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Speaker 4: The information economy has a ride. The world is teeming
Speaker 4: with innovation as new business models reinvent every industry industry.
Speaker 4: Inside an Analysis is your source of information and insight
Speaker 4: about how to make the most of this exciting new era.
Speaker 4: Learn more at inside analysis dot com, insideanalysis dot com
Speaker 4: and now Here's your host, Eric Kavanaugh.
Speaker 5: All right, ladies and gentlemen, Hello and welcome back once
Speaker 5: again to the only coast to coast radio show all
Speaker 5: about the information economy. It's Inside Analysis, yours truly, Eric
Speaker 5: Kavanaugh is here with the legendary entrepreneur, the man about
Speaker 5: i'd say, the man of my Townity's the man about
Speaker 5: the world. He's all over the place Shanghai, Malaysia doing
Speaker 5: amazing things in the world of modern technology. We have
Speaker 5: Alvin fu his latest Gig zero two launch is about
Speaker 5: three years old now, and he knows a lot about bitcoin,
Speaker 5: knows a lot about enterprise technology and really global market trends.
Speaker 5: And Alvin, I'll just throw it over to you first.
Speaker 5: We are living in fascinating times right now. And when
Speaker 5: I look at these foundational models that are coming out,
Speaker 5: what I find so fascinating is that they are, in
Speaker 5: many senses a reflection of human knowledge. It's like a
Speaker 5: dynamic encyclopedia Britannic. I think gets things wrong. Sometimes they're
Speaker 5: still hallucinating a bit, and we're all working on that.
Speaker 5: We're working on the ground truth. But you just suddenly
Speaker 5: have at your fingertips outrageous amounts of information which can
Speaker 5: be shared and articulated in perfectly syntactically correct sentences. That's
Speaker 5: a really big deal. What are your thoughts, having been
Speaker 5: in the industry for a couple decades now or more,
Speaker 5: what are your thoughts about this inflection point we're facing
Speaker 5: right now?
Speaker 6: Well, Eric, thanks, thanks again for inviting me to your show. Well,
Speaker 6: we are living in an exciting time. You know something
Speaker 6: that never I mean, I mean we grew up. I
Speaker 6: think we probably grew up almost at the same time,
Speaker 6: the same era where we saw, you know, everything that
Speaker 6: was analog, right, you mentioned encyclopedia, You know things that
Speaker 6: that I think kids of today don't even know what
Speaker 6: what in the world encyclopedia because now get access to
Speaker 6: the internet. And now of course you know AIHL g BT.
Speaker 6: You know, the way is rapidly moving towards an era
Speaker 6: where nobody can comprehend and the speech will only.
Speaker 2: Get faster and faster.
Speaker 6: And AI I think it's going to be the tool
Speaker 6: or the single single because you know, to me is
Speaker 6: the biggest denominator that's going to disrupt every single business
Speaker 6: in every category, every industry, and possibly our.
Speaker 2: Lives as well.
Speaker 6: So we are we are definitely living in exciting times,
Speaker 6: and I think it's just going to get much faster
Speaker 6: and we just have to accept and I always coined
Speaker 6: this this this term. You know, we live in an
Speaker 6: era where we need to learn very quickly. We also
Speaker 6: need to unlearn what we are learned very quickly so
Speaker 6: that we can relearn new things, because I think that
Speaker 6: is the only way to stay relevant or staying ahead
Speaker 6: of the game.
Speaker 5: That's a brilliant Yeah, that's a really good point. We
Speaker 5: have to unlearn to relearn. It kind of reminds me
Speaker 5: of one of the challenges with these models. So Watson Acts,
Speaker 5: i'm told, was designed originally such that you could pull
Speaker 5: out a data set and then retrain the model. And
Speaker 5: I'm sure they did that because they realized we might
Speaker 5: load something in and then realize, oh, we shouldn't have
Speaker 5: done that take it back out. Well, most of these
Speaker 5: other models are not built like that, and once you
Speaker 5: train a model on something, it's very hard to untrain it.
