: It's anything it can help you.

1575
01:17:13,640 --> 01:17:16,399
Speaker 4: We can't help all businesses equally, but no, we can't

1576
01:17:16,399 --> 01:17:17,079
help any business.

1577
01:17:17,159 --> 01:17:19,079
Speaker 2: Yeah, any business. That's what I'm thinking, is like, there

1578
01:17:19,159 --> 01:17:22,720
is a way to make yourself more efficient using technology

1579
01:17:22,800 --> 01:17:27,319
that isn't going to cost you a salary and benefits

1580
01:17:27,319 --> 01:17:30,319
and all that, which is maybe I shouldn't be saying that,

1581
01:17:30,359 --> 01:17:33,159
but and that's the fear, right, that's the fear that

1582
01:17:33,199 --> 01:17:33,880
people have.

1583
01:17:34,279 --> 01:17:36,800
Speaker 4: But augment their employees that they have.

1584
01:17:36,800 --> 01:17:39,479
Speaker 2: Now, yes, right, and grow and then maybe.

1585
01:17:39,880 --> 01:17:43,319
Speaker 4: Take away jobs trying to make people work better and

1586
01:17:43,439 --> 01:17:45,520
more efficiently and get more done with less time.

1587
01:17:45,760 --> 01:17:47,199
Speaker 2: Yeah, I think it's great working here.

1588
01:17:47,199 --> 01:17:49,119
Speaker 3: I must be like, hey, we don't get salary, we

1589
01:17:49,119 --> 01:17:49,960
don't get benefits.

1590
01:17:52,920 --> 01:17:58,439
Speaker 2: Chad KM, Jack KM right there, Brendan Fraser and Cody Brendan,

1591
01:17:58,439 --> 01:18:01,479
thank you guys for for coming then. And Brendan, I

1592
01:18:01,520 --> 01:18:05,960
hope that uh someday maybe you have jet cheapt write

1593
01:18:05,960 --> 01:18:08,800
your script and you I don't know, getting.

1594
01:18:08,520 --> 01:18:09,800
Speaker 4: The partner with the real one.

1595
01:18:09,800 --> 01:18:13,439
Speaker 2: There you go. I think it's great. It's what is

1596
01:18:13,439 --> 01:18:14,199
it rock AI?

1597
01:18:14,399 --> 01:18:15,119
Speaker 6: It's rock AI.

1598
01:18:15,199 --> 01:18:17,720
Speaker 5: Yeah, And if anybody's interested in going to the event,

1599
01:18:17,960 --> 01:18:20,319
we have an event break just have to click on

1600
01:18:20,439 --> 01:18:22,479
the event bright link if you do a search for

1601
01:18:22,560 --> 01:18:23,600
it in their portal.

1602
01:18:25,640 --> 01:18:27,520
Speaker 2: Just so you just look for rock Ai.

1603
01:18:27,640 --> 01:18:29,720
Speaker 5: It's a free it's a free event, but we have

1604
01:18:29,800 --> 01:18:31,279
to make sure that you have to r s VP.

1605
01:18:31,560 --> 01:18:33,199
Speaker 6: Okay, tell Tony how many people?

1606
01:18:33,520 --> 01:18:33,840
Speaker 12: Yeah?

1607
01:18:33,880 --> 01:18:36,960
Speaker 2: Okay, So and that's on December fourth, Yeah, which is

1608
01:18:37,000 --> 01:18:39,880
a Wednesday. We say Wednesday, Yes, Saturday, Monday, Yes, I

1609
01:18:39,920 --> 01:18:42,640
did in my in my mind, I'm going it's Monday.

1610
01:18:42,640 --> 01:18:43,880
It's December second.

1611
01:18:43,880 --> 01:18:44,600
Speaker 3: He needs a calendar.

1612
01:18:44,800 --> 01:18:47,000
Speaker 2: I do. I need a calendar, I need chet CHPT,

1613
01:18:47,119 --> 01:18:49,640
I need all of it. Thank you, gentlemen. We will

1614
01:18:49,640 --> 01:18:52,479
take a moment and be right back. Victor Chrysler Dodge

1615
01:18:52,520 --> 01:18:55,680
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1635
01:20:00,159 --> 01:20:06,239
Speaker 12: Colon's Blowing to the Empty Stands, Super Bowl Dreams, sent.

1636
01:20:11,239 --> 01:20:14,800
Speaker 13: The Season, Lem State and Hop Bricks down.

1637
01:20:14,640 --> 01:20:23,159
Speaker 3: By the Level Dreams, Do the Empty Stands, super Gold Dreams.

1638
01:20:21,560 --> 01:20:24,279
Speaker 10: And sent Stan Blowing Registration.

1639
01:20:24,560 --> 01:20:27,600
Speaker 2: Vin wanted a prompt a nineties alternative song about how

1640
01:20:27,600 --> 01:20:29,680
the Bills will lose the Super Bowl this year because

1641
01:20:29,680 --> 01:20:33,279
he's a Patriots fan Stu and then what Bridge Greg

1642
01:20:33,319 --> 01:20:36,800
Connors will jump off him the Princess time as the

1643
01:20:36,840 --> 01:20:39,920
billstall one long time, Greg Will.

1644
01:20:40,119 --> 01:20:42,840
Speaker 3: By the Precious times, the phill small one more time.

1645
01:20:42,840 --> 01:20:47,279
Speaker 10: Don't rivers merch downtown SHOs upon mine.

1646
01:20:48,359 --> 01:20:50,159
Speaker 12: The little starts champ.

1647
01:20:50,479 --> 01:20:53,960
Speaker 2: All right, here's the other version of its.

1648
01:20:52,960 --> 01:20:56,279
Speaker 7: Being directed, gusting off a little town, just breaking hearts out.

1649
01:20:56,319 --> 01:20:58,640
It's under round, Colen's blown.

1650
01:20:58,720 --> 01:20:59,840
Speaker 10: Do they empty stand?

1651
01:21:00,199 --> 01:21:11,039
Speaker 7: Super Bowl dreams? The red will saying goesn't not a

1652
01:21:11,119 --> 01:21:16,960
little dreams? Thought your lives step grips.

1653
01:21:16,600 --> 01:21:17,359
Speaker 1: And a hard freak.

1654
01:21:20,159 --> 01:21:26,960
Speaker 2: I like the first I think better winess. It's a

1655
01:21:27,039 --> 01:21:29,880
great hook, though, correct will find.

1656
01:21:33,359 --> 01:21:35,439
Speaker 3: Who's gonna get the text hurt you or me tomorrow?

