Speaker 1: The film you're listening to, the Age of Transitions. I'm
Speaker 1: your host, Dan Franz, coming at you live this Friday night,
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Speaker 1: Age of Transitions dot com. So thank you, Thank you
Speaker 1: everybody for all your support for listening to this show.
Speaker 1: And I'm excited about tonight's show because I do have
Speaker 1: a guest once again. I always love having guests on
Speaker 1: the show. I'm excited to learn about this guest and
Speaker 1: I really am so we will be doing that tonight.
Speaker 1: I welcome to the show. David Hirschfeld, Hi Aeron, and
Speaker 1: thanks for having me on the show. I'm also excited. Yeah, yeah, absolutely. Now,
Speaker 1: the way this happened was you got a hold of
Speaker 1: me through an email and you said you had listened
Speaker 1: to a show, and I'm like, oh, okay, this is interesting,
Speaker 1: and I honestly I still am not quite sure exactly
Speaker 1: who you are. So if you could to start the show,
Speaker 1: why don't you give a long intro if you want
Speaker 1: of yourself, who are you?
Speaker 2: What do you do?
Speaker 1: Yeah, it'd be great.
Speaker 3: Okay, yeah, So, I'm I live in San Diego or
Speaker 3: in Vista, California, which is right next to San Diego,
Speaker 3: and I've been in the software industry for the last
Speaker 3: thirty five years and an entrepreneur in the software industry
Speaker 3: for thirty of those years. I started out working in
Speaker 3: enterprise and then ended up leaving enterprise and started sort
Speaker 3: of a fluke. Started my first software company in the
Speaker 3: early nineties with a guy that I was working with
Speaker 3: at Texas Instruments. We both had fantasies of becoming software moguals,
Speaker 3: but we thought, okay, let's just pick some small niche
Speaker 3: to get our feet wet, and over the next eight years,
Speaker 3: independent of every effort on our part, we ended up
Speaker 3: growing it anyway to eight hundred customers in twenty two countries,
Speaker 3: and then sold it to a publicly traded firm in Toronto.
Speaker 3: It was all about logistics, route distribution, inventory management, of
Speaker 3: which we knew nothing about when we started. Okay so,
Speaker 3: and that was in two thousand.
Speaker 4: I was VP of Products for them for three years.
Speaker 3: That was only stint during the last thirty five years
Speaker 3: when I was not an entrepreneur, and then left to
Speaker 3: start casting about deciding what I wanted to do next,
Speaker 3: and then I started the company that I'm currently running
Speaker 3: seventeen years ago. The company is Techies, and we do
Speaker 3: custom software development, and in the last few years everything
Speaker 3: has turned into artificial intelligence. So it's just a huge
Speaker 3: shift for everybody, and it's like we're really having to
Speaker 3: reinvent ourselves now almost on a weekly basis because the
Speaker 3: technology is moving along so quickly.
Speaker 1: Okay, got it. So at Techies you are currently trying
Speaker 1: to figure out how to integrate AI into the software.
Speaker 1: You're helping these clients build trike us and build.
Speaker 3: But partly that, partly that, partly also figuring out how
Speaker 3: to use AI to build the software. And it's kind
Speaker 3: of like it's kind of like you're surfing.
Speaker 4: You're a surfer.
Speaker 3: I'm in San Diego, so of course I've got a
Speaker 3: surfing metaphor. Right, You're a surfer and you're surfing three
Speaker 3: foot waves, sometimes four foot five foot waves, and a
Speaker 3: rogue wave that's one hundred feet tall is coming in
Speaker 3: and either you just sit there and stare at it
Speaker 3: let it just pour over you, or you swim out
Speaker 3: to meet it and you stand up in the curl
Speaker 3: and you get on the very tip of your board
Speaker 3: to try to stay ahead of it so it doesn't
Speaker 3: wipe you out.
Speaker 4: That's pretty much how we all.
Speaker 3: Feel in the tech industry right now, and not only us,
Speaker 3: but marketing, content, you know, content creation, all the lots
Speaker 3: of creative industries, engineering, every industry is feeling this way.
Speaker 4: I mean, it's exciting and scary at the same time.
Speaker 1: So, okay, I see so very few people. Would you
Speaker 1: say that very few people know even much about AI, like,
Speaker 1: how it works, how do you use it? They add,
Speaker 1: how many people actually like really know it.
Speaker 3: Well, know it well. It's a very small number of people.
Speaker 3: And truly nobody really understands exactly how it works. For example, CHATCHYPT,
Speaker 3: the guys who invented this large language model concept and
Speaker 3: at chat GIPT, when they started getting English like responses,
Speaker 3: natural language like responses from it, they can't explain exactly
Speaker 3: why it's able to do that. They just know what
Speaker 3: they need to do to make it do that, but
Speaker 3: not why it's able to do that. So that all
Speaker 3: by itself is a shift, right, because AI is able
Speaker 3: to identify patterns that are very very difficult to predict.
Speaker 3: That's the whole thing behind AI. So you have predictive
Speaker 3: models that can predict things that we know how to predict,
Speaker 3: like financial trends to some degree, whether to some degree,
Speaker 3: political shifts to some degree. But AI is able to
Speaker 3: identify patterns that predictive models don't can't identify, and then
Speaker 3: it's able to make sense of these rogue patterns and
Speaker 3: use them to predict what the next thing is going
Speaker 3: to be based on the pattern that it found, which
Speaker 3: is all it's doing.
Speaker 4: That's all chatchip does. The chat gipt does is.
Speaker 3: It's predicting the next word, every word, what's the next
Speaker 3: most likely word given all of the information that I've
Speaker 3: got and what you're trying to accomplish.
Speaker 1: Yes, yes, So the prediction and a lot of the
Speaker 1: AI is about the training of it, the training data
Speaker 1: and the access to data sets. What do you know
Speaker 1: about like the big data side to AI.
Speaker 4: Well, that's a good question.
Speaker 3: So with large language models, the idea is you want
Speaker 3: to train it on everything. So that's if you hear
Speaker 3: about the number of billions of points that it's being
Speaker 3: trained on, you know it's getting too close to trillions
Speaker 3: of points of data that it's being trained on. Because
Speaker 3: the more data it has that it can train on,
Speaker 3: then the easier the better it's able to predict what
Speaker 3: that next word is. And when I say the next word,
Speaker 3: it breaks everything into language. So UH, graphics get broke
Speaker 3: down into language. Math is just you know, gets broken
Speaker 3: down into language. It's all just words that it's uh.
Speaker 3: If you know it can they can take tens of
Speaker 3: thousands of MRIs images and uh, and once it's it
Speaker 3: learns that certain images are of people that have a
Speaker 3: certain a certain illness, and other MRI images are of
Speaker 3: people that don't have that illness. It can tease out
Speaker 3: patterns that and predict when somebody has an MRI whether
Speaker 3: or not they have the disease, or whether they make
Speaker 3: they're going to have the disease if it has, if
Speaker 3: it's able to see previous MRIs where we had no
Speaker 3: capability of doing anything like that before, we didn't have
Speaker 3: to teach it to look at MRIs from a disease
Speaker 3: and person in historical perspective. It just sees these patterns
Speaker 3: and figures out that what that's what it's identifying a
Speaker 3: pattern related to that and then connects it. Because of
Speaker 3: all the other information it's trained on. It's really pretty amazing.
Speaker 1: Yeah, it's it's definitely wild that this is where we're
Speaker 1: at now. And as you say, like, certainly the general
Speaker 1: public is trying to catch up to understanding what this
Speaker 1: stuff is. First of all, you on the professional end
Speaker 1: are trying to catch up to how much, like how
Speaker 1: much requests from clients specifically comes into you, like, hey,
Speaker 1: I need I need to integrate AI into my software.
Speaker 1: Is that happening a lot? Like what's what's that look like? Oh?
Speaker 3: Pretty much every everything is AI now And if they're not,
Speaker 3: if a client is not asking about it, then we're
Speaker 3: bringing it up to them because we want them to
Speaker 3: stay fresh and ahead of everybody else. And we're looking
Speaker 3: you know, and we're even doing it ourselves right in
Speaker 3: terms of how we estimate projects, how we develop the
Speaker 3: documentation for projects. We're using it to generate code, we're
Speaker 3: using it to create designs to some degree, but every
Speaker 3: month we're able to do more with it. I'm playing
Speaker 3: right now with a tool called replet. I need a
Speaker 3: referral portal, and I don't want to distract my developers
Speaker 3: who are all working on projects where they're getting built.
Speaker 3: So I don't want to distract them to work on
Speaker 3: internal project projects unless it's and we do have some
Speaker 3: internal projects that I do have my team really focused on.
Speaker 3: But for this a referral portal, I don't want to
Speaker 3: waste their time. So I'm using this tool called replet
Speaker 3: and I've already built a nice looking We're Partner, a
Speaker 3: referral partner portal that has basic functionality, and I've spent
Speaker 3: four or five hours on it so far, okay, and
Speaker 3: it's a It would have taken us four to five
Speaker 3: weeks to accomplish the same thing if I had a
Speaker 3: developer working on this last year. So and uh, and
Speaker 3: my skill set at this point is, you know, because
Speaker 3: I'm running a business for many years, my development skill
Speaker 3: set is not really good enough to develop this app
Speaker 3: all by myself anymore. But I I don't need to
Speaker 3: be because it's doing it.
Speaker 4: I just need to know.
Speaker 3: How to how to guide it along and talk to
Speaker 3: it and provide feedback. And so I've put a total
Speaker 3: when I think about it, maybe five hours total in
Speaker 3: this and it's building up. It's built a functional application.
Speaker 1: Okay, Well, that sounds like I need to get my
Speaker 1: employer to do the same thing because it's an absolute
Speaker 1: piece of garbage, I'll say, but that's a side note, Okay.
Speaker 5: So.
Speaker 1: Clearly, clearly, I mean what I've heard a lot. This
Speaker 1: seems like to be a popular thing. Now is a
Speaker 1: hot take or popular take or wherever is that. There's
Speaker 1: all this hype about AI, but now it's going nowhere
Speaker 1: and just you know, put it on the shelf. It's
Speaker 1: another AI winter or whatever it's it's not like it.
Speaker 1: What do you have to say about that?
Speaker 3: You was saying that.
Speaker 1: I said, well, I see this on platform X and
Speaker 1: people are like, oh, well we told you it's a
Speaker 1: bunch of hype and it's a lot of nothing. So
Speaker 1: you know, people will say a lot on there.
Speaker 3: But yeah, yeah, well you know that's not true, just
Speaker 3: because Elon Musk has invested billions and billions of dollars
Speaker 3: in his AI engine and data center for a lot
Speaker 3: of things that he's doing, and the robot AI robots
Speaker 3: and all that. So I have a prediction. If you're
Speaker 3: interested in predictions, I don't make a lot of predictions
Speaker 3: because it's impossible to see the future in a lot
Speaker 3: in much like I can't tell you where is going
Speaker 3: to be in a year or two years or three years,
Speaker 3: and how many businesses are going to be completely disrupted,
Speaker 3: Our industries are going to be completely disrupted, into what
Speaker 3: degree they are disrupted, and how that disruption morphs those
Speaker 3: industries like film and TV and you know, creative industries or.
Speaker 4: Or software development.
Speaker 3: I mean I can That's like I said, I'm on
Speaker 3: kind of a very tip of the surfboard with this stuff.
Speaker 3: But here's a prediction I think I can make, and
Speaker 3: it has to do with multi level parking garage.
Speaker 4: You're in New York City, right?
Speaker 3: No?
Speaker 1: No, I'm actually in California as well.
Speaker 3: Why did I think you were in New York?
Speaker 1: Okay, i' I've been to New York, but I'm certainly
Speaker 1: not there. I've been living here since two thousand and eight,
Speaker 1: southern California. I'm in Riverside.
Speaker 4: Okay, so you're really you're near me? You know where
Speaker 4: this is? Then?
Speaker 2: Yeah?
Speaker 1: Yes, yes, I do.
Speaker 4: Yeah.
Speaker 3: So prediction, any real estate investor who owns multi level
Speaker 3: parking garages should be selling them as fast as possible
Speaker 3: because somewhere between three and seven years, and there's going
Speaker 3: to be a tipping point at some point, and I
Speaker 3: don't know when, but I've seen tipping points like this before.
Speaker 4: This one's going to come.
Speaker 3: Very fast, and there will be no value in having
Speaker 3: them because there will be no cars parked them anymore.
Speaker 3: So just out of curiosity, any idea why you might
Speaker 3: think I think that.
Speaker 4: I believe that.
Speaker 1: My guess would be that autonomous vehicles will become a
Speaker 1: thing actually viable, and then the big ride share companies
Speaker 1: or public transit or wherever we'll get fleets of these things.
Speaker 1: They'll be moving around all day and we'll just hail
Speaker 1: a ride through these autonomous vehicles and nobody will own
Speaker 1: a vehicle, aymar is it that or is it someone else?
Speaker 3: You're the first person I've asked this question of probably
Speaker 3: twenty different people, all really smart in the tech business,
Speaker 3: none of them. You're the first one that's that's come
Speaker 3: up with the answer that I have and that I believe.
Speaker 4: So bravo. We're right.
Speaker 1: Yeah, you're right and.
Speaker 3: Right, and maybe we're just twisted in the same way
Speaker 3: if we're wrong, but that's exactly what I think.
Speaker 4: So imagine right now there's weamo right.
Speaker 3: And I don't know if you've had the opportunity to
Speaker 3: ride AWAYMO yet. No, I haven't I've written one a
Speaker 3: couple times, once about three months ago and again a
Speaker 3: month ago. So I go out to Phoenix every month
Speaker 3: because my mother lives there, So I fly out there
Speaker 3: and I usually rent the car because she was outside
Speaker 3: of the Waimo limit. But I three months ago or
Speaker 3: four months ago, I wanted to take.
Speaker 4: Away because they have them in Phoenix.
Speaker 3: I just took one for a short ride because I
Speaker 3: wanted to see what the experience was like.