Speaker 5: And the example I give is like raising kids. If
Speaker 5: you curse in front of your two year old, don't
Speaker 5: be surprised if you curses back, because that's now in
Speaker 5: her model, right, So it's hard to you can try,
Speaker 5: like with your rag model, you can try now, don't
Speaker 5: curse the only daddy can say that word. You know,
Speaker 5: good luck with that one, right, What do you think
Speaker 5: about that?
Speaker 2: All? Right? I mean it's easier said than done. I
Speaker 2: mean learning, I think is given.
Speaker 6: Everyone learns something, right, to unlearn what they've learned, that's.
Speaker 2: Difficult, right.
Speaker 6: And if you look at you know, these days, when
Speaker 6: you talk about you know, maybe maybe twenty years ago,
Speaker 6: when you tell people that you have got like twenty
Speaker 6: three years of work experience, that means a lot, right,
Speaker 6: That's that's valuable, right, But twenty years to thirty years
Speaker 6: of work experience in today's world, that's a lot.
Speaker 2: That's that's not that's not going to be helpful.
Speaker 6: And because you're going to come with legacy, right, lots
Speaker 6: of baggages and and it's difficult to learn something new
Speaker 6: and let's not even talk about learning something new. To
Speaker 6: unlearn what you've learned for the last twenty three years difficult.
Speaker 6: So that's why a lot of companies, when you look
Speaker 6: at how they're moving forward, you know, what they've been
Speaker 6: organized to achieve past success, right, is probably going to
Speaker 6: make you know, probably going to be very difficult for
Speaker 6: them to to move forward because of the legacy, right,
Speaker 6: because it's very hard for a company that has been
Speaker 6: around for for fifty years, one hundred years, right to unlearn,
Speaker 6: to uncheck themselves right and reorganize them again in a
Speaker 6: way that is totally not what they're used to.
Speaker 2: So unlearning is actually a lot lot harder.
Speaker 6: Relearning is, probably, but you need to unlearn first before
Speaker 6: you can relearn. So again, in that, in that, in that,
Speaker 6: in that context, while it all seems easy, it's.
Speaker 2: Not not so simple after all.
Speaker 6: But so this is something I practice all the time,
Speaker 6: and and I'm not so young, but but I've learned
Speaker 6: how to, you know, sometimes dump out.
Speaker 2: All the all the all the all the legacy and.
Speaker 6: Trying to keep an open mind. Now, keeping an open
Speaker 6: mind is is also easier said and done. Now, well
Speaker 6: what you want to keep an open mind, but you're
Speaker 6: still structure within a framework. Right. So so that's why
Speaker 6: I'm and I always talk about when people always say
Speaker 6: let's think out of the box, right, But the trove
Speaker 6: is that it's very difficult because if you're getting the
Speaker 6: same people who have been in the same industry for
Speaker 6: twenty thirty years and asking him to think out of
Speaker 6: the box is almost next to impossible. The only way
Speaker 6: to think out of the box right is to get
Speaker 6: someone not from the same industry right to look in
Speaker 6: and figure out how to think out of that industry.
Speaker 5: Mm hmmm, So someone like gohead, go ahead, No. I
Speaker 5: was going to say, you bring up a lot of
Speaker 5: really really good points here, and from an organizational perspective,
Speaker 5: I think you're going to need a lot of introspection
Speaker 5: and then some extro spection, I suppose, and as you suggest,
Speaker 5: get someone to come in from outside the organization and
Speaker 5: just look at your plan, look at your vision.
Speaker 3: You know.
Speaker 5: I have a really good friend who is a developer.