1657
01:21:35,680 --> 01:21:36,319
Speaker 2: So we call.

1658
01:21:38,359 --> 01:21:38,560
Speaker 3: Yes.

1659
01:21:38,880 --> 01:21:42,680
Speaker 2: That's absolutely great.

1660
01:21:42,760 --> 01:21:44,800
Speaker 3: Kevin wrote song for you for dance bandform.

1661
01:21:46,640 --> 01:21:50,479
Speaker 2: That's pretty funny. But these guys from rock AI are

1662
01:21:50,560 --> 01:21:54,520
saying that they can even make your business run more efficiently.

1663
01:21:55,119 --> 01:21:59,359
Can we say, how like employee theft that sort of thing?

1664
01:21:59,520 --> 01:22:02,079
Speaker 6: Oh yeah, I mean we can absolutely cover that.

1665
01:22:02,720 --> 01:22:05,000
Speaker 5: But no, there there are programs, especially like in the

1666
01:22:05,039 --> 01:22:09,079
industrial space that we that we utilize that you know,

1667
01:22:09,159 --> 01:22:13,359
we can implement into camera systems and actually track employee

1668
01:22:13,399 --> 01:22:16,680
efficiency or really more importantly safety for a lot of

1669
01:22:16,720 --> 01:22:19,520
companies because safety is it's a big thing. Yeah, you know,

1670
01:22:19,600 --> 01:22:23,520
are you lifting things properly? You know, are forklifts being

1671
01:22:24,039 --> 01:22:25,640
used in stunts type of thing?

1672
01:22:27,159 --> 01:22:30,680
Speaker 2: And we can actually we can actually forklift w forklift jousting.

1673
01:22:31,720 --> 01:22:37,000
Speaker 5: That's so you can build real time reports. But you know,

1674
01:22:37,279 --> 01:22:39,000
and that's that's the other thing. You know, people are

1675
01:22:39,039 --> 01:22:40,880
gonna be like, oh, that's horrible. I don't want a

1676
01:22:40,960 --> 01:22:44,319
camera breathing down my neck. That's not how it's being used.

1677
01:22:44,359 --> 01:22:46,479
It's really being used for safety. But it can also

1678
01:22:46,640 --> 01:22:49,239
build accountability.

1679
01:22:49,520 --> 01:22:52,039
Speaker 8: But you can also reward your employees too. You know,

1680
01:22:52,079 --> 01:22:53,159
it doesn't have to be a bad thing.

1681
01:22:53,279 --> 01:22:54,840
Speaker 5: It's one of those things where if you're doing good

1682
01:22:54,880 --> 01:22:57,840
work and you're being safe and everything, you should be

1683
01:22:57,920 --> 01:22:59,680
building a reward structure based off of that.

1684
01:23:00,079 --> 01:23:00,279
Speaker 2: They have.

1685
01:23:00,760 --> 01:23:02,479
Speaker 3: I mean, like I even said that that a I

1686
01:23:02,800 --> 01:23:04,560
even kind of looks out for you, Like if you're

1687
01:23:04,760 --> 01:23:07,119
put in how do I commit suicide? It's going to

1688
01:23:07,159 --> 01:23:09,039
flag your accounting and do things like that.

1689
01:23:09,600 --> 01:23:12,319
Speaker 5: There's guardrails to that, and that's that's what it's for.

1690
01:23:13,640 --> 01:23:16,520
You know, companies that have accidents. That's obviously costly, but

1691
01:23:16,560 --> 01:23:18,840
they don't want their employees, especially that they put money

1692
01:23:18,880 --> 01:23:20,840
and time into training, getting hurt.

1693
01:23:21,000 --> 01:23:22,520
Speaker 6: So we can keep that from happening.

1694
01:23:22,920 --> 01:23:25,640
Speaker 2: The uh but Greg got a business. What do you mean,

1695
01:23:26,039 --> 01:23:28,560
oh Ai, I don't want people get hurt. Hurt?

1696
01:23:28,760 --> 01:23:29,600
Speaker 4: Well, how to pivot.

1697
01:23:31,039 --> 01:23:34,920
Speaker 2: But they have software now for students that a teacher

1698
01:23:35,000 --> 01:23:39,279
can go in and see how many key strokes and

1699
01:23:39,439 --> 01:23:43,439
how long you worked on something. Right, So the teacher

1700
01:23:43,560 --> 01:23:46,800
was explaining to a class, going, hey, I had a

1701
01:23:46,920 --> 01:23:51,800
senior who this was the question. He spent one minute

1702
01:23:51,800 --> 01:23:56,560
in twenty eight seconds and hit three key strokes because

1703
01:23:56,600 --> 01:23:58,760
all he did was copy and pasted from somewhere else.

1704
01:23:59,000 --> 01:24:01,359
And that's not what I want. And they can see it,

1705
01:24:01,560 --> 01:24:03,239
and they can see it all in real time as

1706
01:24:03,239 --> 01:24:05,720
it happens. They played the video back like he played

1707
01:24:05,800 --> 01:24:08,319
back the bagage, like, oh my god, I would have

1708
01:24:08,359 --> 01:24:09,199
been so screwed.

1709
01:24:09,520 --> 01:24:12,680
Speaker 3: There was people that were fired from remote jobs because

1710
01:24:12,680 --> 01:24:14,439
they went on Amazon, you know, and since they had

1711
01:24:14,439 --> 01:24:16,640
that thing where it would just a little check into it. Yeah,

1712
01:24:17,640 --> 01:24:19,479
there was people that were doing that on their mouse,

1713
01:24:20,239 --> 01:24:22,800
going out to shop or whatever for hours on end.

1714
01:24:22,960 --> 01:24:25,319
So and they were able to track and say, yep,

1715
01:24:25,479 --> 01:24:26,960
you just clicking.

1716
01:24:26,720 --> 01:24:28,760
Speaker 4: This if we want to go like that far with it, Like,

1717
01:24:28,800 --> 01:24:31,239
then what's stopping students from having the script written and

1718
01:24:31,319 --> 01:24:32,800
then just copying the strip script?

1719
01:24:32,840 --> 01:24:33,800
Speaker 2: A completely right?

1720
01:24:33,960 --> 01:24:38,520
Speaker 4: Right, But in that case, like if if an employee

1721
01:24:38,560 --> 01:24:40,560
is able to do that and automate their job like that,

1722
01:24:42,439 --> 01:24:45,720
the job's wrong. Like change the job, make it one

1723
01:24:45,920 --> 01:24:49,319
that is incorporates the AI so factor that in, Oh

1724
01:24:49,439 --> 01:24:53,399
they can do that, so then make AI do that,

1725
01:24:53,680 --> 01:24:55,199
and then now your job description is this.