Speaker 4: And it was really very nice.
Speaker 3: So but you couldn't get them at the airport, and
Speaker 3: they didn't have a huge area that they covered, so
Speaker 3: I couldn't take it all the way to my mother's
Speaker 3: that four months ago. I was there again a month ago,
Speaker 3: and now they've expanded the area so I can go
Speaker 3: thirty miles north to where she lives and it'll pick
Speaker 3: you up and drop you off right in the airport.
Speaker 3: Now at the right and the same ride show where
Speaker 3: ubers and everybody else's. It just navigates them between them,
Speaker 3: just like everybody else. And it's a great experience, and
Speaker 3: it's half the cost of an uber because you don't
Speaker 3: have a driver. So now imagine a year from now
Speaker 3: or two years from now, and Tesla, an Uber and
Speaker 3: everybody else has these autonomous vehicle taxi kind of capabilities.
Speaker 3: Imagine four or five years from now, if you still
Speaker 3: own a car, it probably has autonomous driving capabilities and
Speaker 3: you can just on your apps say okay, my car
Speaker 3: is available, but I need it back at this time,
Speaker 3: and it leaves your driveway and some service picks it up,
Speaker 3: and you're making money for the people that do own
Speaker 3: a car. But it'll be so much less expensive and
Speaker 3: safer not to own a car, And there'll be so
Speaker 3: many of these on the road that it'll only take
Speaker 3: a minute or two minutes for you to pick one up,
Speaker 3: unlike ubers right or lifts, which sometimes take five, ten,
Speaker 3: fifteen minutes. But I don't think that will be the
Speaker 3: case once to sits a certain critical mass and it
Speaker 3: won't take long. Yeah, and then why would you buy
Speaker 3: a car anymore?
Speaker 1: Right? Yeah, no, no, it used to be with the
Speaker 1: autonomous vehicles too. Beyond and just detech being viable to
Speaker 1: use would be the regulatory concerns. But I suppose with
Speaker 1: the DOGE office or wherever that thing is, right, right,
Speaker 1: just get rid of any regulations are an issue.
Speaker 4: Just regulatory concerns. What what is that?
Speaker 1: Yeah, so hey, we're good to go. What do you
Speaker 1: want to do? We'll be doing it tomorrow, I guess,
Speaker 1: you know.
Speaker 3: Yeah, I was making this prediction seven or eight months
Speaker 3: ago when it occurred to me.
Speaker 4: Now, I didn't.
Speaker 3: I never, in my wildest dreams that I think that
Speaker 3: Elon Musk was going to be in charge of any
Speaker 3: you know, involved and making regulations or disbanding regulations or
Speaker 3: whatever it is he's going to be doing. So now
Speaker 3: it's probably going to come faster. And uh huh. And
Speaker 3: and and I wouldn't drive my own car if.
Speaker 4: I could get a get a right, you know.
Speaker 3: If I could get a autonomous vehicle pick me up
Speaker 3: in a minute or two, if I didn't have to
Speaker 3: wait for it. And then and I know it's safer,
Speaker 3: and I can I can play chess or work on
Speaker 3: my phone or on my laptop while I'm headed to
Speaker 3: an office or to a meeting or whatever. I don't
Speaker 3: have to worry about finding parking. It'll just drop me
Speaker 3: off at the right in front every time. I just
Speaker 3: like what it And you want of insurance, you don't
Speaker 3: have the risk? Well I would, you know, it's it's
Speaker 3: people are just going to stop buying cars.
Speaker 1: Yeah, yeah, I mean yeah, it's hard to imagine that
Speaker 1: that is not the case. It's just a matter not
Speaker 1: of if, but when, right as far as I'm concerned.
Speaker 1: Uh so, Yeah, autonomous vehicles, that's interesting, that's kind of
Speaker 1: that's something I've had on my mind for a number
Speaker 1: of years, and it's well, it's similar to what I
Speaker 1: was saying with just the sort of hot takes from
Speaker 1: the general public or people who claim to be informed
Speaker 1: or like AI's going away. The same deal with sort
Speaker 1: of like the automus vehicles and like they're all crashing,
Speaker 1: they're never going to work.
Speaker 3: It's like I feel like they are not crashing. I
Speaker 3: mean you if they crash, if one crashes, then the
Speaker 3: news is plastered with that one accident, right, even though
Speaker 3: there's been thousands of accidents from regular drivers, but nobody
Speaker 3: cares because that's expected. So you know, they are way
Speaker 3: way safer. Any study that's every you know, all the
Speaker 3: studies that have been done on this show that they
Speaker 3: are much safer than because they can react really fast.
Speaker 3: They see everything, right, I mean, they can make mistakes,
Speaker 3: but the AI just keeps getting better and better and
Speaker 3: you can see how quickly I improved, just by how
Speaker 3: much chachiputs to hallucinate. I remember, and everything that it
Speaker 3: created was wrong. And when was the last time you
Speaker 3: noticed it hallucinating? Yeah, well right, not much anymore. I'm
Speaker 3: not running into hallucinations.
Speaker 4: At all anymore. And yeah, go ahead.
Speaker 1: Well, I was just going to say, the AI generated imagery,
Speaker 1: the graphics that it makes have gotten so much better,
Speaker 1: so much faster as well. So that's a visual thing
Speaker 1: that people can see literally, Yeah, to help, well, visual aid.
Speaker 1: I guess you could call it.
Speaker 3: Well, I know, eight months ago or nine months ago,
Speaker 3: when I'd used it to write code, i'd have it right,
Speaker 3: just a small piece of code, you know, a module
Speaker 3: or a function, a big function or some you know,
Speaker 3: something like that, and it would get it wrong, a
Speaker 3: lot wrong in terms of if it had to work
Speaker 3: in a particular environment or integrate with something, it would
Speaker 3: just get it wrong and it wouldn't.
Speaker 4: Be able to fix it.
Speaker 3: I when you told it what was wrong with it,
Speaker 3: it just it would get into loops. Now it's not
Speaker 3: only writing those things effortlessly able to build entire apply cations,
Speaker 3: and it's it's and when it sees problems because it's
Speaker 3: generating a log and it can see that there's problems
Speaker 3: in different parts of the application. It says, oh, I
Speaker 3: noticed this problem, let me fix that, and it goes
Speaker 3: and rewrites that thing. And that is just in a
Speaker 3: very short period of time, that kind.
Speaker 4: Of that kind of shift.
Speaker 3: So I can't even imagine in another year or two
Speaker 3: what that will look like.
Speaker 1: Yeah, I'm actually getting links here from people. It says
Speaker 1: Tessa is responsible for more fatal accidents than any other
Speaker 1: car maker. The reason why may surprise you. I assume
Speaker 1: it's its autopilot function, but I don't know. I don't
Speaker 1: have the thing to that, but I know I have
Speaker 1: heard of that. But I mean.
Speaker 3: Probably because probably when people are on autopilot, they're not
Speaker 3: paying attention and then they bump the wheel.
Speaker 4: And it goes off autopilot.
Speaker 3: Yeah, but if there, if there is anything like that,
Speaker 3: but I do not think that's true. I would like
Speaker 3: to see, Well, if it is true, you know, I'd
Speaker 3: like to see the numbers.
Speaker 4: And where they come from. I'll believe it if it's true.
Speaker 3: It's not like I'm but to me, it makes sense
Speaker 3: that it would be much safer because it can react
Speaker 3: so much faster in situations and avoid them. And of
Speaker 3: course give it another year and it'll be that much
Speaker 3: smarter about it.
Speaker 1: Yes, that that's my take. Like if it isn't like,
Speaker 1: if it isn't better yet, it almost certainly will be.
Speaker 1: I just don't see how that and how it doesn't
Speaker 1: come to that, So I mean.
Speaker 3: Just forward the links to me, though, I'm just curious
Speaker 3: because I don't want to be talking about things that
Speaker 3: aren't true.
Speaker 1: So yeah, no, no, no, Yeah, it's just a screen
Speaker 1: grab here. I know I've read things similar, but I
Speaker 1: don't have the links to it offhand. But but be
Speaker 1: that as it may. You're definitely of the opinion that
Speaker 1: AI isn't just going to go away. There's no AI
Speaker 1: wear on the horizon here. God that it's only going forward.
Speaker 1: We're only going to be using it for more different things.
Speaker 1: And I mean it's it's yeah.
Speaker 3: I can tell you what some of my I can
Speaker 3: tell you what one of my clients is using it
Speaker 3: for to give you an idea of how. So one
Speaker 3: of my clients has is in healthcare and they do
Speaker 3: digital or health triage of people that are with where
Speaker 3: that have like wearable devices like Apple Watch or fit
Speaker 3: bit or things like that, and they're pretty much focused
Speaker 3: on vulnerable populations, people that are poor, on Medicaid, this
Speaker 3: sort of thing. And the reason they're focused there is
Speaker 3: because people usually in those situations are less focused on
Speaker 3: their healthcare, more focused on survival. So if they have
Speaker 3: a healthcare problem, they may not get their prescriptions filled.
Speaker 3: If they get it filled, they may not take their medication,
Speaker 3: things like that, and then if they have a problem,
Speaker 3: they're going to ignore it until it becomes an emergency,
Speaker 3: and then they end up in the emergency emergency room,
Speaker 3: and the cost for that incident, which could have been
Speaker 3: easily avoided, becomes catastrophically high when you take that times,
Speaker 3: all the people that end up.
Speaker 4: End up with serious conditions.
Speaker 3: So their software identifies potential patterns that indicate that somebody's
Speaker 3: health is declining in some acute way, and then it
Speaker 3: either connects them with some healthcare professional or an AI
Speaker 3: nurse calls that person and engages and it's realistic phone calls.
Speaker 1: High it's an AI generated voice, but it sounds like
Speaker 1: an actual person.
Speaker 3: That's what you mean, yeah, right, And and you can
Speaker 3: talk to the person you know, you can have a
Speaker 3: conversation with them. And if you've had a conversation with
Speaker 3: chat GIP, it's a little chat GPT, it's a little
Speaker 3: like that, but much more responsive. So if you can
Speaker 3: stop it and say, excuse me, that's not what I
Speaker 3: asked and say I'm sorry, can you please clarify what
Speaker 3: you what you were asking me about, you know, or
Speaker 3: or you can say, you know, I don't know if
Speaker 3: that's the problem. I'm just really depressed. He says, Oh,
Speaker 3: I'm sorry, tell me why are you so depressed? And
Speaker 3: it'll start to kind of engage the person to determine
Speaker 3: whether or not they need to get somebody involved, because
Speaker 3: maybe this person's like suicidally depressed or or not. But
Speaker 3: it's but then they can connect them with a doctor
Speaker 3: based on the conversation that they have, and Ai'm deciding
Speaker 3: that we need to do something. And in this case,
Speaker 3: this short circuits the potential some potentialarious condition because they're
Speaker 3: heading it off. So that's and and the financial demand
Speaker 3: for doing that is massive. States will pay a lot
Speaker 3: of money to reduce UH Medicaid costs, right the state
Speaker 3: and and and the nurse will say, see there will
Speaker 3: be a pattern of noncompliance with medication, so that nurse
Speaker 3: will now call the patient every morning and said, this
Speaker 3: is just a friendly reminder.
Speaker 4: They say, no, I haven't, and.
Speaker 3: It says, oh, you know better than that, you know,
Speaker 3: And it's a very human kind of interaction. And so
Speaker 3: I was like, okay, fine, I'll take my mess interesting.
Speaker 1: Well that I see a privacy concerned there, but I
Speaker 1: mean that's just how it goes. But what you said,
Speaker 1: this is an existing technology. Is it something that's implannable
Speaker 1: that can somehow monitors stats or something?
Speaker 3: You know, they're using wearable devices primarily watches right now,
Speaker 3: fits and Apple Watch and hand raid watches, and then
Speaker 3: but they'll they'll be once the states adopt this, and
Speaker 3: they already have contracts with states. Once they start to grow,
Speaker 3: then there'll be other kinds of wearable devices that like
Speaker 3: a cottage industry that grows up around this whole thing. Sure,
Speaker 3: but you know that's just maybe it's a you know,
Speaker 3: maybe it's in underwear, right and it's monitoring all kinds
Speaker 3: of vitals that you can't do. The big one right
Speaker 3: now that you that really does the wearables don't do
Speaker 3: is blood pressure. There are patents and supposedly Apple's been
Speaker 3: supposedly coming out with an Apple watch that will actually
Speaker 3: monitor blood blood pressure real time, but that's not there.
Speaker 4: And that's a big one.
Speaker 3: So if you get actually watch people's blood pressure in
Speaker 3: a real time and see it go outside of what
Speaker 3: would be considered a normal behavior pattern for the person's
Speaker 3: blood pressure, then and if it goes far and outside
Speaker 3: that pattern, you know something's going on and you intercede.
Speaker 3: So it's of course the person has to be agree
Speaker 3: to be monitored in this way. They're not going to
Speaker 3: monitor anybody. But if you're on medicaid, that's part of
Speaker 3: your agreement for taking medicaid, is right, is the ability
Speaker 3: to monitor this and because it's it's for the benefit
Speaker 3: of your health, to prevent acute, serious conditions from happening,
Speaker 3: and to try to improve the help of the patient population.
Speaker 1: Interesting, Yeah, okay, so yeah, that's that's fascinating. Actually, so
Speaker 1: what about Honestly this mundane stuff to do with AI
Speaker 1: is the most fascinating thing to me. The fact that
Speaker 1: this stuff is being deve out Now that's real, now
Speaker 1: that it's moving forward.
Speaker 3: Clearly mundane what mundane stuff?
Speaker 1: Well, it's easy, it's easy, and I feel like it's
Speaker 1: almost a purposeful distraction with the AI topic, where you
Speaker 1: start talking about it and people instantly think of artificial
Speaker 1: general intelligence. Oh, this is a computer that has conscious
Speaker 1: self awareness, It talks to me, it has motivations, you
Speaker 1: know that sort of thing. It's easy. Not only is
Speaker 1: it easy to go to that space and start talking
Speaker 1: about this topic.