Speaker 5: He's been doing this stuff for twenty odd years in
Speaker 5: the valley in San Francisco, and he has a really
Speaker 5: interesting mantra where he says, busy is the enemy of
Speaker 5: creative And what he means is, if you're just constantly
Speaker 5: behind the eight ball, if you're constantly trudging away, trudging away,
Speaker 5: you're not thinking of creative answers. And especially in the
Speaker 5: coding world and the information architecture world, there are no
Speaker 5: limits to how you can design something these days. And
Speaker 5: I think a lot of people who don't know code
Speaker 5: don't realize how constrictive it is in terms of how
Speaker 5: you have to write things. You have different ways, different architectures,
Speaker 5: calling you, of course, modular architectures, you have monolithic. You
Speaker 5: now have all these distributed systems like Kubernetes. My point
Speaker 5: is that there are countless ways to reinvent how you're
Speaker 5: doing things, but it does require that sort of shedding
Speaker 5: of the old mindsets. And that's what you're talking about,
Speaker 5: right It's being able to really thoughtfully discard the structures
Speaker 5: of your thinking to adopt a new way of living
Speaker 5: and doing.
Speaker 6: What do you think, well, I I can, I can resonate.
Speaker 6: I mean, the thing is that now I work with developers,
Speaker 6: I'm not a coder.
Speaker 2: I'm bye bye.
Speaker 6: By practice, I'm I'm supposed to be practicing law. I
Speaker 6: actually graduated with a law degree some thirty years ago.
Speaker 6: Uh and and my first job was I actually started
Speaker 6: off in an advertising industry, so nothing to do with
Speaker 6: technology and nothing to do with whatever that I'm doing
Speaker 6: right now. So it has gone through an evolution that
Speaker 6: I got into internet and gradually understand networking and then
Speaker 6: understand one point oh two point zero and subsequently I'm
Speaker 6: just trying to understand and and you know, you know,
Speaker 6: have a much better grap than Web three point zero.
Speaker 2: So the entire evolution.
Speaker 6: Has taken, you know, some twenty five years or more,
Speaker 6: right to learn and learn and also relearn and and
Speaker 6: when I work with my my coders, now, my coders
Speaker 6: are so bake into the way of working, right. Therefore,
Speaker 6: whatever they think about is always you know, the practicality
Speaker 6: and and how you code. But when you when I,
Speaker 6: when I work with them, I I don't think so
Speaker 6: much of coding. I think of user experience, you know. Uh,
Speaker 6: I think more in terms of the practicality.
Speaker 2: And the the the.
Speaker 6: Application and how that how would that then adapt and
Speaker 6: adapt to the to the real world.
Speaker 3: Right.
Speaker 6: So so that's why when you when we look for
Speaker 6: people within the team, we want to find a good combination,
Speaker 6: a combination of someone who can quote very well and
Speaker 6: also very receptive because the probably the problems a lot
Speaker 6: of coders is that they're also receptive, and they always
Speaker 6: stuck right stuck within the idea the square. And then
Speaker 6: the thinking is that they always start then and not
Speaker 6: willing to move beyond. So we need to find a
Speaker 6: good combination. You know coders, we are you know CEO
Speaker 6: who are very open minded. And then we're got you know,
Speaker 6: product persons who understand products very well and use experience
Speaker 6: and the customers, so that that's a good combination. If
Speaker 6: you look at most successful set up, they are made
Speaker 6: up of combination of people who are really good in
Speaker 6: their own domain and who are very very receptive because
Speaker 6: in today's role, right, it's all about understanding your customer.
Speaker 6: If you understand them and being able to execute right
Speaker 6: according to what they need, right, and that makes the
Speaker 6: product very successful. And that's lacking in a lot of
Speaker 6: companies because you know, some of them are just good engineers,
Speaker 6: they're good programmers and that's all about it. But to
Speaker 6: understand the customer and take it to market sometimes lacking.
Speaker 5: Right.
Speaker 2: So so again, when.
Speaker 6: You want to find a team, right, you need to
Speaker 6: find a team that are able to do what I've
Speaker 6: just said. But if you look at most organizations I'm
Speaker 6: talking about multinationals, the companies that has been around for
Speaker 6: a long time, the combination that actually missing and most
Speaker 6: of the time being led by people who have been
Speaker 6: in the industry right for several years. And if even
Speaker 6: if they will find replacement for the CEO or CFO.
Speaker 6: Usually they will also they will they will end up
Speaker 6: finding the old gods from another company, a similar company,
Speaker 6: to run the company because it's safe to do so, right,
Speaker 6: Because if you find someone who is.