1726
01:24:55,520 --> 01:24:57,720
Speaker 2: Yeah, it's almost like you need the people to be

1727
01:24:57,880 --> 01:24:59,800
the testers to bend the rules a little bit to

1728
01:25:00,000 --> 01:25:01,039
figure out what's next.

1729
01:25:01,199 --> 01:25:04,039
Speaker 4: The people that can do that that automate their jobs

1730
01:25:04,079 --> 01:25:06,680
and then walk away from the computer honestly, like it.

1731
01:25:06,760 --> 01:25:09,359
Speaker 3: Wasn't even they weren't. They were just doing it so

1732
01:25:09,439 --> 01:25:10,560
it would show they weren't away.

1733
01:25:10,680 --> 01:25:15,000
Speaker 4: It's that management or it doesn't understand AI and hasn't

1734
01:25:15,079 --> 01:25:18,079
evolved the role to fit the modern world.

1735
01:25:18,279 --> 01:25:21,039
Speaker 2: Well, I hear what you're saying, because you can see

1736
01:25:21,159 --> 01:25:25,199
sometimes people on remote jobs. I can see, Hey, Brendan's

1737
01:25:25,199 --> 01:25:27,720
at his desk right now, or Brendan's online and it

1738
01:25:27,800 --> 01:25:31,199
looks like he's there and he's or Brendan's in a meeting, right,

1739
01:25:31,279 --> 01:25:33,560
and it looks like that Brendan could be out, you know,

1740
01:25:34,520 --> 01:25:38,079
slamming shots, doing whatever Brendan wants to do. And that's

1741
01:25:39,520 --> 01:25:42,319
a different thing, And I think that leads to a

1742
01:25:42,399 --> 01:25:48,399
lot of distrust with old school bosses versus somebody who's

1743
01:25:48,439 --> 01:25:51,119
a little more I guess, modern new school.

1744
01:25:51,279 --> 01:25:55,039
Speaker 4: Why does the job exist? What is the output requirement

1745
01:25:55,079 --> 01:25:57,239
for that job to be profitable for the business? What's

1746
01:25:57,279 --> 01:25:58,680
the ROI is the job getting done?

1747
01:25:58,760 --> 01:25:59,159
Speaker 2: Yes or no?

1748
01:25:59,479 --> 01:26:01,119
Speaker 4: Like that's that's kind of the modern way of looking

1749
01:26:01,119 --> 01:26:02,680
at it. The trust is a big thing, and I

1750
01:26:02,720 --> 01:26:05,439
think that's a different conversation about the big return to

1751
01:26:05,520 --> 01:26:06,359
office push.

1752
01:26:06,199 --> 01:26:09,319
Speaker 2: But yeah, it is. There is a huge, huge right

1753
01:26:09,399 --> 01:26:12,640
now right with everybody pushing to get back into the office.

1754
01:26:13,560 --> 01:26:14,119
Do they have that?

1755
01:26:14,760 --> 01:26:16,560
Speaker 3: Yeah, I'm supposed to be in three times a week.

1756
01:26:16,600 --> 01:26:19,720
Can I I find myself honestly less productive in the

1757
01:26:19,760 --> 01:26:21,960
office than I do at home. Yeah, because I'm up

1758
01:26:22,039 --> 01:26:23,960
at the office, I'm wandering around talking to people I

1759
01:26:24,000 --> 01:26:27,000
haven't seen, catching up with this at home. If I

1760
01:26:27,039 --> 01:26:29,239
have a question for somebody, toument I am Other than that,

1761
01:26:29,319 --> 01:26:30,840
I'm not bothering anybody.

1762
01:26:31,119 --> 01:26:35,920
Speaker 2: Yeah, hmm, what's the better way in your opinion, is

1763
01:26:36,000 --> 01:26:38,199
there a better way? It depends on the business.

1764
01:26:38,439 --> 01:26:43,000
Speaker 4: I firmly believe that management and companies that operate basically

1765
01:26:43,159 --> 01:26:45,239
embracing AI in every single role and knowing people are

1766
01:26:45,279 --> 01:26:48,920
going to use it and then changing every single role

1767
01:26:48,960 --> 01:26:50,760
to accommodate that, and then say, okay, this is the

1768
01:26:50,840 --> 01:26:52,640
expectation and being fair about it.

1769
01:26:52,680 --> 01:26:55,720
Speaker 2: Can you lower salaries because AI is there?

1770
01:26:56,000 --> 01:26:59,039
Speaker 4: Well, if you're not doing if you're doing it wrong,

1771
01:26:59,239 --> 01:27:01,159
then you can try, But then that job's not be

1772
01:27:01,359 --> 01:27:03,359
looked at as very valuable and nobodys gonnapply to it.

1773
01:27:03,520 --> 01:27:06,279
Speaker 2: I got you, Okay? Should we call Greg? I got

1774
01:27:06,359 --> 01:27:08,640
his I'm all set. Here's yeah, give him a call.

1775
01:27:08,680 --> 01:27:11,680
See what he says. See if you answers great Connors,

1776
01:27:11,960 --> 01:27:14,000
Connors and Faris. We have a new song for him.

1777
01:27:16,239 --> 01:27:18,760
Tell him then it's Zeer Faull. What's up?

1778
01:27:18,800 --> 01:27:19,279
Speaker 12: What up?

1779
01:27:21,560 --> 01:27:24,000
Speaker 3: He didn't want to answer this call.

1780
01:27:24,119 --> 01:27:27,600
Speaker 2: We're on the podcast and we have we have some

1781
01:27:27,800 --> 01:27:31,439
AI guys in tonight and we were talking about different

1782
01:27:31,479 --> 01:27:34,279
AI platforms and one of them is called Suno and

1783
01:27:34,359 --> 01:27:38,680
it'll write songs for you. So your friend who is

1784
01:27:38,840 --> 01:27:41,079
just such a huge fan of yours, I don't know

1785
01:27:41,079 --> 01:27:42,319
if you know Kevin Mirror.

1786
01:27:42,960 --> 01:27:43,079
Speaker 14: Uh.

1787
01:27:44,279 --> 01:27:47,159
Speaker 2: He asked for a nineties alternative song about how the

1788
01:27:47,239 --> 01:27:51,119
Buffalo Bills lose the Super Bowl this year and what

1789
01:27:51,560 --> 01:27:54,760
bridge Greg will jump off? I didn't have to bridge part.