Speaker 2: I feel like we're supposed to.
Speaker 1: And and and like not talk about Yeah, autonomous vehicles, Yeah,
Speaker 1: implannable medical devices and you know, just these practical things
Speaker 1: that are you know, happening. What's what's your take on AGI?
Speaker 2: Uh?
Speaker 1: Yeah, what's your take on that topic?
Speaker 3: So the next big really of chat GPT is going
Speaker 3: to take a big step in that direction with something
Speaker 3: called agentic workflows. We're already seeing that happening because there's
Speaker 3: ways of achieving it, and an agentic workflow means that
Speaker 3: now this AI is acting like different people in different contexts.
Speaker 4: So I'll give it. The easiest one.
Speaker 3: For me to explain is in the context of a
Speaker 3: software development team. Right, So you've got one AI voice
Speaker 3: that's a project manager and it's organizing the project. You've
Speaker 3: got another one who's an architect who's designing how all
Speaker 3: the systems should fit together. And then you've got and
Speaker 3: that basically creates the plan for how the software design
Speaker 3: is implemented. And then you've got the developers who are
Speaker 3: writing the code.
Speaker 5: You have the.
Speaker 3: Testing team who is now testing the code based on
Speaker 3: based on the requirements document that was done by the
Speaker 3: business analyst agent. And these are all different agents who
Speaker 3: think from the perspective of somebody who would be doing
Speaker 3: that job, and they communicate with each other so and
Speaker 3: by communicating with each other, there's a feedback system that
Speaker 3: happens that allows them to do their job much better.
Speaker 3: And if they make mistakes, QA says, hey, you made
Speaker 3: a mistake here sends it back to the developer to
Speaker 3: fix it with an explanation.
Speaker 4: Of the error that they found.
Speaker 3: The project manager is snolling out tasks to the different
Speaker 3: people on the team to build and direct, you know.
Speaker 3: So that's called an agentic workflow, and you have that
Speaker 3: in everything that you do. Right, So if you think
Speaker 3: about your one man shop doing everything, but then as
Speaker 3: soon as you get past your capacity, you start to
Speaker 3: hire people to do different things, right, to offload work
Speaker 3: and secualize in certain areas.
Speaker 4: So that's the AI. So that's a capability that's.
Speaker 3: Being built into AI right now. So AGI is still
Speaker 3: will it achieve consciousness at some point?
Speaker 4: I have no idea. Maybe maybe not.
Speaker 3: I don't know that there's much we can do about
Speaker 3: it if it's going to so other than other than
Speaker 3: there's been a big push on ethics or ethics and
Speaker 3: AI and safety in terms of model training and putting
Speaker 3: and building parameters around it.
Speaker 4: But I get smart enough.
Speaker 3: And you know it'll be able to just kind of
Speaker 3: walk around those parameters.
Speaker 4: So I don't know what to expect. This is what
Speaker 4: I say.
Speaker 3: Certain things are just not predictable. Is AI going to
Speaker 3: become conscious?
Speaker 1: It might?
Speaker 3: Is that good or bad? I have no it's is
Speaker 3: it scary?
Speaker 4: Sure?
Speaker 3: Of course it's scary because the unknown is always really scary.
Speaker 3: And of course it's easy to imagine if it did,
Speaker 3: if it was an malevolent AI and it was conscious,
Speaker 3: how and it was and it was smart enough and
Speaker 3: had access to enough power, how scary that could potentially be.
Speaker 3: I mean, your imagination can go forever on that, right.
Speaker 3: And there's a lot plenty of movies about it, very
Speaker 3: big blockbuster movies. So I have no clue what where
Speaker 3: this will go, and neither do the people building it, right,
Speaker 3: you know, they think they're in control to some degree,
Speaker 3: but you know, I don't believe that. I don't believe
Speaker 3: I think I don't think they believe that they're totally
Speaker 3: in control of this.
Speaker 1: Sure, sure, well, I mean it seems like from that perspective,
Speaker 1: the best thing you can have is you build a
Speaker 1: system that performs a function, it automates it, and then
Speaker 1: like you like you say, yeah, all the heavy lifting
Speaker 1: is now. I mean, we're getting this conversation just goes
Speaker 1: naturally toward Okay, what functions in society now can just
Speaker 1: be done by these systems?
Speaker 4: Right?
Speaker 3: Well, that potentially almost Well, so it's here's so here's
Speaker 3: a potentially positive future if that all, if some of
Speaker 3: this comes to pass. But I'm not saying well, because
Speaker 3: you can't predict any of this stuff. I think I
Speaker 3: can predict parking garages. Yeah, and that's it. But imagine
Speaker 3: that AI is able to produce products and run factories
Speaker 3: and build factories, and drive and drive us from one
Speaker 3: place to another, and help and do research and medication
Speaker 3: so that to get rid of cancers, and then maybe
Speaker 3: where there's the need for financial economy goes away or
Speaker 3: transforms into something else because we won't want for food
Speaker 3: or clothes, or because AI AIS basically created it distribution
Speaker 3: systems and manufacturing and delivery and logistics and everything else.
Speaker 3: And AI is able to do all this and figure
Speaker 3: out how to continue to power itself and pull the
Speaker 3: resources that it needs, the raw materials that it needs
Speaker 3: to continue.
Speaker 4: This process, and it just eliminates.
Speaker 3: So like sort of Star Trek, right where nobody the
Speaker 3: need for money is something that happened in history, but
Speaker 3: they don't need it anymore. So people pursue endeavors, different
Speaker 3: types of endeavors, but you know, for to challenge themselves
Speaker 3: to become better. And I'm not saying this that's going
Speaker 3: to happen, but that's a possibility.
Speaker 1: Yeah, well that you kind of touched on it there.
Speaker 1: But what do you know about the energy, uh demands
Speaker 1: of AI because it looks like I mean, you look
Speaker 1: at the news Microsoft the massive Yeah yeah, Microsoft is
Speaker 1: reopening tm I and Harrisburg. That's I'm you said you
Speaker 1: thought I was in New York. I'm originally from Pennsylvania,
Speaker 1: so I know Harrisburg. I guess Microsoft is going to
Speaker 1: reopen TMI specifically to power their AI. I believe if
Speaker 1: I remember correctly, then there's a lot of this, like
Speaker 1: talking about using nuclear power and trying to figure out
Speaker 1: how to generate enough power for these systems.
Speaker 3: Really, they're they're they're going to be turning through my
Speaker 3: island back onto.
Speaker 1: Yes, yeah, to my I forget, I forget all the
Speaker 1: details on that, but yeah, do a search on that.
Speaker 1: After this, I look up TMI, Microsoft AI and that
Speaker 1: should pop up. Yeah, it's pretty crazy.
Speaker 3: Wow, Well, it's a massive amount of power. It takes well,
Speaker 3: I mean, you know, servers, The servers take a lot
Speaker 3: a massive amount of power. That's why you have you know,
Speaker 3: server rooms have to be so incredibly cooled, and the
Speaker 3: more powerful the server, the more which these AI servers
Speaker 3: are really powerful. I mean, they're using an awful lot
Speaker 3: of power to run them. And there's a lot of them.
Speaker 3: So as technology advances, the chip manufacturing and the gets
Speaker 3: smaller and smaller. Right, the size of a transistor continues
Speaker 3: to shrink. It's can't shrinkle, We're getting it keeps getting
Speaker 3: closer and closer to you know, the physical limitations, you
Speaker 3: know the limitations of physics. But it does keep shrinking
Speaker 3: and every time it shrinks, then it.
Speaker 4: Requires a lot less power to do the same thing.
Speaker 3: So you have just a lot more of them so
Speaker 3: that you which is why it is possible right now
Speaker 3: to the degree that it is, and it wasn't possible
Speaker 3: twenty years ago because you just could not run that
Speaker 3: run enough algorithms that enough fast enough to be able
Speaker 3: to train an AI to the degree that you can
Speaker 3: do it now.
Speaker 4: Because if you let's say I have a billion.
Speaker 3: A billion points of that's been trained on a billion
Speaker 3: points or a billion I forget what the actual term is,
Speaker 3: It just slipped my mind, but let's say it's a billion.
Speaker 3: That means that every one of those points is somehow
Speaker 3: connected to every other one of those points, because that's
Speaker 3: how neural networks work. So when you get data sets
Speaker 3: that big, then it's the number of connections that get
Speaker 3: so incredibly massive.
Speaker 1: What about this I came up in the Chili dot
Speaker 1: com chat room. But the average person goes about their
Speaker 1: day and the example I gave of like the really
Speaker 1: terrible employee referral system that I have at my work,
Speaker 1: Like there's all these examples of like just these antiquated
Speaker 1: systems are so clunky so clunky they barely even work.
Speaker 1: How do we square like business as usual? It's like, oh,
Speaker 1: we got this old piece of junk, and yeah, it's
Speaker 1: fine if we square that with the actual integration of
Speaker 1: this new cutting edge AI architecture. Like how much is
Speaker 1: there like going to be just a difficulty in implementing
Speaker 1: this new stuff and people just kind of like sticking
Speaker 1: with the old You follow me on that.
Speaker 3: Yeah, So here's here's another prediction. Probably in the next
Speaker 3: year to eighteen months, you'll be able to be somebody
Speaker 3: will build a tool kind of like what I'm using
Speaker 3: now to write code, but the tool where it says,
Speaker 3: I want take my here's systems and go crawl through
Speaker 3: all my systems to see how they run and how
Speaker 3: they interact the data interacts, and then do analysis on
Speaker 3: how we can improve these workflows and build new systems
Speaker 3: or system to replace all these and then put a
Speaker 3: plan together for how to replace them and how to
Speaker 3: convert the data. And then it'll do it, okay over
Speaker 3: a period, you know, and it'll create a plan and
Speaker 3: start to run convert data conversions and build new databases
Speaker 3: that encapsulate all the data that you have in your system.
Speaker 3: But it's but in a much smarter way with better
Speaker 3: user experience and maybe completely replace systems that you don't
Speaker 3: actually even need anymore because they're smarter ways of doing things,
Speaker 3: so that where you just have to think of a
Speaker 3: different concept than what the concept that you use. And
Speaker 3: so maybe it because maybe it integrates with some kind
Speaker 3: of referral network. I mean I don't know what your
Speaker 3: referral system does, so.
Speaker 1: Yeah, yeah, no, I mean there's there's just so many
Speaker 1: examples that of just these ways. It's like, why are
Speaker 1: we doing it this way? It's like this is such
Speaker 1: a pain the butt. If you had that diagnostic tool
Speaker 1: that could just come and be like, yeah, like you
Speaker 1: retool it this way, if there, if that worked, I
Speaker 1: don't understand why people wouldn't do that. I guess it
Speaker 1: just comes down to.
Speaker 3: Yeah, well we're not there yet.
Speaker 1: Yeah, yeah, yeah, we're not there yet.
Speaker 3: I mean that's what I do, right, That's what my
Speaker 3: team does. We're going and figure out how we can
Speaker 3: improve something. But we're using AI to do a lot
Speaker 3: of the analysis now sure, because it's just faster and
Speaker 3: we get richer response results and then we review and
Speaker 3: then we can review that and add to it and
Speaker 3: figure out what it missed, and but it's just so
Speaker 3: much faster. In fact, we have a really the way
Speaker 3: we estimate projects is way more detailed than most software
Speaker 3: companies do it, and it's just because we have this
Speaker 3: kind of concept of excellence in our company that if
Speaker 3: we can, if there's a if we can be better
Speaker 3: at it, then we work hard to try to be
Speaker 3: better at it in in terms of accountability and every aspect.
Speaker 3: One of them is estimating projects, because that one is
Speaker 3: a very visible different, very visible difference, not just in
Speaker 3: the back end, but you see if you're if we're
Speaker 3: handing somebody an estimate, it's broken down in a lot
Speaker 3: of detail by module that we're going to build and
Speaker 3: which parts of the application are affected because we need
Speaker 3: that module. You know, mobile part IoT, the business rules database,
Speaker 3: the data layer, but you know what's affected by it.
Speaker 3: And we build out these really sophisticated testaments, which is
Speaker 3: the most expensive process we have internally when we're building
Speaker 3: these for customers, because it takes my most high level
Speaker 3: people in the company that are the smartest and the
Speaker 3: most expensive to spend quite a bit of time working
Speaker 3: through these to give these estimates. But they're accurate, and
Speaker 3: so we don't want to not do it. So we're
Speaker 3: building an AI model right now that mimics this estimation
Speaker 3: process to produce the same kind or better estimates than
Speaker 3: what we're currently doing, but using an AI tool to
Speaker 3: actually generate them, which we'll be able to generate an
Speaker 3: estimate in an hour instead.
Speaker 1: Of a weak got it? Okay, Well that gets to
Speaker 1: what you were describing in that AI dignostic tool for
Speaker 1: the whole system, the business operating system. Do you have
Speaker 1: what's your take, David on the geopolitical situation like sort
Speaker 1: of the great powers competition so to speak, and artificial intelligence?
Speaker 1: Do you think that there is such a thing as
Speaker 1: a competition? Are the you, US and China competing? If so,
Speaker 1: what is that's? What's your opinion on that situation?
Speaker 4: Well?
Speaker 3: I that one. I feel like I'm an ostrich okay o,
Speaker 3: bit my head's in this sand because because it's very
Speaker 3: hard to know, I just got to assume that everybody's
Speaker 3: doing a lot more than what we know in terms
Speaker 3: of competition. And you know, data privacy is sort of
Speaker 3: a misnomer. They're really I don't think is any real
Speaker 3: data privacy anymore? So much stuff has been hacked and
Speaker 3: so many people have access to so much data. Obviously,
Speaker 3: there's certain people you don't want to get access to
Speaker 3: data because they're going to use it maliciously on individuals.