1790
01:27:55,720 --> 01:27:58,239
And here is said song. I don't know if you

1791
01:27:58,239 --> 01:27:59,520
can hear it, but there's one little.

1792
01:28:02,079 --> 01:28:06,880
Speaker 12: Town skin breaking clocks every time Colan's blowing to the

1793
01:28:07,039 --> 01:28:11,039
empty stands. Super Bowl dreams sent.

1794
01:28:13,159 --> 01:28:14,600
Speaker 2: Here we go, here comes to Greg Park.

1795
01:28:14,720 --> 01:28:19,640
Speaker 13: The hook is, Craig, you ever stayed and hope Gregs

1796
01:28:19,720 --> 01:28:23,479
down by the rivel wet dreams, A little Colon's blown

1797
01:28:23,560 --> 01:28:26,239
to the empty stands, super Gold.

1798
01:28:26,079 --> 01:28:31,239
Speaker 7: Dreams like sand say stand bone web stayed, Gregs down

1799
01:28:31,359 --> 01:28:33,399
by the river web dreams, A little.

1800
01:28:33,840 --> 01:28:36,720
Speaker 2: Breaks down by the river for dreams a lope. I

1801
01:28:36,800 --> 01:28:38,760
don't know, Craig. I feel a little bad, but it

1802
01:28:38,840 --> 01:28:40,560
was kind of funny. We did get a good chuckle

1803
01:28:40,600 --> 01:28:40,880
out of it.

1804
01:28:42,640 --> 01:28:46,359
Speaker 14: Well, I mean, it is funny, but that's probably the

1805
01:28:46,439 --> 01:28:51,239
reality if it happened. No, no, no sorrows.

1806
01:28:51,319 --> 01:28:52,720
Speaker 3: You're gonna get a loped up the Bills and the

1807
01:28:52,760 --> 01:28:53,159
Super Bowl.

1808
01:28:53,239 --> 01:28:57,239
Speaker 2: No, I think, uh, I think the chances of the

1809
01:28:57,319 --> 01:28:59,720
Bills in the Super Bowl look brighter and brighter every day.

1810
01:29:02,520 --> 01:29:05,119
Speaker 14: Yeah, I think you know. I mean, look, as long

1811
01:29:05,199 --> 01:29:10,239
as the Bills continue to be solid in their like

1812
01:29:10,399 --> 01:29:14,000
how they manage the game and not turn the ball over,

1813
01:29:14,800 --> 01:29:17,279
you know, this defense is stepping up to the challenge.

1814
01:29:17,840 --> 01:29:20,000
And that's the part that I'm thrilled grid with the

1815
01:29:20,079 --> 01:29:23,239
Bills is that the defense. I mean, look, they're deeping up.

1816
01:29:23,359 --> 01:29:25,760
They've been beeping up on that defense, and the fact

1817
01:29:25,800 --> 01:29:28,840
that they were able to hold the Homes to twenty

1818
01:29:28,920 --> 01:29:30,359
one points is huge.

1819
01:29:31,359 --> 01:29:33,680
Speaker 3: How could AI help the Bills win on the field,

1820
01:29:35,439 --> 01:29:36,359
That's a great question.

1821
01:29:36,640 --> 01:29:39,800
Speaker 2: I don't watch football, I don't watch the bull This.

1822
01:29:40,000 --> 01:29:42,199
Speaker 14: Is how I think AI can help the Bills is

1823
01:29:42,279 --> 01:29:48,159
that is that they have to utilize, especially against defenses

1824
01:29:48,199 --> 01:29:51,399
that play as much man demand as Spags does. With

1825
01:29:51,560 --> 01:29:56,119
the Chiefs, they got to use motion more. I mean

1826
01:29:56,439 --> 01:29:58,279
there is Dan, there is drilling there.

1827
01:29:58,520 --> 01:29:59,760
Speaker 2: No, he's not not tonight.

1828
01:30:00,039 --> 01:30:05,119
Speaker 14: Oh all right, well, I just it's for me. It's uh,

1829
01:30:05,600 --> 01:30:08,239
it's a matter of that offense, right, I mean Brady

1830
01:30:08,720 --> 01:30:13,319
did well, but look the AI, the AI that Josh

1831
01:30:13,399 --> 01:30:17,640
has played on that fourth and two play is epics

1832
01:30:18,680 --> 01:30:22,039
because the Chiefs ran the perfect defense for the play

1833
01:30:22,159 --> 01:30:24,439
that was called because the built up that they'd be

1834
01:30:24,640 --> 01:30:28,279
manned a man but they actually did a press They

1835
01:30:28,359 --> 01:30:31,680
did a press zone coverage. So Josh is about to

1836
01:30:31,720 --> 01:30:34,600
throw an intersection to recognize it. Thank God that AI

1837
01:30:34,760 --> 01:30:44,279
that he has there. You kidding me. I'm plugged in

1838
01:30:44,399 --> 01:30:47,920
right now, Kevin, and uh, and he made the adjustment

1839
01:30:48,199 --> 01:30:50,720
and and it, you know, and then he just made

1840
01:30:50,840 --> 01:30:54,199
he just made it happen. Josh making dreams happen. Man,

1841
01:30:54,319 --> 01:30:57,840
it was Uh, it was exciting. Too bad, you guys weren't.

1842
01:30:57,640 --> 01:31:00,279
Speaker 2: There that I got to tell you something that looked

1843
01:31:00,399 --> 01:31:07,079
like just an environment that you'll never forget loud exciting,

1844
01:31:08,000 --> 01:31:11,079
you know. And I get it. It's regular season. What

1845
01:31:11,239 --> 01:31:13,880
happens in the playoffs, We know that. But this was

1846
01:31:14,000 --> 01:31:17,279
it was nice to end their undefeated season mark.

1847
01:31:17,319 --> 01:31:18,399
Speaker 3: The soldier was looking for you.

1848
01:31:19,520 --> 01:31:22,720
Speaker 14: Oh, I mean, I gotta tell you. I mean people

1849
01:31:22,800 --> 01:31:27,079
were like, ah, you know, McDermott, humble and hungry. Who's

1850
01:31:27,079 --> 01:31:30,199
gonna remember who won week to eleven in the twenty

1851
01:31:30,319 --> 01:31:33,960
twenty four football season. You know, who's gonna remember this

1852
01:31:34,239 --> 01:31:36,920
team when they're playing in the playoffs and they know

1853
01:31:37,000 --> 01:31:39,279
what it feels like to be at home and how

1854
01:31:39,319 --> 01:31:41,880
important this game was to get a higher seat. This

1855
01:31:42,000 --> 01:31:44,359
game was huge for them. The most important thing for

1856
01:31:44,479 --> 01:31:46,119
me is I think it's going to give them the

1857
01:31:46,159 --> 01:31:50,560
confidence that they need to win and play in the playoffs. Yeah,

1858
01:31:50,600 --> 01:31:54,119
because last the last two years that the Built had

1859
01:31:54,159 --> 01:31:58,560
beaten the Chief in the in the in the in

1860
01:31:58,640 --> 01:32:02,359
the regular season, he's weren't at full strength the Chief.

1861
01:32:02,600 --> 01:32:06,000
Chris Jones was out, Kelsey was out. This year, the

1862
01:32:06,119 --> 01:32:08,960
only person that was out that is of any significance

1863
01:32:09,399 --> 01:32:13,560
was Pacheco, And I don't think Pacheco's gonna make that

1864
01:32:13,800 --> 01:32:16,399
much of a huge difference in the games that come,

1865
01:32:16,439 --> 01:32:19,319
particularly the way they've run the balls without him. Yeah,

1866
01:32:19,479 --> 01:32:21,319
So I think this game for the Bills gives him

1867
01:32:21,319 --> 01:32:23,479
a lot of confidence that they played the Chief full

1868
01:32:23,520 --> 01:32:25,840
strength for the first time and beat him.

1869
01:32:26,359 --> 01:32:30,760
Speaker 2: How about the fact that Milano could be back and

1870
01:32:30,880 --> 01:32:34,600
you've got guys playing so well on defense already. Would

1871
01:32:34,600 --> 01:32:37,720
that be a disruption in your opinion? I mean, really,

1872
01:32:37,840 --> 01:32:39,960
the guy who was many people think is the leader,

1873
01:32:40,039 --> 01:32:42,479
but ye have Bernard playing out of his mind.

1874
01:32:44,119 --> 01:32:46,560
Speaker 14: Yeah, No, Bernard is playing out of his mind. But

1875
01:32:46,760 --> 01:32:50,960
you know, I mean Dorian, Dorian Williams is doing really well.

1876
01:32:51,640 --> 01:32:54,319
But he's still I mean, he had a rough game

1877
01:32:54,399 --> 01:32:58,199
against the Chiefs that that he played well, but there's

1878
01:32:58,239 --> 01:33:02,159
a lot more that that that Mlonald brings to the table,

1879
01:33:02,920 --> 01:33:05,720
that that would be an addition to the team. Now,

1880
01:33:06,079 --> 01:33:08,239
what I think this does is that you know, I

1881
01:33:08,319 --> 01:33:10,840
mean Mlonald's coming off of two injuries.

1882
01:33:10,920 --> 01:33:12,560
Speaker 3: Here, Yeah, right, are you playing?

1883
01:33:14,359 --> 01:33:16,279
Speaker 14: I am playing pac Man. I'm trying to back out

1884
01:33:16,319 --> 01:33:18,680
of the driveway. My mom pinned me in and so

1885
01:33:18,880 --> 01:33:20,640
I'm freaking bouncing off to her car.

1886
01:33:20,960 --> 01:33:23,479
Speaker 2: So I'm sorry. I didn't We should hang up and

1887
01:33:23,600 --> 01:33:28,199
let you go. I didn't mean to disrupt your nightday.

1888
01:33:29,039 --> 01:33:33,560
Speaker 14: Hey, it's just start Tuesday night diet her, that's all,

1889
01:33:33,800 --> 01:33:36,239
you know. Taking mom out for dinner on Tuesday. I

1890
01:33:36,319 --> 01:33:39,039
got a so little, so little love for there. So

1891
01:33:39,479 --> 01:33:42,399
Jen and I are taking her out to dinner, going

1892
01:33:42,520 --> 01:33:45,039
down to Patron Saint, the new steakhouse.

1893
01:33:46,760 --> 01:33:49,680
Speaker 2: Heard many things about Patron Saint, another one of those

1894
01:33:49,760 --> 01:33:52,159
Josh Miles places, and people are loving it.

1895
01:33:53,159 --> 01:33:55,640
Speaker 14: Yeah that's what we're hearing. So you know, I figured

1896
01:33:55,680 --> 01:33:58,680
that I would take take Mom and Jen down to

1897
01:33:58,760 --> 01:34:00,439
try it out and we could give you a review.

1898
01:34:00,640 --> 01:34:07,800
All right, But getting back to Milano getting back to Milano.

1899
01:34:07,880 --> 01:34:10,359
I think what they what this allows this team to

1900
01:34:10,439 --> 01:34:12,399
do is to allow Milano to come back and come

1901
01:34:12,439 --> 01:34:15,359
back at full train. And Milano is the type of

1902
01:34:15,439 --> 01:34:18,439
athlete has a skill set and the experience that he

1903
01:34:18,520 --> 01:34:21,079
can just fit in and now you've got depth there

1904
01:34:21,800 --> 01:34:25,079
and that that definitely helps the defense and changes the

1905
01:34:25,119 --> 01:34:28,760
defense because having two players that have that speed and

1906
01:34:28,800 --> 01:34:32,359
the jilly like Bernard and now Milano fit the system

1907
01:34:32,439 --> 01:34:35,840
so well that again going in the Bills just got

1908
01:34:35,920 --> 01:34:38,439
to stay healthy right coming into December. It's all about

1909
01:34:38,520 --> 01:34:41,920
being healthy in December. But most importantly last year, we

1910
01:34:42,000 --> 01:34:44,800
were healthy in December. We were not healthy in January

1911
01:34:45,359 --> 01:34:47,479
and that's where the and that's where we got banged up,

1912
01:34:47,680 --> 01:34:50,760
and that's where the Chiefs did their thing. So, you know,

1913
01:34:51,199 --> 01:34:54,319
God willing and everything continues to go well and the

1914
01:34:54,359 --> 01:34:57,239
Bills stay healthy through December and into January. Because we

1915
01:34:57,319 --> 01:34:59,560
got banged up in that first playoff game against the Steelers.

1916
01:35:00,079 --> 01:35:04,039
Speaker 2: Yeah we did. But there's something different. I don't know

1917
01:35:04,039 --> 01:35:06,159
if you agree with this or not. There feels like

1918
01:35:06,279 --> 01:35:10,039
there's something different. There was a calm, cool collectiveness with

1919
01:35:10,239 --> 01:35:14,840
this team. Josh making smart moves even the run. You know,

1920
01:35:15,159 --> 01:35:17,720
you're calling it the josh Ai right, seeing a play

1921
01:35:17,920 --> 01:35:20,399
that isn't there and not forcing it and taking off

1922
01:35:21,119 --> 01:35:24,600
there just seems to be something that's I don't know.