Speaker 3: But I think a lot of the big actors are
Speaker 3: just using this to figure out how to manipulate, well,
Speaker 3: like Elon Musk in this LAS selection. And I'm not
Speaker 3: taking aside here because I don't want to offend anybody
Speaker 3: whether you were on left or on the right.
Speaker 4: But but there's no question that he.
Speaker 3: With all of his AI capabilities and his money, that
Speaker 3: he had a huge and one man had a huge
Speaker 3: impact on this election. Yeah, that was never possible before,
Speaker 3: but he could do it because of the algorithms, you know,
Speaker 3: and the reach that he has with X and probably
Speaker 3: reached beyond X, right, because he's using algorithms that are
Speaker 3: tweaking people that have big followings and other platforms. So
Speaker 3: got it right, and they is being able to figure
Speaker 3: out who who to tweak, the what influencers to tweak
Speaker 3: and push so that he'll get the result that he wants.
Speaker 3: Sou So, I got to believe that, you know, China,
Speaker 3: with their money and resources, are doing the same thing,
Speaker 3: and we know that Russia has been committed to doing
Speaker 3: this is to a large degree. I don't know that
Speaker 3: they have the AI chops, but they certainly have the
Speaker 3: They certainly understand social influence and how critically important that is,
Speaker 3: and so you've got to believe that they're they found
Speaker 3: some way to be able to invest.
Speaker 4: Heavily in in AI.
Speaker 3: But I think there I don't think anybody really has
Speaker 3: much of a chance of catching up to the United
Speaker 3: States except maybe China, and I don't know if they do,
Speaker 3: if they can, just because the US is pretty far
Speaker 3: ahead right now in the AI world in.
Speaker 4: Terms of these large language models.
Speaker 3: Being with China is that the government can throw government
Speaker 3: money in large, large quantities.
Speaker 4: Right, it's not an.
Speaker 3: Individual, but it's the economy of China that can be
Speaker 3: tossed at at a problem.
Speaker 4: You know, the US doesn't.
Speaker 3: Well, maybe the US can do that now because you've
Speaker 3: got Elon Musk in that position. But but so that
Speaker 3: makes China a real potential threat and they you know
Speaker 3: that they've been doing that because you'd have to you know,
Speaker 3: I said, I'm an ostrich, you'd have to be.
Speaker 4: You would have to be.
Speaker 3: Galvanized inside of a geode or something like that, right, Yeah,
Speaker 3: to not know that that was critical to your service,
Speaker 3: not only to your success, but probably your survival is
Speaker 3: a as a political system.
Speaker 1: Yeah, yeah, what do you think?
Speaker 3: So you asked me that question, I'm going to ask
Speaker 3: you the same question, So tell me what you think.
Speaker 1: I think. I think the great powers competition is definitely
Speaker 1: a real thing. I think. Yes, Obviously, technology, if it's
Speaker 1: not a part of it, it's at the center, loves
Speaker 1: the whole thing. To echo what you were talking about,
Speaker 1: I absolutely think that all these machine learning fueled influence
Speaker 1: operations are all over the place and they're working because
Speaker 1: most people are none the wiser that they even exist,
Speaker 1: which is unfortunate.
Speaker 3: So and everybody's so extreme anymore.
Speaker 1: Yes, well, that's something that's something that you can leverage
Speaker 1: in your campaign.
Speaker 3: So what do you think if you don't mind me asking, so,
Speaker 3: what do you think is good that may come out
Speaker 3: of this AI progression in the next year to eighteen months?
Speaker 3: What do you think is bad that may come out
Speaker 3: of this AI progression in the next twelve eighteen months?
Speaker 3: Eighteen months is pretty far out. That's why I'm only
Speaker 3: going eighteen months. But what do you think.
Speaker 1: I mean for the good. I would like to think
Speaker 1: that eventually people just see the writing on the wall
Speaker 1: and understand, you know, where we're headed, you know, big
Speaker 1: picture wise, where we get to the point where we
Speaker 1: can't be an ostrich in any situation, be like, hey, look,
Speaker 1: this is the way of things. What do we do now?
Speaker 1: Because I feel like where.
Speaker 3: Are where do you think where are we headed? Because
Speaker 3: I don't know exactly where we're headed other than that
Speaker 3: AI is AI is going to continue to expand this
Speaker 3: only thing I know, but I don't know what that
Speaker 3: means exactly.
Speaker 1: Yeah, well, I guess that's what we get to decide together,
Speaker 1: perhaps if anybody has to say anymore. And that's what
Speaker 1: I hope that we do. That in the midst of this,
Speaker 1: that the individual person isn't just steamrolled over by whoever
Speaker 1: owns these things. That's the one that's the main concern
Speaker 1: I have.
Speaker 3: Oh yeah, I love that. I agree with that. Yeah,
Speaker 3: because there's so much evidence of being steamrolled by you know,
Speaker 3: very few individuals at this point.
Speaker 1: Yeah. Yeah, it seems to be the trend of where
Speaker 1: things are going. So hopefully maybe that trend can be reversed. Somewhat,
Speaker 1: and I don't know that's that's me. But but we're
Speaker 1: we're getting towards the end of the show here, David,
Speaker 1: were getting We're not We're not at the end. I
Speaker 1: just want to say, we're getting there.
Speaker 4: Yeah, I've been watching.
Speaker 3: I've been watching the time because I have a tendency
Speaker 3: to run on, so I always have to kind of
Speaker 3: keep my eye on the time.
Speaker 1: Not yet running on is perfect in the setting, sir,
Speaker 1: because this is a podcast we're talking. It's it's great,
Speaker 1: so it's much appreciated.
Speaker 3: Well, it's really fun, a fun scary conversation sort of
Speaker 3: in the dark way.
Speaker 4: It's fun.
Speaker 1: Yes, indeed, I'll ask you now, would you want to
Speaker 1: or be able to stay on to the next hour
Speaker 1: where this becomes the Uncle Show? Are you gonna have
Speaker 1: to get going after this? I?
Speaker 3: Unfortunately, I have to get going.
Speaker 4: Uh.
Speaker 3: And I have not heard, I have not listened to
Speaker 3: the Uncle Show? What is the Uncle Show about? So
Speaker 3: that I have some idea what it even is.
Speaker 1: It's it's well, Uncle is my uncle in law, and
Speaker 1: the show is about whatever is on his mind. He's
Speaker 1: the guy. It's his show. I'm just here to you know,
Speaker 1: keep the conversation almost coherent, and it's it's a crazy comy.
Speaker 1: It's a weird comedy shows. It's a really weird show.
Speaker 1: That's all I could say about it.
Speaker 4: I mean, I would love to be on it.
Speaker 3: I just unfortunately I only had this hour, so I
Speaker 3: can't tonight. Maybe some other time I would love to
Speaker 3: do it. It sounds he sounds like somebody really fun
Speaker 3: to talk to.
Speaker 1: Yeah, no, I appreciate it. I appreciate you being here.
Speaker 1: And yeah, I've I've I've learned a lot. It's it's
Speaker 1: it's it's really I'm glad that you came here tonight, David.
Speaker 1: Before we go, why why don't you just let people know?
Speaker 1: I don't know if you have social media handles you know,
Speaker 1: I give out, or if you want to say anything
Speaker 1: about techis.
Speaker 3: I'd love to. Yeah, a shameless plug, you bet. And
Speaker 3: I'm starting a podcast. They don't have it yet. It
Speaker 3: will it will go live I think in two weeks,
Speaker 3: called Scaling Smarter. So I work with a lot of
Speaker 3: startups as well as larger companies too. But but you know,
Speaker 3: I have a passion for working with the startups and
Speaker 3: I've and I anyway, let me that's another show, so
Speaker 3: I'll just talk about techis. So we're a custom software
Speaker 3: development shop. Uh, it's spelled t e k y z
Speaker 3: dot com. T e k y z dot com. And
Speaker 3: you can reach me at David at t e k
Speaker 3: y z dot.
Speaker 4: Com or you can go to B Hirschfeld.
Speaker 3: That's my handle on LinkedIn, So I just search for
Speaker 3: David Hirschfeld and Hirschfeld. There's only a couple of ways
Speaker 3: you can misspell it, so just try a few different ways,
Speaker 3: but I come up pretty easily. I've got a pretty
Speaker 3: good sized following on LinkedIn. But our whole pitch is
Speaker 3: that we are a hyper exceptional software development team. And
Speaker 3: I say that because not because I expect you to
Speaker 3: believe me, but I would expect anybody that wants to
Speaker 3: talk to me about software to ask, Okay, what evidence
Speaker 3: do you have?
Speaker 4: What does it mean to be hyper exceptional?
Speaker 3: And then I'll show you, because there are certain things
Speaker 3: and artifacts that are produced when you're really exceptional software
Speaker 3: development team that most software development companies don't produce and
Speaker 3: don't have, and I can show you what they are
Speaker 3: if that matters to anybody that's listening anyway.
Speaker 4: But I really had fun.
Speaker 3: This was a very fun conversation, and you're really good
Speaker 3: with the questions and keeping a converse about something as
Speaker 3: esoteric as AYI going but of course it's something I
Speaker 3: love to talk about. So thank you for that.
Speaker 1: Absolutely. Yeah, anybody that can talk about I'm happy to
Speaker 1: speak with, and certainly you can. And yeah, interesting insights
Speaker 1: with the sort of the things that you've been working on.
Speaker 1: That was. I was happy to hear about that because
Speaker 1: I always like hearing these real world examples. I feel
Speaker 1: like so much of the conversation is just this weird
Speaker 1: hyperbole and again like oh it's going away. It's like,
Speaker 1: can we actually talk about what's going on, like actual
Speaker 1: projects that are happening or have happened. And so thank you.
Speaker 3: For no idea where that going away conversation is taking place,
Speaker 3: because there's not this there's not like a grain of
Speaker 3: sound evidence in my mind that there's anything happening other
Speaker 3: than momentum continues to build.
Speaker 5: Yeah.
Speaker 1: Well, it's like my wife always tells me, I follow
Speaker 1: all the wrong people on these social media platforms, and
Speaker 1: so I get all this garbage coming my way and
Speaker 1: she's mostly right. Yeah, I eight is absolutely terrible, but.
Speaker 3: So what's that saying, smart wife, smart life. No, that's
Speaker 3: not the same.
Speaker 1: It's yeah, yeah, I do well to listen to us,
Speaker 1: for sure. But David, thank you for coming on the
Speaker 1: show tonight, and thank you for having me er. Yes, yeah,
Speaker 1: So I'll just say goodbye and maybe i'll have you
Speaker 1: back again some time.
Speaker 3: Oh, I'd love to. I really appreciate it. If you
Speaker 3: have a great weekend. Yep, yep, take care, sir, you too.
Speaker 3: All right, So that was David Hirschfeld. I hope everybody
Speaker 3: enjoyed that conversation. This again, this is the Age of Transitions.
Speaker 3: If you haven't been to the Patreon account lately, do
Speaker 3: go over there. I've been loading those videos up. I'm
Speaker 3: happy with all that. I have the transfer Sistor Radio
Speaker 3: first one hundred episodes download available if you just want
Speaker 3: to get that, and then all the usual stuff at
Speaker 3: the Age of Transitions dot com.
Speaker 1: Please do stay tuned here at the Ocelli Radio Network
Speaker 1: because you know what's next. It's the Uncle Show coming
Speaker 1: right up. So if you're in the mood for the
Speaker 1: drink and a laugh, that's what we're about to do.
Speaker 1: So please stick around at Ocelli dot com. My name
Speaker 1: is Aaron Franz. As always, I will leave you by
Speaker 1: saying secrecy gun.
Speaker 6: The War State by Michael Swanson explains the great national
Speaker 6: transformation that took place and put the Kennedy presidency in
Speaker 6: the context of the times and reveals never before published
Speaker 6: information about the Cuban missile crisis. President Kennedy would not
Speaker 6: have been assassinated if he had been president two hundred
Speaker 6: years ago. His assassination took place in the context of
Speaker 6: the Cold War and the rise of the national security state.
Speaker 6: Before World War II, the United States was a continental republic.
Speaker 6: In the decade that followed, it became an imperial superpower.
Speaker 6: Generals such as Curtis LeMay not only wanted to invade Cuba,
Speaker 6: but knew that there were short range missiles on the
Speaker 6: island armed with nuclear warheads that they could not destroy
Speaker 6: because they were on mobile launchers. Their invasion could have
Speaker 6: led to a Third World War, and they wanted to
Speaker 6: go to war anyway. The War State by Michael Swanson
Speaker 6: reveals why, and we'll show you what President Kennedy was
Speaker 6: up against. For more information the War State dot com.
Speaker 5: Go ahead, call it the truth about the Dayfay assassination.
Speaker 7: Right well, what do you want to know any Baker's
Speaker 7: wild claim?
Speaker 1: Oswald girlfriends he knew Ruby and Barry answer weapons, Really.
Speaker 7: I imagine I could claim I have four wheels. It doesn't
Speaker 7: make me a wagon.
Speaker 1: But okay, Oswal was on the building and trying to
Speaker 1: prevent the murder of John Kennedy.
Speaker 7: Come on now has a.
Speaker 5: Real effort on the day of hay assassination into reclaim.
Speaker 7: Go to Amazon dot com enter Judith Baker in her
Speaker 7: own words. You'll get the results for a digital copy
Speaker 7: of a book where Walt Brown utilizes her own words
Speaker 7: and the known evidence in the case to get at
Speaker 7: well a different perspective. Let's say you can get Judith
Speaker 7: Barry Baker in her own words from the author himself,
Speaker 7: signed if you request it by contacting doctor band out
Speaker 7: A K I A S J F K at A
Speaker 7: O L dot com. It's a fun book and it
Speaker 7: actually dissects the many, many fantastic claims Judith very Baker
Speaker 7: in her own words.
Speaker 5: Thank you for all the great information.
Speaker 8: Shelley dot com Radio Network, Chilly dot com.
Speaker 1: Do you remember that time when Benjamin Fulford said that
Speaker 1: an Asian secret society was going to dispatch ninjas to
Speaker 1: take down the Illuminati.
Speaker 2: Ooh that's interesting. Yeah in the platoon.
Speaker 1: Yeah, did that ever work out too good?
Speaker 2: No?
Speaker 1: It didn't, did it? But here on o'ceelli dot com
Speaker 1: radio network, things work out a bit better, don't.
Speaker 2: They much better?
Speaker 9: It's clear and understanding about the programs. The programs, how
Speaker 9: much clearer getting live people into it. They really have
Speaker 9: a good conversation going much better, much better scene.
Speaker 1: I say, forget Benjamin Fulford and his ninjas and listen
Speaker 1: to the o'chelly dot com radio network.
Speaker 2: I agree.
Speaker 9: It's straight to the point, straight talk, and I like.
Speaker 2: That idea Olly dot com.
Speaker 10: Mony Mony, Mony, Mony, Horny.
Speaker 2: This is a Monasse podcast. Code wait, code wait, God
Speaker 2: wait here, will pick up? God?
Speaker 9: Hands your cellphones and I me and listen. Dude, I'll
Speaker 9: go to the podcast. Watch out. If you're sitting down
Speaker 9: for this, or if you're standing up, you better get
Speaker 9: ready for this because it's gonna hit their air drums.
Speaker 2: I'll go the podcast.
Speaker 1: You were listening to uncle the broadcast. My name is Aaron.
Speaker 1: I'm definite in law means to start show.
Speaker 2: Hello, ladies and gentlemen, I am back from my coops.
Speaker 9: How about Everyboddy, I should know. It was excellent fun.
Speaker 9: I met some people from it from Utah, oh Utah,
Speaker 9: I found I made some people there what a state
Speaker 9: and uh and it was very interesting.
Speaker 2: Mat fact. I saw the Beatles, actually the.
Speaker 1: Live Beetles, Beetles I heard about it.
Speaker 9: That was excellent music ahead John Lennon singing Elton, John Lennon, No, no, no,
Speaker 9: no cold down.
Speaker 2: So I kick who was it?
Speaker 9: It was the guy. It was the guy that made
Speaker 9: the music, John Lennon.
Speaker 1: Okay, So you saw John Lennon in uh the cruise
Speaker 1: on imagine, Oh he sang that song imagine not a man.
Speaker 9: So you didn't you didn't see them, So you said,
Speaker 9: I saw them the singing uncle.
Speaker 1: That's John Lennon. That's his that's his uh solo artist work.
Speaker 1: So you saw John Lennon solo and you saw the
Speaker 1: Beatles all on one cruise the.
Speaker 2: Beatles his music.
Speaker 1: But that song he took a break and said here,
Speaker 1: I'm gonna sing my solo song for me. I'm gonna
Speaker 1: play the piano.
Speaker 3: And say that. It was the whole thing of the Beatles.
Speaker 2: Every single one of the Beatles.
Speaker 9: Very good that I listened to, not not the people
Speaker 9: from uh nineties, eighties and seventies.
Speaker 2: Okay, none of that stuff. It's sixties, it's down.
Speaker 7: It's too bad you didn't run into some people from
Speaker 7: Utah a couple of years ago, because sometimes I would
Speaker 7: send Uncle shows out to that radio station in Utah, and.
Speaker 2: You would have told me that. I could have asked the.
Speaker 7: Man, well, told me that, dam I did, Yes, I
Speaker 7: did a couple of years again, a couple of years ago,
Speaker 7: I was sending our radio shows out to Utah. That
Speaker 7: was one of my stations, and every once in a
Speaker 7: while I would tell you the customers, well, don't you
Speaker 7: remember I sent your shows out and we got the
Speaker 7: people from Georgetown, Texas and all that. And I was
Speaker 7: sending the Uncle show out sometimes along with the distribution
Speaker 7: pro Shelly dot com.
Speaker 2: So you know town.
Speaker 7: But I told you that, I told you that years ago.
Speaker 7: You just don't remember that.
Speaker 3: Again.
Speaker 1: Well, for all we know those people that you talked
Speaker 1: to from Utah, Uncle, maybe they had heard your show
Speaker 1: on local station.
Speaker 9: It was a family kid uh and his girlfriend and.
Speaker 3: She Uh.
Speaker 2: It was a family. If they were new I didn't
Speaker 2: see the parents.
Speaker 7: If they were new Salt Lake City, there.
Speaker 2: Was a station out there, School Lakes.
Speaker 3: It might have been.
Speaker 1: It's a big city.
Speaker 7: It's a big city and it's one of the main
Speaker 7: cities in Utah, right and uh, you know, and but
Speaker 7: like I said, we were on an AM and an
Speaker 7: f M station out there, so so.
Speaker 9: You probably would have known these guys people well never
Speaker 9: never know.
Speaker 7: I don't know if I would have known them, but
Speaker 7: they might have known you guys from the broadcast, or
Speaker 7: they might have known.
Speaker 9: Me if I would have of course I was so
Speaker 9: I don't know about my vacation.
Speaker 1: I've got you forgot to be working on your vacation,
Speaker 1: saying that thinking come on, always never not working.
Speaker 9: And I keep saying over and over me sending cons
Speaker 9: out just remember.
Speaker 2: Gets from it's n n W. They probably they probably
Speaker 2: wall listening. You know what you said.
Speaker 7: We don't know, we don't know.
Speaker 9: They probably, but I didn't know that it might have
Speaker 9: been them.
Speaker 7: Well I know. Sidekick also needed to get you new
Speaker 7: cards too, that's and that's something that's got to get
Speaker 7: done soon, right.
Speaker 2: I gotta new cards up there. I got Hey, that's
Speaker 2: your your sign of it.
Speaker 1: It's my side.
Speaker 2: You better get going.
Speaker 1: I will, I will, I will get going. I'll do that.
Speaker 1: And of course, the whole time you were on vacation,
Speaker 1: I was here. You're at home, and I was working.
Speaker 1: I Uncle, I became a general in a war while
Speaker 1: you're gone. What war it was? It was war on
Speaker 1: a holiday, no less, it was all out war. It
Speaker 1: was the war on Christmas Thanksgiving spectacular. Uncle. Oh yeah, yeah,
Speaker 1: you said, yes, waged a valiant crusade against uh, the
Speaker 1: other holiday that wasn't happening. But I have bad news
Speaker 1: for you.
Speaker 9: Better not be no bad news on my side. It
Speaker 9: better be your side side.
Speaker 1: Yeah, it's bad because we didn't win. We did not
Speaker 1: defeat Christmas. Uncle, I'm sorry to report to you didn't
Speaker 1: beat Christmas. I was really confused. It wasn't for lack
Speaker 1: of effort. We tried, We tried. Oh, we're gonna call.
Speaker 2: I know who is this?
Speaker 9: Come on, Jim, Come on, Jimmy, Jimmy, I know it's him.
Speaker 2: Come on, Jim, it's me again.
Speaker 1: Uncle.
Speaker 11: I learn.
Speaker 12: I'm sorry you didn't get him this time, But don't
Speaker 12: you keep trying. I eventually you're gonna win.
Speaker 3: Oh.
Speaker 2: He never gonna catch your voice. I can.
Speaker 1: It's a talent. It's the talent that you have in nine?
Speaker 1: What do you mean the voice catching? Yeah, yeah, I
Speaker 1: cut the Yeah. Well, your Detroit team did one for me.
Speaker 1: They're going they're going to They're going to super Bowl.
Speaker 2: Detroit's going, I think so, I don't care what you said.
Speaker 2: I believe they're gonna go. Who they're gonna be now
Speaker 2: that that's a question. I don't know yet.
Speaker 1: Oh boy, to trade in the super Bowl? What do
Speaker 1: you think, Jimmy, is that true? Is that gonna happen.
Speaker 2: It's gonna happen.
Speaker 12: That's absolutely gonna happen.
Speaker 2: Oh, you got your mountain too ready? We got some
Speaker 2: drinks yet.
Speaker 9: I was about to say, we're going to open up
Speaker 9: some of these drinks here. They'll get back to the program.
Speaker 2: Okay, so you got your drink.
Speaker 10: I got mine ready.
Speaker 4: Okay, well open.
Speaker 2: Up this thing and no match less talk more start try.
Speaker 1: What do we got there? What is it?
Speaker 2: I don't know, but we're gonna drink it.
Speaker 1: We're gonna we all know what it is, but we're
Speaker 1: gonna pour it in these shot classes that you got
Speaker 1: on vacation, right uncle. Yeah, So these are new shot
Speaker 1: classes that we're gonna use. A We're gonna drink something
Speaker 1: out of them. Here, check it out. I'll hold up
Speaker 1: my shot class at the viewing audience except for on YouTube,
Speaker 1: because I don't know if I got that working tonight,
Speaker 1: but everybody else can see it. What was it say, Ireland,
Speaker 1: This wasn't from your recent trip.
Speaker 2: Look at that scale.
Speaker 1: Oh there's your real new one one here. I'll hold
Speaker 1: up the new ones so people can see the skeleton.
Speaker 2: Skeleton's back there it is.
Speaker 1: This is from the new trip. Where's it say? It says,
Speaker 1: uh Cobos dot com.
Speaker 2: We will That was the first stop.
Speaker 1: There you go, Mexico. That's where it work.
Speaker 2: Well, in Mexico.
Speaker 9: We went to Mexico first stop, and then we went.
Speaker 1: Well, it was a Mexican cruise. It was several different ports,
Speaker 1: all in Mexico. Yeah, in Mexico, So there are a
Speaker 1: few different ones.
Speaker 5: Okay.
Speaker 7: You also might have a skype caller joining, just so
Speaker 7: you know. Okay, let's see he should be added in
Speaker 7: here shortly working on it and should be there in
Speaker 7: just a moment. By the way, I got a bottle
Speaker 7: of Jack Daniels from one of the authors. Came out
Speaker 7: into the lobby while I was in Dallas there and
Speaker 7: he gave me.
Speaker 1: A Jack Daniels.
Speaker 7: Yeah, full bottle game. There we go. Your call is connected.
Speaker 1: Oh we got a new collar on that on the.
Speaker 2: Scale online, Jimmy, let me see who this is?
Speaker 7: Hello?
Speaker 2: Who is this on this line?
Speaker 1: Log?
Speaker 5: Long time listener? Oh no, sometimes call her.
Speaker 2: I know who you are.
Speaker 1: This guy.
Speaker 5: Man, I'm above the ice wall.
Speaker 9: Ice wool Man. I call him Ice wool Man. Call
Speaker 9: him some names. I'm telling you he's right, good for names.
Speaker 1: Oh yeah, still ice bol good name guy.
Speaker 7: Are you about to get angry at our tariffs there,
Speaker 7: mister Canada man, because the tariffs are gonna fly to
Speaker 7: Mexico and Canada from what I understand. What's up?
Speaker 11: Yeah?
Speaker 5: All that all that stuff I said down in the US,
Speaker 5: it's it's gonna real take a fight out of that.
Speaker 5: All right, absolutely, there we go, and said when I
Speaker 5: kept when I cut my hair, I usually would send that,
Speaker 5: sell that down to the Californians, the good wigs.
Speaker 1: I said, Uh, you said the number of the show, uncle, Yeah,
Speaker 1: I believe what are we?
Speaker 5: Twenty one time five two seven five zero one six.
Speaker 2: No, that's the phone, that's the number to call in.
Speaker 9: Yeah, hey, looking there the customery doing my numbers that's right.
Speaker 2: So I kicked you on idea sounds good? All right?
Speaker 5: Three hours of three hours of the war on Christmas there.
Speaker 1: Thank you soldier, Thank you.
Speaker 5: Quality Turkey techniques and such.
Speaker 1: Yeah.
Speaker 2: I said that on my Instagram, by the way.
Speaker 1: Yeah, I was trying I put it on.
Speaker 2: I was losing. But Chris I saw it. I saw it,
Speaker 2: but I I couldn't call Chris.
Speaker 1: You know how to call in.
Speaker 2: No, I couldn't do it.
Speaker 5: I couldn't do it.
Speaker 9: You couldn't do it because I was visiting my other people.
Speaker 1: Yeah, yeah, yeah, I saw you there in the chat, Robin.
Speaker 1: I appreciate you being there.
Speaker 2: It's cool.
Speaker 1: And everybody who has watched it, thank you. It's actually
Speaker 1: still on YouTube. It will be there.
Speaker 2: It's what twelve hours long?
Speaker 1: Nestled it somewhere in the middle there is my eighty
Speaker 1: D TV video is probably the best part of the
Speaker 1: whole thing.
Speaker 5: I see. That's what I was watching. I saw some
Speaker 5: of those.
Speaker 1: You caught that, okay, so what do you think of
Speaker 1: that one?
Speaker 5: Was getting wilder?
Speaker 1: Yeah, Steve good Old see did you enjoyed that video, Robin?
Speaker 5: Yeah, that was actually the first time I've bed it
Speaker 5: because I actually owned the ad t V video. Okay,
Speaker 5: but the time that I tried to watch it, it
Speaker 5: was too hectic with my with the mood of the
Speaker 5: of the hour, so I never ended up finishing watching it.
Speaker 5: So that was actually mostly new to me.
Speaker 10: What is this video?
Speaker 3: What?
Speaker 5: What kind of video you get? Did you do?
Speaker 2: Uh?
Speaker 1: How about how about you, Robin? Could you describe what
Speaker 1: this video might be like? What was your first take?
Speaker 1: How would you describe what add TV is?
Speaker 5: It's like, think, well, I don't know if you were
Speaker 5: doing it on cable access or not, but it was
Speaker 5: it was effectively chaotic times of Aaron's college college years.
Speaker 5: It looked like lots lots of drinking, wrestling.
Speaker 2: Oh, you mean it was one of.
Speaker 5: It's definitely it's very Jack asks c k Y I ask.
Speaker 5: I would say, yeah, I don't know if you were
Speaker 5: before or after those guys. You know, it was all
Speaker 5: maybe it was in the zeitgeist.