1923
01:35:24,880 --> 01:35:27,279
I don't know if it's a team intelligence, not just

1924
01:35:27,359 --> 01:35:30,199
player intelligence, but overall team just seems to be more

1925
01:35:30,239 --> 01:35:32,640
aware of things and you and you go, boy, that

1926
01:35:32,760 --> 01:35:36,760
can only get better? And will that help them?

1927
01:35:37,159 --> 01:35:37,359
Speaker 7: Is this?

1928
01:35:37,960 --> 01:35:40,199
Speaker 2: Is this the super Bowl season? Could this be the

1929
01:35:40,319 --> 01:35:43,439
year that you got two teams that have never won

1930
01:35:43,520 --> 01:35:47,119
a Super Bowl, the Bills and the Lions facing off potentially?

1931
01:35:47,520 --> 01:35:50,640
Speaker 14: Yeah, I think I think you're You're spot on. And

1932
01:35:50,760 --> 01:35:54,600
what this team is is a team. They all have

1933
01:35:54,760 --> 01:35:59,399
a it's all about each other. It's not about not

1934
01:35:59,560 --> 01:36:03,680
about individual it's about the team. And Josh is truly

1935
01:36:03,760 --> 01:36:06,680
the full time leader here. He is the guy, and

1936
01:36:06,840 --> 01:36:09,439
he is humble. He is a very humble person. He

1937
01:36:09,520 --> 01:36:12,439
doesn't look really accolades. He's always pushed it to everybody else.

1938
01:36:13,000 --> 01:36:16,039
Guys respond to that. You got rid of the cancer

1939
01:36:16,520 --> 01:36:18,840
when Giggs was in and he was all about Josh.

1940
01:36:18,920 --> 01:36:20,800
He was all about the love, he was all about

1941
01:36:20,840 --> 01:36:24,119
the team. Everything was good. That was their strongest season.

1942
01:36:24,720 --> 01:36:26,359
It's when all of a sudden he got to be

1943
01:36:26,479 --> 01:36:29,359
about him more so than it didn't seem like the

1944
01:36:29,479 --> 01:36:32,159
team is when you start to get those erosions, you

1945
01:36:32,199 --> 01:36:35,520
start to get those splinters, and that people don't respond

1946
01:36:35,600 --> 01:36:38,760
to that. I mean, the greatest compliment that this team

1947
01:36:39,000 --> 01:36:41,479
received so far this year, in my opinion, was the

1948
01:36:41,600 --> 01:36:44,359
Marii Cooper's comment in the locker room after the game

1949
01:36:44,960 --> 01:36:47,960
about how different it feels, how good it feels to

1950
01:36:48,000 --> 01:36:50,079
be a part of this team, A part of this

1951
01:36:50,319 --> 01:36:53,319
group died. I was just like, you know what, Bill,

1952
01:36:53,479 --> 01:36:55,800
You're spot on. That's the difference.

1953
01:36:56,000 --> 01:37:00,800
Speaker 2: Yeah, it's kind of Look, it kind of comes through

1954
01:37:01,039 --> 01:37:04,439
when you watch this team because there's that it doesn't

1955
01:37:04,479 --> 01:37:08,840
feel forced or hurried or there's just a collective Uh.

1956
01:37:09,640 --> 01:37:13,079
I want to say, a collective confidence with the team

1957
01:37:13,479 --> 01:37:15,600
that you know they they can do this, and look

1958
01:37:15,960 --> 01:37:20,800
they put up great points. Cooper looks like he fits in. Well, uh,

1959
01:37:21,239 --> 01:37:23,399
you know, I can only see you know what happens

1960
01:37:23,439 --> 01:37:25,760
when Keon Coleman comes back or if he is he

1961
01:37:25,840 --> 01:37:28,000
coming back, Yeah, he'll be back, so yeah he should

1962
01:37:28,039 --> 01:37:28,319
be back.

1963
01:37:29,880 --> 01:37:33,119
Speaker 14: Yeah. And again me with Coleman, I'm luke warm with Coleman.

1964
01:37:33,199 --> 01:37:35,760
I don't think Amari Cooper is a great addition for

1965
01:37:35,880 --> 01:37:38,560
Coleman too, because you see how you run routes right.

1966
01:37:38,720 --> 01:37:40,560
He can see what it takes to be a professional.

1967
01:37:40,960 --> 01:37:43,279
And Coleman has evolved and he's had some spots where

1968
01:37:43,279 --> 01:37:45,600
he has played well. The think I'm most impressed with

1969
01:37:45,680 --> 01:37:47,399
Coleman is this blocking up the field.

1970
01:37:47,840 --> 01:37:48,039
Speaker 2: Yep.

1971
01:37:48,279 --> 01:37:51,800
Speaker 14: His downfield blocking to me through a rookie to some

1972
01:37:51,880 --> 01:37:55,079
of the best I've ever seen and even been looked at.

1973
01:37:55,840 --> 01:37:58,239
And I love that kind of stuff. Foot Again, that's

1974
01:37:58,279 --> 01:38:01,119
about being humble. You get big egos. Why am I

1975
01:38:01,199 --> 01:38:04,600
blocking downfield? I'm not getting involved knocking up with my statue.

1976
01:38:05,600 --> 01:38:08,199
I'm not collecting fantasy points for it. Some of the

1977
01:38:08,279 --> 01:38:11,640
guys don't do that though, But Josh and McDermott has

1978
01:38:11,680 --> 01:38:15,319
got each individual person believing that for a higher good

1979
01:38:15,359 --> 01:38:19,199
and for a higher cause. By the way o Cyrus torran,

1980
01:38:19,880 --> 01:38:22,760
you want to talk about unsung heroes, he played Chris

1981
01:38:22,960 --> 01:38:25,960
Jones better than I think any lineman the Bills have

1982
01:38:26,039 --> 01:38:29,600
ever had in any guard, tackle or center position, including

1983
01:38:29,760 --> 01:38:34,399
Eric Woods. That guy was an animal against him on Sunday. Yeah,

1984
01:38:34,680 --> 01:38:36,560
those are the type of things that you get guys

1985
01:38:36,600 --> 01:38:39,279
buying in and playing at that level and trusting the

1986
01:38:39,319 --> 01:38:41,760
guy next to you to do their job. That's what

1987
01:38:41,920 --> 01:38:44,520
makes this team special. And that's what got me, and

1988
01:38:44,760 --> 01:38:46,560
I know so many other people was so excited about it.