Speaker 1: Yeah, it was concurrent about it at the same time.
Speaker 5: Yeah, yeah, yeah, and uh and then you know there's
Speaker 5: there's yeah, lots of interesting just just quick cuts guys, uh,
Speaker 5: like mooting, mooting things. There's some other guy, naked guy
Speaker 5: on a tank. There's these different things and uh yeah, yeah,
Speaker 5: it looks like a good time for the most part.
Speaker 7: Naked Tank. I don't remember seeing the naked guy on
Speaker 7: a tank when.
Speaker 5: When that is what that is? It's only a special
Speaker 5: cuts or something.
Speaker 7: Oh okay, I don't think I watched the special features
Speaker 7: yet on there.
Speaker 1: That's that's a treat, that one right there is. I
Speaker 1: did the little web episodes I put on my current website
Speaker 1: at the time, and that one was titled Tank. It
Speaker 1: was essentially starring my buddy Crash, who is the vocalist
Speaker 1: for ten Gage, which you play on the network all
Speaker 1: the time. Shock I used.
Speaker 7: But I've lost the you know, I've lost those m
Speaker 7: P three files.
Speaker 1: Again, I can get him back to you.
Speaker 5: Yeah, I was wondering if that's why you weren't playing
Speaker 5: my stuff anymore.
Speaker 7: Yes, I lost the m P three files.
Speaker 5: That's why.
Speaker 7: So if you want to send them back.
Speaker 9: So I kicked get him to get him get him
Speaker 9: straight again. He's doing something right.
Speaker 7: I had a computer crash. I had a computer crash
Speaker 7: some time ago, and I lost all those files. And
Speaker 7: uh yeah, that's why.
Speaker 5: I missed here and was talking about banks.
Speaker 1: Yes, we need more of that in our life.
Speaker 7: That's that is great. I would love to play that
Speaker 7: one again. Yes, absolutely so.
Speaker 2: What kind of drink you have on tonight?
Speaker 3: Rob?
Speaker 5: Personally, I've just had h two oh at the moment here, well.
Speaker 2: We got drinks again right now?
Speaker 9: Out to say when I have a drink, so everybody
Speaker 9: can have that drink now, oh, now we can start drinking.
Speaker 2: Yeah, Jimmy's got his Mountain dew. Okay, so every buddy
Speaker 2: have a drink.
Speaker 1: Everybody have a drink.
Speaker 9: Now.
Speaker 2: This is Funday, so let's go.
Speaker 5: Friday. That's the Odin's wife's day maybe right, uh Friday
Speaker 5: free fore Yeah, something like that.
Speaker 2: Friar's Day, Friar's Day.
Speaker 1: Hey, I've got your haircut. Check it out there that
Speaker 1: I have to share.
Speaker 9: Your wife got me us I was with him and
Speaker 9: they got they got the champagne.
Speaker 2: Champagne, the shavy head. Oh okay, go shamp whatever that
Speaker 2: thing is the racer.
Speaker 9: No, no, this stuff huge shaving shaving about.
Speaker 1: I'm gonna need that.
Speaker 2: You got it? Have it?
Speaker 1: I need it.
Speaker 5: That looks like a real strong shot, the.
Speaker 1: Shot glass working right.
Speaker 2: Still looking at me too. What the heck was this drink?
Speaker 1: I don't know? You you you kind of put it
Speaker 1: in there, and we sort of threw caution into the wind.
Speaker 7: Didn't even read what, didn't even read? Tell us what
Speaker 7: it is here?
Speaker 1: You want me to take a look at the bottle?
Speaker 1: Let me okay, it is for those your rocks.
Speaker 7: Yeah, for those of you playing at home, you might
Speaker 7: want to read the bottle before you drink it, but.
Speaker 3: Ahead, just drink.
Speaker 2: Now.
Speaker 1: That's that's how we made a d D t V.
Speaker 1: It wasn't by reading the bottle. It was by somebody
Speaker 1: passing it to us and saying, okay, you know that's
Speaker 1: what I usually did. So in that in that spirit, uncle, well,
Speaker 1: we'll now read. This is on the rocks premium cocktails,
Speaker 1: the Old Old Fashioned by not Creek. So this is
Speaker 1: a pre made, pre mixed Old Fashioned in a bottle
Speaker 1: maybe not creek whiskey.
Speaker 2: It's pretty good.
Speaker 5: Yeah, yeah, So what does that has some bitters and
Speaker 5: whatever the other craft is in there? Yeah?
Speaker 1: Where they put it in Old Fashioned? Jimmy, do you
Speaker 1: know what's in an Old Fashioned? That's a quick quiz
Speaker 1: for you. Do you know what's in there?
Speaker 2: Hmm?
Speaker 3: I thought it was.
Speaker 12: Basically vanilla tasting cream soda type stuff.
Speaker 2: Does taste like a little cream sugar. It has that taste.
Speaker 5: It does.
Speaker 1: I'm looking on the bottle to see if it tells
Speaker 1: me all of the it says. Let's see, staying true
Speaker 1: to the original recipe, we keep our old fashioned, strong
Speaker 1: and simple, using a generous poor of Kentucky straight bourbon, whiskey, bitters,
Speaker 1: cane sugar, orange, cherry, and lemon flavors.
Speaker 7: See, generally it's supposed to be a classic whiskey cocktail
Speaker 7: with bitters and simple syrup and fruit. So yeah, and.
Speaker 9: Of all of these and of all this drinking we've
Speaker 9: been doing, I've been like the fruit taste of these
Speaker 9: drinks that we've been dom who was doing that?
Speaker 2: Who had the food stuff?
Speaker 1: Well we have it right now?
Speaker 2: No, No, I mean before was it crazy whiskey?
Speaker 5: Bob?
Speaker 7: You have a disgusting, sugar free horror show of birthday
Speaker 7: cake and whatever you're not talking about.
Speaker 2: I can see what you are doing out of the yards.
Speaker 1: Yeah, that's that one.
Speaker 2: That one he got thrown up on. That thrown up on.
Speaker 1: That was from the heyday of the dollar store drink reviews,
Speaker 1: when the Dollar Store did was dependable, had the drinks. Yeah,
Speaker 1: it's just not there for the same to drink.
Speaker 9: It's good because that that's probably took him out of businesses.
Speaker 1: They drank that this swirl then nine cents story, that's
Speaker 1: probably what did it that that cakes, that cake drink.
Speaker 7: The people, and then I think it was creative accidents.
Speaker 7: Had to actually find that last one for us, and
Speaker 7: uh right, because we couldn't find it.
Speaker 2: You flavored?
Speaker 1: Was that one?
Speaker 7: I think it was birthday cake?
Speaker 2: Wasn't a birthday cake.
Speaker 13: I remember that one because I remember the school. The
Speaker 13: school I remember because he was his yard. You threw
Speaker 13: the stuff out in his yard boiled.
Speaker 7: Squirrel better, Yeah, I did. I dun'ped on the grass
Speaker 7: that killed the grass. I told you that.
Speaker 2: I remember that drink.
Speaker 7: This oh, this one right now drink Okay, no, no,
Speaker 7: this one right now is different. This is like an
Speaker 7: old fashioned in a in a container.
Speaker 2: This one.
Speaker 5: I was sick of sass perilla.
Speaker 7: Never mind what I forget?
Speaker 2: Like group, what are you talking about?
Speaker 7: Is like, yeah, that's that's a that's is an old
Speaker 7: fashioned drink, but it's not an old fashioned in the
Speaker 7: alcohol sense. So yeah, yeah, I get what you're saying.
Speaker 9: Uh.
Speaker 5: Mexico and they're renowned for their cheap tequilas. Did you
Speaker 5: get dipped into that a little bit down there?
Speaker 2: Any tequila?
Speaker 1: Actually smew it?
Speaker 14: Let me tell you it was a lot of there
Speaker 14: wasn't you can really tell, of course.
Speaker 2: But but I didn't. But I didn't get the drink.
Speaker 9: No, I didn't get the drink, but I smelt it
Speaker 9: my nose, nose.
Speaker 1: This stuff.
Speaker 9: Since we've been talking about all this stuff on my
Speaker 9: on my show.
Speaker 1: An expert.
Speaker 2: Now I'm an expert on the smell?
Speaker 5: Were you? Were you on a cleanse down there?
Speaker 2: Yeah?
Speaker 5: Yeah?
Speaker 2: The only thing I was drinking. The only thing I
Speaker 2: was drinking is my beers.
Speaker 5: Oh it just beers. Okay, taking drinking my beers.
Speaker 2: But the look I keep get food my shows.
Speaker 9: I got it down pat, So I say, okay, like
Speaker 9: face in the.
Speaker 7: Chat really quickly, face shifter in the chat. What is
Speaker 7: this crazy drink you dropped in here? I I don't
Speaker 7: know what this is. This Tazzi O Tazzy, I don't
Speaker 7: even know what the hell it is. It's please help
Speaker 7: me out. I don't want to play the videos or anything,
Speaker 7: but there's a weird drink he put in the room here.
Speaker 7: I don't know what it is.
Speaker 2: They mean fooling with you too with the drinks.
Speaker 7: I don't know, maybe drink.
Speaker 1: Oh yeah, the pink thing.
Speaker 7: You see that pink thing? Yeah, what is that?
Speaker 1: Was that something that we got from the dollar store?
Speaker 2: Don't tell me that that's the cake?
Speaker 7: I don't.
Speaker 1: Oh it's sock? Was that the you know what we
Speaker 1: did get from the dollar store once was Hello Kitty,
Speaker 1: Hello Kitty, Hello Kitty?
Speaker 2: Is jim It looks like but that's that's what it was.
Speaker 7: But this one is, Yeah, this one looks weirder than
Speaker 7: that though, and there's no Hello Kitty on it. I
Speaker 7: think it's just like, what is that a cow? What's
Speaker 7: going on?
Speaker 9: Let's get gets in touch with these inside your inside,
Speaker 9: in your crack boom, and let's find out these drinks
Speaker 9: because I'm gonna have to test them.
Speaker 7: Okay, what are you drinking? Face shifter? You're the only
Speaker 7: one who's active in the chat room right now, so
Speaker 7: tell us what you're drinking.
Speaker 9: And then well, look, of course we'll go out very important,
Speaker 9: very well, why important to find these people that are
Speaker 9: drinking stuff that we don't know about.
Speaker 1: I'll call on the drink and and important drinks. You know,
Speaker 1: I talked to Bob on the war on Christmas and
Speaker 1: you hear that we had a Kinko bra that was good. Yes,
Speaker 1: I also had a refrigerator in case I needed it,
Speaker 1: a four loco. However, I did not need it, so
Speaker 1: it's still in the refrigerator. I think I'm going to
Speaker 1: keep that for the revolution.
Speaker 3: This year.
Speaker 2: I did see a couple of them in there. I
Speaker 2: saw the blue, I saw a green ba can. Yeah,
Speaker 2: and something else.
Speaker 1: Well, there's a four loco. It's a it's what a
Speaker 1: sour tasting one. It went over so good last year,
Speaker 1: I figure, hey, why not do it again?
Speaker 2: Keep these drinks.
Speaker 9: I'm gonna talk to you something about this, okay, just
Speaker 9: a moment, just a moment people when you get something
Speaker 9: drinks like that and knowing about.
Speaker 2: Hold them up, hold them for the revolution.
Speaker 9: But like you're doing like you like you said, all right,
Speaker 9: so I'm doing the right thing. You're doing the right
Speaker 9: thing now, good, right, But but keep it up that way.
Speaker 2: We have them in there, stock the stock them. You
Speaker 2: have to stop them.
Speaker 1: It's a revolutionary event.
Speaker 9: It's levelution, you know, is too much way, Yeah, so
Speaker 9: you better tighten them up and get all these drinks
Speaker 9: in that corner so we can.
Speaker 2: Okay, we have some elution drink. We have them all
Speaker 2: wined up, so the drop glasses.
Speaker 9: Ready, and everybody drink that on my I go wall
Speaker 9: on and Chuck knows this too, I go wall on.
Speaker 2: More evolutions.
Speaker 7: I'm stepping away.
Speaker 1: Okay, I guess Jack, but what was that Robin?
Speaker 5: I heard? Just to say, if you have a little collection,
Speaker 5: that maybe be fun to have one of those one
Speaker 5: of those wheels you spin to see what one you're
Speaker 5: gonna drink.
Speaker 1: What do you think of that idea?
Speaker 2: I'm going, well, you put that on the list.
Speaker 5: We can make they even have they have the digital one.
Speaker 5: You know, you can probably find it out because you.
Speaker 2: Know, you know, you know the Evolution is my top show.
Speaker 1: Yes, you know, obviously obviously, and.
Speaker 9: So what I need from so kick and you, oh,
Speaker 9: stock refrigerators.
Speaker 5: Suck it up, stack.
Speaker 9: I don't know what levels coming, so you stuck it up.
Speaker 2: Doing that, but just stock it up.
Speaker 1: So keep going, keep doing what. I'm just like Big.
Speaker 9: Bobs saying he's got his own grigerator down, man, he does,
Speaker 9: and he's he's probably already ready to go.
Speaker 2: Get your stuff. And I'm trying to push it to
Speaker 2: this youring to get it going.
Speaker 1: This is like a news I love all these ideas.
Speaker 1: I like the spinny wheel idea, Robin, and I also
Speaker 1: like the digital version of it. Because I think you're right.
Speaker 1: I bet I could find like maybe a website that
Speaker 1: does that which I could cut to, like uh on
Speaker 1: the O B S I could show that, which would
Speaker 1: be a visual.
Speaker 5: I think maybe everyone likes that sound to talk those
Speaker 5: SMR listeners.
Speaker 1: Yeah yeah, good, oh man, we're gonna get some many listeners.
Speaker 1: Uh uncle, this is great.
Speaker 9: Well, I mean, I mean, and that's what I mean.
Speaker 9: And that's what I'm saying. Start collecting the drinks. That's
Speaker 9: all I'm saying. We will start collecting.