1989
01:38:46,960 --> 01:38:48,640
Speaker 2: Yeah, did you buy ten percent?

1990
01:38:50,880 --> 01:38:53,600
Speaker 14: Man? You guys, I mean you guys. I've told you, guys,

1991
01:38:53,640 --> 01:38:55,760
the story about the lines and the bills, the connections

1992
01:38:55,760 --> 01:38:57,560
between the lines and the builds is a lot stronger

1993
01:38:57,640 --> 01:39:00,960
than most people understand or know. Ralph Wilson was part

1994
01:39:01,039 --> 01:39:03,479
owner of the Lion with the poor family, and he

1995
01:39:03,600 --> 01:39:07,560
relinquished it in order to buy the bills. So after

1996
01:39:07,720 --> 01:39:10,680
meeting Ralph and his wife and knowing that and getting

1997
01:39:10,720 --> 01:39:13,039
to appreciate that and how he had that, you know,

1998
01:39:13,640 --> 01:39:17,119
you know, it's it's you know, it's like your first kid,

1999
01:39:17,960 --> 01:39:19,920
well both your kids, but you know there's always a

2000
01:39:19,920 --> 01:39:22,359
little there was a little something special there. So I

2001
01:39:22,560 --> 01:39:26,359
love that the line you're doing what they're doing or Luke,

2002
01:39:26,439 --> 01:39:28,800
you know, Luke is the second one. He's the one

2003
01:39:28,880 --> 01:39:31,079
that you know, he's the one that I was able

2004
01:39:31,119 --> 01:39:33,680
to go after and get Lukey David.

2005
01:39:33,800 --> 01:39:34,000
Speaker 2: Yeah.

2006
01:39:34,319 --> 01:39:38,119
Speaker 14: So anyways, great time, guys, appreciate the phone call.

2007
01:39:38,199 --> 01:39:43,039
Speaker 2: All. Thanks for letting us, interrupt your knight, say hi

2008
01:39:43,119 --> 01:39:45,600
to mom as you check out Patron Saint.

2009
01:39:46,760 --> 01:39:49,880
Speaker 14: Yes. And the next time Kevin requests a song for me,

2010
01:39:50,000 --> 01:39:52,520
can it be a positive one, something that's fun?

2011
01:39:57,399 --> 01:40:03,039
Speaker 3: Says that's not possible. Cary Rails, thank.

2012
01:40:02,880 --> 01:40:05,239
Speaker 14: You, Greg, Hey, guys have fun.

2013
01:40:05,359 --> 01:40:09,000
Speaker 2: Thanks go Bills. There he goes Greg Connor. So that's

2014
01:40:09,079 --> 01:40:12,199
interesting with the chat, GPT song and everything. Yeah, I'm

2015
01:40:12,199 --> 01:40:12,560
pretty sure.

2016
01:40:13,359 --> 01:40:13,600
Speaker 13: Ai.

2017
01:40:14,399 --> 01:40:16,359
Speaker 2: Well, I don't think he understood the question when I

2018
01:40:16,399 --> 01:40:21,279
said the Bills sold ten percent of the team to investors.

2019
01:40:21,720 --> 01:40:23,680
And I keep saying he's the future owner of the

2020
01:40:23,720 --> 01:40:26,199
Buffalo Bills because he sponsors training camp and he does all.

2021
01:40:26,880 --> 01:40:30,920
Speaker 3: He's Tracy McGrady and Josie Altador. Yeah, I can't think

2022
01:40:30,920 --> 01:40:31,560
of the third guy.

2023
01:40:32,359 --> 01:40:35,560
Speaker 2: So this is sort of like Lebron buying into some

2024
01:40:35,840 --> 01:40:38,279
soccer team over in Britain. Doesn't he own Is he

2025
01:40:38,399 --> 01:40:41,079
part of an investor group that owns some of that? Yeah?

2026
01:40:41,680 --> 01:40:43,720
So that trade. Because I'm here, Tracy McGrady, I'm going

2027
01:40:43,760 --> 01:40:46,199
with to Tracy McGrady know about owning the Buffalo Bills,

2028
01:40:46,239 --> 01:40:47,239
but interesting.

2029
01:40:47,000 --> 01:40:50,399
Speaker 3: Great use of money, about putting the money in.

2030
01:40:50,640 --> 01:40:52,760
Speaker 2: That's all he needs to know about that is exactly

2031
01:40:52,920 --> 01:40:53,560
exactly true.

2032
01:40:53,640 --> 01:40:55,640
Speaker 3: Put your money in, put your feet up, and cash

2033
01:40:55,720 --> 01:40:56,279
those checks.

2034
01:40:57,000 --> 01:40:59,760
Speaker 2: Anything else you want to say, Cody about AI that

2035
01:40:59,840 --> 01:41:01,359
we missed on I.

2036
01:41:01,479 --> 01:41:03,439
Speaker 5: Mean, we could go on for hours, but you know,

2037
01:41:04,319 --> 01:41:06,520
come to our event and we can you know, cover

2038
01:41:06,640 --> 01:41:09,079
it much more in de Honestly, you know event bright

2039
01:41:09,319 --> 01:41:12,720
check it out December fourth, Rock AI Rock AI.

2040
01:41:12,920 --> 01:41:14,920
Speaker 2: So just put it in an ro O C aile

2041
01:41:14,960 --> 01:41:15,800
you're searching.

2042
01:41:15,600 --> 01:41:18,239
Speaker 5: You can do that or honestly, it's really easy to

2043
01:41:18,319 --> 01:41:21,039
find on event break if you just scroll through events.

2044
01:41:21,079 --> 01:41:24,880
But yeah, December events on December fourth, Tony D's.

2045
01:41:24,800 --> 01:41:29,640
Speaker 2: Okay, very good. And anything that we missed Brandon AI.

2046
01:41:30,039 --> 01:41:31,840
Speaker 4: We can talk for hours, but yeah, yeah, I think

2047
01:41:31,840 --> 01:41:32,279
we covered it.

2048
01:41:32,479 --> 01:41:35,560
Speaker 2: But everything from like finding efficiency to what your employees

2049
01:41:35,600 --> 01:41:39,199
are doing to basically even like employee theft, you can.