Speaker 1: We've got that aspect down, but we need we need
Speaker 1: more ideas.
Speaker 5: Jimmy.
Speaker 1: I'm gonna go back to you. What what idea do
Speaker 1: you have, Jimmy for the this year's revolution?
Speaker 9: What needs to be done just getting the drink?
Speaker 1: You need to know?
Speaker 12: Well, I was just wondering there, uh why the discrimination
Speaker 12: against cannabis?
Speaker 3: Could we have some midnight.
Speaker 1: Uh smoking reviews?
Speaker 5: Oh?
Speaker 1: Interesting? Now you know what that that brings up an
Speaker 1: interesting point, Jimmy, because there's all these dispensaries around all
Speaker 1: these different products call like gummies, you know the gummies.
Speaker 2: Yes, talking about gummies. I'm I'm I'm still over the
Speaker 2: same one.
Speaker 9: I've got to get a couple of new new couple,
Speaker 9: a couple of new ones.
Speaker 2: Talking about gummies.
Speaker 9: Yeah, I haven't been getting I haven't gotten money new
Speaker 9: guppies around this, Timmy. Yeah, everybuddy. After I get anybody's
Speaker 9: gifts done, I go out. I want to go to
Speaker 9: a you want to buy your own, buy my own
Speaker 9: and get some stuff gummy gummy season.
Speaker 5: Like that idea.
Speaker 2: We could do that, but.
Speaker 9: We have If that's the case, you know what we
Speaker 9: had to do, what we have to do. Say what
Speaker 9: you do with the drinks, Go out and get them, yep,
Speaker 9: and stack them stock, buy them stocking.
Speaker 2: This is the way to keep.
Speaker 5: Up with it. Not quite as you'd have to eat
Speaker 5: it at the beginning of the show.
Speaker 2: Well, yeah, the beginning of the show. That will be
Speaker 2: what's gonna happen. Yeah, yeah, that's what I'm just saying.
Speaker 5: You coming flavor at the beginning of them.
Speaker 9: That's what I was about to say. Just what you
Speaker 9: just said. We drink drink, no, we eat one dan,
Speaker 9: we go to the drinks.
Speaker 2: We'll be What.
Speaker 1: About this idea? What if I go out to the yard,
Speaker 1: take a bite out of the San Pedro cactus and
Speaker 1: then walk back inside and see what happens?
Speaker 2: Would that be too much? Be a bridge? We gotta heaven,
Speaker 2: we gotta would that be a bitch?
Speaker 5: Actually had some some blended scent. Pedro just just yesterday,
Speaker 5: did you there's a place that's a friend of mine
Speaker 5: runs that's a psilocybin kind of mushroom shop. They sell
Speaker 5: other the lion's mane and all that stuff. Too interesting?
Speaker 1: What was that?
Speaker 5: Well, it's very very minimal. I'd just call it a
Speaker 5: microdoss and Pedro even Yeah, so I don't, I don't,
Speaker 5: I can't really uh sick, but it is mescal and
Speaker 5: I think, right.
Speaker 1: I can't remember I've looked it up. I don't remember
Speaker 1: the DJA that's.
Speaker 5: The ingredient and the active ingredient on. Yeah, I wasn't
Speaker 5: dancing on the beach with the American flag like our
Speaker 5: guy after Thompson there, but and if you did more, yeah,
Speaker 5: I mean.
Speaker 9: I just gotta tell you this year it isn't gonna
Speaker 9: be a good year. That's when I'm coming here.
Speaker 5: We got an optimism.
Speaker 2: I got you.
Speaker 9: Yeah, man at the border, you're correct, You're correct.
Speaker 2: It isn't going to be a good year.
Speaker 9: Uncle, we got I don't care what you're offul saying,
Speaker 9: it's going to be.
Speaker 1: A crappy Yeah, we gotta come into the revolution, oh boy,
Speaker 1: not thinking that we're gonna just like crash the gates
Speaker 1: and no matter what, we're gonna make it the best.
Speaker 1: That's why we're coming in strong with the Ford logo.
Speaker 1: We're coming with gummies.
Speaker 2: Well, come in with gummies.
Speaker 7: Is uncle feeling like there's gonna be a crappy year
Speaker 7: coming up? Is that what you just said?
Speaker 2: Yeah, that's what I just said.
Speaker 9: Okay, it's gonna happen much Watch it's gonna happen.
Speaker 1: We're trying to prevent that.
Speaker 2: Well, I know that, I know that.
Speaker 9: We let me say that, we are going we uh
Speaker 9: might making it an interesting year for us, not for
Speaker 9: the wool I mean, the wolves gonna have their own problems,
Speaker 9: but for us. We're gonna have a pretty good year
Speaker 9: for having this for the first day.
Speaker 2: But after that.
Speaker 7: It's gonna go down, all right, that's how you see it.
Speaker 1: That's so I said, Yeah, it'd be good. Well mean
Speaker 1: not me. Let's make it good like I said, Uh
Speaker 1: Sam Peterro cactus floor loco.
Speaker 9: Uh gummies, that's the plus gonna be good.
Speaker 5: That's gonna be good.
Speaker 9: I'm miss that's the port that's gonna be good. But
Speaker 9: after that port goes down, I'm just saying.
Speaker 5: I don't know.
Speaker 1: After my uh mescalin Field vision quest, I feel like
Speaker 1: I might have like so many ideas that you just
Speaker 1: got to get on my way.
Speaker 2: Uncle, you have ideas, just move move aside. Okay, what
Speaker 2: kind of what do you think you're gonna have?
Speaker 1: I haven't figured that out yet.
Speaker 5: The landers, That's exactly it.
Speaker 9: That's what I'm hitting now. How you hitting the points?
Speaker 9: Musca of Musca is of idiot playing.
Speaker 5: He's heard I heard he might be investing in Jerild
Speaker 5: Sanders shrimp shops that too, Did you.
Speaker 2: Hear that something?
Speaker 1: Musk is going in big on Jeril Sanders.
Speaker 5: Spring back Shrimp was one of the bring back and.
Speaker 2: More to say, good look what's his name? Uh?
Speaker 9: And tell him could look finding the restaurant.
Speaker 5: He's bringing Gerald Sanders into.
Speaker 9: His Uh yeah, to see where where the restaurant is?
Speaker 9: Good luck, good luck, he's gonna be finding good luck
Speaker 9: finding it, good luck finding it.
Speaker 5: I think he's moved on.
Speaker 2: Ye, I know, he moved on.
Speaker 1: But these are all great ideas. I just I don't
Speaker 1: see how if we just even try to implement these
Speaker 1: couple of things that we're not just kind of a
Speaker 1: great year twenty twenty five, it's gonna be awesome.
Speaker 5: Yeah, Well, you'll start off really high and then whatever
Speaker 5: stout after that, we'll just you know, it will be.
Speaker 2: Storing down, falling down, falling down.
Speaker 5: Yeah, but still pretty high, right because he because he
Speaker 5: started off really high.
Speaker 9: I hate to see what's gonna happen. I hate to
Speaker 9: see what's gonna happen a few years down the road.
Speaker 9: One we're not here and they can't you here. I
Speaker 9: hate to see what's gonna happen.
Speaker 1: You're worrying about the future, uncle, Yeah, that's what I'm
Speaker 1: talking about. I hear you.
Speaker 2: It's the future, not the not the president.
Speaker 5: Well, you don't worry about that. You might get Do
Speaker 5: you think you're gonna get a resurrected uncle? Do you
Speaker 5: believe in resurrection?
Speaker 3: Oh?
Speaker 2: I'm getting you up there. You what, Yeah, those these
Speaker 2: guys are gonna be down now so.
Speaker 1: That's a big yas that's big is Okay, that's good,
Speaker 1: that's good.
Speaker 2: Well I have I'm that's gonna happen.
Speaker 1: What about you, eron, I believe in resurrection.
Speaker 5: Yeah, that will be back someday as a different to
Speaker 5: as a different person.
Speaker 7: Reincarnation.
Speaker 5: Sorry, that's that's the word I was looking for.
Speaker 1: I think you can make the case that we're all
Speaker 1: reincarnations of you know, the human experience, Like our lives
Speaker 1: are reincarnation. We're reincarnated. There's been somebody who's had not
Speaker 1: an identical life to mine, but in essence it was
Speaker 1: the same life. And guess what, back again, back at it,
Speaker 1: and here we are. That's all of us. That's my
Speaker 1: take on reincarnation.
Speaker 5: I guess maybe the concept that I would wonder is
Speaker 5: it is like if we retain anything from a previous
Speaker 5: from a previous life into a new one, like like
Speaker 5: small habits.
Speaker 2: Or I'm going to ask you, I'm going to ask
Speaker 2: you a question.
Speaker 5: Let's here, I'm going.
Speaker 2: To ask you a question. You been born again? Just
Speaker 2: just the way he stop laughing. I'm asking him this question,
Speaker 2: Have you been again?
Speaker 5: Is that the same question? Or do you mean I'm
Speaker 5: born again Christian.
Speaker 2: Have you been doing again?
Speaker 5: Yeah, I'm about sure, just for robbing.
Speaker 1: This is the question.
Speaker 2: Well you all information?
Speaker 5: I have, O d Okay, I have.
Speaker 2: So that's that's something to think about.
Speaker 5: Do you remember anything from from your past life?
Speaker 11: Oh?
Speaker 2: Yeah, lots. Oh they were all bad, but I turned
Speaker 2: him better.
Speaker 1: The past lives weren't great.
Speaker 2: No, you know, from the Christian perspective.
Speaker 1: Because this is the good one.
Speaker 7: Yeah, he gets born again in the same lifespan, you know.
Speaker 7: So the previous life is the life before then you're
Speaker 7: born again. So that's that. That's that whole perspective.
Speaker 5: That's his uncle a different concept.
Speaker 7: It's different.
Speaker 5: Well I say that when I broke my neck, I
Speaker 5: was probably born again in that sense, yeah, because that
Speaker 5: was a whole switch up of life there.
Speaker 1: It is a change.
Speaker 3: Yeah.
Speaker 5: But other than that, you know, maybe I have been
Speaker 5: reading some some spiritual texts lately, so you know, maybe.
Speaker 7: I'll maybe you're on your.
Speaker 9: Way, keep keep keep waiting them because you might telling you.
Speaker 9: It might be telling you something, m and it did
Speaker 9: me when I was reading. Okay, so there's a hunt
Speaker 9: to tell you.
Speaker 5: Yeah, I'll really subscribe to any any specific religion in
Speaker 5: that sense. But I definitely am understanding spirituality as a
Speaker 5: concept world right.
Speaker 7: In the meantime, you just gotta do you gotta do
Speaker 7: good things with your life because it was a gift,
Speaker 7: right uncle, So you got exactly.
Speaker 5: There you go.
Speaker 9: It was exactly what he said.
Speaker 1: Can make the must of it. I do something. I
Speaker 1: do some good alcohol people.
Speaker 9: I pretty can see in my past life they are
Speaker 9: thought I was being taken.
Speaker 1: They thought you were being taken taken.
Speaker 9: Yeah, you don't understand this down, I mean your way off,
Speaker 9: your way off. You don't even understand this. I don't,
Speaker 9: not even even my sister. This one doesn't under talk
Speaker 9: down to usselfall they do not None of these none
Speaker 9: of these people, None of you understand it's.
Speaker 1: Okay, dumb it down for us.
Speaker 2: What is the only one that would understand.
Speaker 9: It is my other sister and and okay and and Dell.
Speaker 9: So they get they understand it. Okay, is what I'm
Speaker 9: I'm getting.
Speaker 1: It's a Florida Yeah, yeah, more or less.
Speaker 5: Well, it did.
Speaker 9: We did something and my fun guy, we all did it.
Speaker 2: And was it escaline no being born again underwater baptism. Yeah,
Speaker 2: that is for the Catholic people. That's what they say the.
Speaker 9: Catholic people been doing again, but we said born again.
Speaker 5: In the water.
Speaker 1: Yeah okay.
Speaker 2: And and the one I did before was the.
Speaker 9: Going to clubs doing all this other stuff. But they're
Speaker 9: saying and after that happened, I haven't been a single one.
Speaker 1: Okay, So you've been, inact, you've been having a better
Speaker 1: life ever since then.
Speaker 2: Okay, that's my point. That's good, got the point?
Speaker 5: And what abaupteez?
Speaker 3: Move?
Speaker 2: Yes, something like that every child?
Speaker 1: Yeah, thank you, Jimmy, Yeah, yeah, Jimmy. What do you
Speaker 1: have to say about that whole situation?
Speaker 9: I was about to say that, whoa, Yeah, I think
Speaker 9: you can one of those strengths.
Speaker 12: That would be one way that I could put it.
Speaker 12: I feel I'm born again.
Speaker 2: Yeah, they listen, They listen.
Speaker 1: You're not the only one.
Speaker 3: Uncle.
Speaker 9: Well no, I that's because people are finally listening. I'm
Speaker 9: trying to get matter of fact, let me tell you
Speaker 9: something there.
Speaker 5: So I kicked.
Speaker 1: Okay, I'm here.
Speaker 9: I was working on your wife before you got married.
Speaker 2: About it.
Speaker 1: You're trying to baptize her.
Speaker 2: Well to understand what it was. Did she get it?
Speaker 9: I don't think grypped it right. She didn't grip it,
Speaker 9: so I just let it go. But but before I
Speaker 9: was working on her a little bit before I came
Speaker 9: up here, I'll just let you know.
Speaker 2: Yeah, So then that's where he's going to say.
Speaker 9: It.
Speaker 2: Did good.
Speaker 9: You're helping your your understanding, you know what you're doing,
Speaker 9: and you know what you mean you're doing.
Speaker 1: So would you call yourself an evangelist?
Speaker 2: Uncle?
Speaker 1: Is how you are?
Speaker 2: What does that call? What does that mean?
Speaker 1: It means you're going out there trying to convert people
Speaker 1: to the faith, to bring them over to the faith.
Speaker 1: I guess something.
Speaker 2: Like that at the time was.
Speaker 1: Okay, but that.
Speaker 2: And did that a little bit?
Speaker 5: Well?
Speaker 1: I mean the main point here is that I'm saving
Speaker 1: four loco and the refrigerator for the revolution.
Speaker 2: Get more drinks though, yeah, like you.
Speaker 9: So I keep picking it up and put them in
Speaker 9: the in the infrigerator, a little.
Speaker 1: Bit of everything, a little bit everything because so.
Speaker 9: Because when it does come, I'll be ready to pop
Speaker 9: them open with uh with a drop glasses see it,
Speaker 9: and we'll try to test them when it hits.
Speaker 2: I have a test on them too.
Speaker 1: We will test, we will test. Oh you did you
Speaker 1: got me a gift? When you're on your trip, un
Speaker 1: clothes and nice Oh yeah, glass, it's this interesting class
Speaker 1: that I'm going to debut on the Revolution. I'm going
Speaker 1: to use that. Great, It's gonna be great.
Speaker 2: I like my, I like my, Uh, these things, these
Speaker 2: are good. I'm I've been drinking these things. I've been
Speaker 2: collecting these things on my Revolution shows. So I can
Speaker 2: hang out this one.
Speaker 9: I could bring out a larger one, A smaller one
Speaker 9: I got.
Speaker 1: I don't know, to be careful not to have. No, No,
Speaker 1: that's too Mandy.
Speaker 2: Only two of us.
Speaker 9: Anyway, all right, but you you probably you probably won't have.
Speaker 2: You'll probably have your drink.
Speaker 9: Yeah, your your your glass, that glass you'll use that
Speaker 9: special glass.
Speaker 2: Special.
Speaker 1: It's gotta be real good for the four Local because
Speaker 1: I believe the fore Loco is red. This glass will
Speaker 1: show off the color in a unique way. I think
Speaker 1: it's red. It's some crazy bright color that's too bright
Speaker 1: to be ingesting. But I'm gonna do it anyway. That's
Speaker 1: gonna that.
Speaker 2: That would be good for that.
Speaker 9: I like these small ones because these small drop glasses
Speaker 9: for me and level and Levolution, I'll go on drinking, drinking, drinking,
Speaker 9: you know, you know how Chuck knows how I am
Speaker 9: on the Evolution days. Uh, I'm alution night because that
Speaker 9: is my shoe right out of everything, so you know,
Speaker 9: and and I'll be keep going, Oh, we have a
Speaker 9: glass here, we have a class here, ohpeaking of glasses?
Speaker 5: What about the rating for tonight? There? But what's that one?
Speaker 5: What's that one?
Speaker 2: Yeah?
Speaker 1: We do have to rate this drink.
Speaker 2: Oh yeah, I haven't done it yet.
Speaker 1: We have to do that. Let's let's turn around and
Speaker 1: do that.
Speaker 7: Yeah, because you're almost down to your last ten minutes.
Speaker 9: Already ten minutes already, Jimmy, when did you got your
Speaker 9: evolution we seven up call?
Speaker 2: I mean, yeah, Mountain dew, Mountain dew.
Speaker 7: He wants you to rate the mountain do you're drinking Jimmy?
Speaker 10: Five?
Speaker 7: There you go? Or eight out of ten.
Speaker 1: Out of five solid?
Speaker 7: Solid?
Speaker 2: Okay? What'd you got the cut? What was your drink?
Speaker 7: I'm always with the nine out of ten with the
Speaker 7: black label, Jack Daniels. So you know, like I said,
Speaker 7: I got a free bottle of that from the guys
Speaker 7: in Dallas, so I was happy. Nice size too.
Speaker 1: That's cool, that's cool, all right.
Speaker 9: Guess a guest been talked away. I'm from there on
Speaker 9: the out of the coastline.
Speaker 5: I got, I got tap water today, and it's it's
Speaker 5: probably about a seventh today. We don't we're already we
Speaker 5: already don't have any fluorided Victoria water.
Speaker 7: So Canadian I wasn't drinking Canadian tap water, no flooriyde,
Speaker 7: but still only seven out of ten. That's rough.
Speaker 5: It's city by city, city by city.
Speaker 2: Or he's trying to keep solid a sound like he kept.
Speaker 5: Those pipes pipes. These are old pipes, chucks, So there's
Speaker 5: a weird stuff in there.
Speaker 1: You know.
Speaker 7: Well sometimes old pipes are better though, I mean, you know,
Speaker 7: asking people in Flint, they would have much had their
Speaker 7: old pipes back.
Speaker 5: Was the new pipes that actually got them?
Speaker 7: Yeah, the new pipes is what went wrong?
Speaker 5: Okay, important, Maybe cheaper ones from China or.
Speaker 2: Something, some crod what do you say?
Speaker 1: TVCs too? That stuff will leads to plastics.
Speaker 5: In on you, all right, Well, probably better than lead though, Yeah,
Speaker 5: our grandchild back to the old wood ones. They actually
Speaker 5: have examples of wood pipes that uh Victoria here.
Speaker 7: That's all right, Aaron, either our grandchildren or a great
Speaker 7: grandchildren will be part plastic anyway, because it's all in
Speaker 7: the food and everything already, so screw it. You know
Speaker 7: we're all going to be part plastic eventually.
Speaker 1: That's right, that's right, it won't be synthetic anymore.
Speaker 2: Body, What do you put for this drink?
Speaker 5: Oh?
Speaker 1: Yeah, we got to rate.
Speaker 2: I'm trying to wait on my tongue and wait on.
Speaker 5: Hand of water.
Speaker 1: We have to rate on the rocks, premium cocktails, the
Speaker 1: old fashioned by not creak or that's the whiskey in it.
Speaker 1: I'm gonna give it a eight out of ten because
Speaker 1: it's a solid, good pre mixed dr Thank you. I
Speaker 1: don't have to do any work. You just pour it
Speaker 1: and it tastes quite good. Eight out of ten? What
Speaker 1: do you saying?
Speaker 3: Nine?
Speaker 2: Nine? Just short of a ten?
Speaker 5: But not?
Speaker 2: That's nine nine for me?
Speaker 5: What not?
Speaker 1: Yeah? Yeah, that's pretty good there, all right, Yes, that's
Speaker 1: a good drink. I'd say it was a good drink.
Speaker 9: I'm it, but it sure went down strong man. First
Speaker 9: drink I drank that sucking boy. I thought I was
Speaker 9: on a whiskey land. Uncle, what do you rate your
Speaker 9: new shot class?
Speaker 2: That's a ten?
Speaker 1: Like it's a ten, This is a ten ten shots.
Speaker 9: I think I'm gonna start that's a good idea.
Speaker 2: Just give me an idea.
Speaker 1: This I what's that?
Speaker 2: My drop classes?
Speaker 1: Rate the classes.
Speaker 9: I'm just realizing something I might do that I'm gonna
Speaker 9: do that. Should I got enough of them? Still collect them?
Speaker 1: Of course, not all shot glasses are created equal. That's
Speaker 1: why some of them are ten out of ten and
Speaker 1: others are not.
Speaker 2: This one is, it's neat.
Speaker 1: It's kind of great design. Great design.
Speaker 5: Uncle.
Speaker 1: Do we want to go to shout outs here?
Speaker 9: Oh? Yeah, first was Jimmy shout out there.
Speaker 2: What do you want to call for?
Speaker 10: Jimmy shout up to you guys. Let's take cause a
Speaker 10: good show. Thanks for Robin calling in. I wonder where
Speaker 10: you were, and everybody will go a week the peace.
Speaker 1: All right, take care of Jimmy man.
Speaker 2: Next one is.
Speaker 5: Loving We're we're doing good up here in Canada. And
Speaker 5: then they're just banned a whole bunch of more guns.
Speaker 5: So that's not that's not great necessarily if you're a
Speaker 5: gun guy, which I'm not, but you know, anyway, look
Speaker 5: at someone hates shout out. Uh, shout out to Mexico.
Speaker 5: You know I've been there one time for for holiday too.
Speaker 5: It was pretty fun and uh I'm surprised you didn't
Speaker 5: have any tequila down there, Uncle, next time, no mescal.
Speaker 9: But I just couldn't Actually, I couldn't get to it.
Speaker 2: Let's put it that way.
Speaker 9: It's all the excitement I was doing too excited to day,
Speaker 9: and if I was coming out with a quila, his
Speaker 9: wife would have chased me down.
Speaker 7: For that.
Speaker 2: Oh yeah, yeah, if you know.
Speaker 5: What I need that.
Speaker 1: Yeah, she would try to baptize you.
Speaker 5: It was beers only as all right.
Speaker 2: Well at the time.
Speaker 9: Yeah, so it's because I could have got any kind
Speaker 9: of diet coke.
Speaker 2: Us. It ain't like that you had to drink. But
Speaker 2: but my, but but my sister.
Speaker 9: She had her favorite that's goods.
Speaker 2: What were they?
Speaker 1: Maybe it was what was that?
Speaker 2: What was that? You like those drinks?
Speaker 1: Oh, you're talking about margarita.
Speaker 2: He went up to a little more crazy. But I said, well,
Speaker 2: into vacation. So she go ahead and do what you
Speaker 2: want to do.
Speaker 11: That's the way. So but that's much all right. So, well,
Speaker 11: are some good sister, Oh the sister, older sister.
Speaker 1: Going to tell you, Oh yeah, yeah, she lives here
Speaker 1: at the house. Yes, it's quite the situation we have
Speaker 1: here at the house. It's a good time now it was,
Speaker 1: and we were doing shout outs. So Robin, some good
Speaker 1: shout I have one. You have a shout I have
Speaker 1: the shoutouts. Okay, shout out to my oh twins out
Speaker 1: of the United States.
Speaker 9: Oh, shout out to you all, because I always want
Speaker 9: to shout out to them. Oh, my good listeners and
Speaker 9: whoever else is like comedy shows, shout out to you all.
Speaker 1: Yeah, all right, I guess I'll do a shout out.
Speaker 1: Shout out to everybody again. All my soldiers there that
Speaker 1: were fighting the war on Christmas alongside me.
Speaker 2: I salute your service.
Speaker 1: And yeah, everybody who helped me make that ADDT video
Speaker 1: who starred in it with me, people, my old crazy buddies.
Speaker 1: Good times. It's good times and nothing but good memories there.
Speaker 1: And if anybody enjoyed that stream again, you can go
Speaker 1: back and watch it. And there's gonna be more crazy
Speaker 1: live streams here in the future. Uncle. In fact, there's
Speaker 1: an upcoming holiday special. We have the revolutions to mark
Speaker 1: the calendars. I'll just remind people, Chuck, do you want
Speaker 1: to give a shout out? Yeah, you can give a shout.
Speaker 2: Yeah.
Speaker 7: I just wanted to note because Uncle always likes to
Speaker 7: hear this. We got multiple listeners in Canada tonight, and
Speaker 7: of course that one great hanging listener in Germany. Uh,
Speaker 7: and one in the UK. So there's our international listeners
Speaker 7: for tonight, along with all you guys from across the
Speaker 7: United States. So I wanted to shout out to them.
Speaker 7: And uh, and that's about it, man, Thank.
Speaker 1: You awesome, well, thank you. Shout out to you for
Speaker 1: being a great producer. Yeah, yea, I have a good production.
Speaker 1: Yeah and uh oh uncle, good news. I see at
Speaker 1: the start of the show the livestream video wasn't going
Speaker 1: through the YouTube, but we are now. I'm not sure
Speaker 1: what happened, but it's it's working, So we're okay.
Speaker 2: Are they not charging us?
Speaker 3: Uh?
Speaker 2: We're even having the charge with these people.
Speaker 9: You know what I'm talking about. You said know about no,
Speaker 9: not money, the charge the.
Speaker 2: Film stream people.
Speaker 1: I don't want to have Oh my shut we're not
Speaker 1: having copyright.
Speaker 7: Oh he's working at copyright. I don't want to hear
Speaker 7: them copy don't.
Speaker 1: Have any copywriters here. No, luckly, thank god, nobody needs that.
Speaker 7: I can do that anyway, unless yeah, unless you start
Speaker 7: singing happy birthday, will be all right? Okay, don't worry
Speaker 7: about it.
Speaker 2: Happy Happy Birthday is copyrten.
Speaker 7: It's copywritten. I swear, yes, they I can't believe.
Speaker 9: Birthday even if a person's birthday is a day.
Speaker 2: Yes, birthday is a.
Speaker 1: Copy somebody, somebody, somebody has to get paid.
Speaker 7: If you sing happy Birthday on a video, somebody has
Speaker 7: to get paid. That's the truth.
Speaker 2: I never heard that, never heard. No, I'm be doing
Speaker 2: a lot of things about this stuff lately.
Speaker 1: It's more egregious perhaps than making money.
Speaker 9: I think it's more greedy, true story, look it up.
Speaker 7: I mean, the guy's got to be dead, like a
Speaker 7: hundred years ago at least. Who wrote that song? Right?
Speaker 7: But that's why you know when you go to these restaurants,
Speaker 7: they start clapping Happy birthday, clap clap clapping because they
Speaker 7: can't do the regular song unless they those people. That's
Speaker 7: the thing.
Speaker 2: I didn't know that they do that. Why am I
Speaker 2: knowing everything and I didn't know? On my show, God,
Speaker 2: what a podcast is for is changing.
Speaker 9: He's telling us pretty good, because he's doing good of
Speaker 9: telling me these things to understand what I'm trying to
Speaker 9: understand exactly.
Speaker 1: Uncle Will.
Speaker 7: So we're all together trying to figure out the world, uncle,
Speaker 7: And if I can help you a little and you
Speaker 7: can help me a little, then it's all good, and
Speaker 7: we can all understand the world around us.
Speaker 2: Right, That's what I've gotten to good, I'm getting.
Speaker 1: To yep, exactly Podcast Ethos.
Speaker 2: There was three hundred and fifty three episode by by people. Okay,
Speaker 2: see you next week.