2050
01:41:39,319 --> 01:41:41,319
Speaker 5: Well you did just ask about the bills. You know,

2051
01:41:41,399 --> 01:41:47,079
you could potentially analyze plays and the entire history of

2052
01:41:47,119 --> 01:41:50,079
plays in the NFL and see what works, what doesn't work,

2053
01:41:50,279 --> 01:41:52,359
and what could be the most efficient way to run

2054
01:41:52,399 --> 01:41:55,279
a play with whatever design that's coming after probability of

2055
01:41:55,359 --> 01:41:57,840
a place basically probability.

2056
01:41:57,319 --> 01:41:59,399
Speaker 3: Statistic probability with the gambling exactly.

2057
01:42:00,199 --> 01:42:04,000
Speaker 8: AI loves data, data, analytics, information.

2058
01:42:04,199 --> 01:42:07,199
Speaker 5: That's what it thrives on. So you give it raw data.

2059
01:42:07,279 --> 01:42:09,720
You can basically feed it the entire history of the NFL.

2060
01:42:10,359 --> 01:42:13,279
Speaker 2: Would I make you uncomfortable if I asked, Like, you know,

2061
01:42:13,520 --> 01:42:15,680
parlays are a big thing, right, so you get four

2062
01:42:16,239 --> 01:42:20,159
parlays or whatever. Somebody's got to get so many yards passing, throwing,

2063
01:42:20,439 --> 01:42:24,439
winning touchdowns. Could you put in certain people and find

2064
01:42:24,479 --> 01:42:29,079
out statistically, probability wise, which has the most likely to

2065
01:42:29,119 --> 01:42:29,479
pay off.

2066
01:42:29,479 --> 01:42:31,760
Speaker 5: It'd be better with people with a long play history

2067
01:42:31,880 --> 01:42:34,720
rather than The more data the better, obviously, But yeah,

2068
01:42:34,760 --> 01:42:38,239
people use this for everything, stock the stock market, I mean,

2069
01:42:38,279 --> 01:42:43,319
you name it. It can find discrepancies and probabilities and statistics.

2070
01:42:43,439 --> 01:42:48,359
Speaker 4: There's a fully autonomous stock market AI that somebody built

2071
01:42:48,600 --> 01:42:55,079
that controlled all the trades and buys, sells, shorts, anything

2072
01:42:55,119 --> 01:42:57,159
like that based off of what they said, like they

2073
01:42:57,159 --> 01:42:59,159
were willing to risk on each trade, and it just

2074
01:42:59,239 --> 01:43:02,000
scanned the entre market, made trades. I think they ended

2075
01:43:02,079 --> 01:43:05,600
up making like thousand dollars.

2076
01:43:06,000 --> 01:43:06,800
Speaker 2: Really Yeah, they.

2077
01:43:07,159 --> 01:43:08,840
Speaker 4: Kept it pretty small because they didn't want to lose

2078
01:43:08,840 --> 01:43:12,359
a lot. But it just doesn't have emotion and it

2079
01:43:12,640 --> 01:43:15,960
goes by data and it succeeds. So I'm sure there's

2080
01:43:15,960 --> 01:43:17,520
people doing some degree than that.

2081
01:43:17,760 --> 01:43:20,279
Speaker 2: Could you guys build an app that would do that

2082
01:43:20,399 --> 01:43:24,960
for somebody? Yes, legalities of it, okay, all right, right, right,

2083
01:43:25,079 --> 01:43:29,279
but I'm just saying, okay, anything's possible. I don't want to.

2084
01:43:29,279 --> 01:43:30,239
I don't want to. Look at.

2085
01:43:32,239 --> 01:43:33,520
Speaker 3: Market is doing fine.

2086
01:43:34,840 --> 01:43:36,600
Speaker 5: That's and that's the big thing with you know, in

2087
01:43:36,680 --> 01:43:39,159
this industry, you know it's going to come down to creativity.

2088
01:43:39,199 --> 01:43:41,960
And honestly, we've been trying to build a few things,

2089
01:43:42,680 --> 01:43:46,279
and especially when you use AI and the patent scene

2090
01:43:46,359 --> 01:43:49,239
per se, it really comes down to it's kind of

2091
01:43:49,239 --> 01:43:51,560
a gray area, but it comes down to the creativity

2092
01:43:51,680 --> 01:43:55,800
of the input user. So where AI might give you

2093
01:43:55,880 --> 01:43:58,560
the answer to something, you know, it still took somebody

2094
01:43:58,720 --> 01:44:00,960
to get that out of it in a working fashion

2095
01:44:01,399 --> 01:44:02,439
better than everybody else.

2096
01:44:02,920 --> 01:44:04,920
Speaker 3: And it's gonna come down to you guys beat something

2097
01:44:05,119 --> 01:44:06,920
and the gonna step in and say.

2098
01:44:08,439 --> 01:44:10,640
Speaker 5: Yeah, I mean, you can't just copy and paste things.

2099
01:44:10,720 --> 01:44:14,399
But you know, if you show your prompt engineering to

2100
01:44:14,520 --> 01:44:17,479
get your answer, you know, in a lot of cases

2101
01:44:17,520 --> 01:44:20,439
it will be acceptable because you know, like we said,

2102
01:44:20,479 --> 01:44:21,760
it's all it's all guardrails.

2103
01:44:21,880 --> 01:44:22,920
Speaker 6: It's how you get your answer.

2104
01:44:23,239 --> 01:44:26,800
Speaker 2: Yeah. I like everything from fitness and health right right

2105
01:44:26,920 --> 01:44:29,199
up to stock market or anything. It's all right there

2106
01:44:29,439 --> 01:44:34,399
at your fingertips. The Barrier, Tantry, Kevin, the Barrier drawn

2107
01:44:35,680 --> 01:44:40,920
all right for Cody, for Brendan from Rock Ai, for

2108
01:44:41,159 --> 01:44:44,439
Kevin writing songs about Greg Connor's taking the bridge. If

2109
01:44:44,479 --> 01:44:47,279
the Bills lose the Super Bowl, I'm Bill Moran, will

2110
01:44:47,359 --> 01:44:56,760
see you tomorrow. Deal didn't know what to do.

2111
01:44:57,279 --> 01:45:01,239
Speaker 15: I'm turning a TV you this stalk and buy a

2112
01:45:01,359 --> 01:45:06,199
tag and about in n estate. Seems they were looking

2113
01:45:06,279 --> 01:45:14,039
for a kind of light often to see please see

2114
01:45:14,159 --> 01:45:16,520
I say Them's California bed and things that got in

2115
01:45:16,520 --> 01:45:18,560
the world season land up opportunity