Speaker 2: New, right, that's taking a lot of risks right.
Speaker 6: For a new startup, it's a lot easier because there's
Speaker 6: no legacy, there's no historical so basically you're starting from
Speaker 6: ground zero. But when you are taking on a mountinnational,
Speaker 6: there are a lot of boundaries that you need to work
Speaker 6: with and then you answer about to your shareholders, your
Speaker 6: board of directors and so forth.
Speaker 2: So it's very difficult. So that's not what you're seeing
Speaker 2: right now.
Speaker 6: We have seen over the last twenty years their disruption
Speaker 6: in several sector industry.
Speaker 2: And many big companies.
Speaker 6: There was one once very big are no longer around
Speaker 6: like companies that called that companies like no Care. And
Speaker 6: now now what is impacting is in what we're seeing
Speaker 6: very clearly is.
Speaker 2: In the auto industry.
Speaker 6: When you look what you're seeing right now, the evs
Speaker 6: from China are now disrupting right the global auto industry
Speaker 6: because the auto industry, which has been so structure and
Speaker 6: organized right to a very well structured supply chain for
Speaker 6: the last god knows how many years, right, are now
Speaker 6: facing disruption caused by companies new EV company that build.
Speaker 2: Cars entirely on their own.
Speaker 6: They design and manufacture a car entirely by themselves in
Speaker 6: the shortest time. If you look at most companies a
Speaker 6: design car, it takes seven years, right, at least seven
Speaker 6: to ten years to come up with one new model. Now,
Speaker 6: the company in China, a company called bid As, I'm
Speaker 6: sure you must have heard, one of the largest EV companies.
Speaker 2: They can come.
Speaker 6: Up with a new model almost every month, right now,
Speaker 6: that's scary, right. So so the Chinese, the Chinese manufacturing
Speaker 6: right has I mean what whatever I always say is
Speaker 6: right Now, anything that that that that it has a
Speaker 6: linkage to electronics, right, whether that's a smartphone or the
Speaker 6: fan that you're using at home, the air conditioning system, whatever,
Speaker 6: that is being powered by electric.
Speaker 2: The Chinese are really good at it.
Speaker 3: Right.
Speaker 6: Years before EVE came about, the Chinese had a hard
Speaker 6: time catching up because it was it was based on
Speaker 6: a very old technology called engine, the combustion engine. Today, right,
Speaker 6: it is being built empowered by batteries, So that's electric again.
Speaker 6: So the electrification of auto, of the auto industry, right
Speaker 6: provides a new entire paradigm shift for the manufacturing the
Speaker 6: auto manufacturing industry in China. And suddenly, right they have
Speaker 6: gone from nowhere and became the largest EV manufacturers in
Speaker 6: the world. Right, So they've disrupted many many industry right
Speaker 6: and and the auto industry is the next one to
Speaker 6: be hit now.
Speaker 2: So so when you look.
Speaker 6: At when you look at a lot of these companies,
Speaker 6: I mean I had the opportunity to speak to some
Speaker 6: of them, some of the CEO that I know personally,
Speaker 6: uh and and most of them started the company almost nothing,
Speaker 6: literally almost nothing, with a couple of people.
Speaker 2: And all they had was a dream that they want
Speaker 2: to build a car.
Speaker 6: Right And and when you look at them, right, they've
Speaker 6: got a lot there have almost no legacy, and all
Speaker 6: they all they know, right is that it's huge market.
Speaker 2: Out there is how how do I come up with
Speaker 2: a car?
Speaker 6: And the shortest sign and the competition in China is
Speaker 6: that they are over one hundred and sixty five EV
Speaker 6: manufacturers only it's crazy and and most of them are
Speaker 6: not making money. Most of them are not making money.
Speaker 6: They're all funded now of course when when when the
Speaker 6: funding stops, like the music stops, right, So so at
Speaker 6: some point they will there's going to be I mean,
Speaker 6: as of now, there are they are already already some
Speaker 6: have already applied for bankruptcy early, right, And I'm sure
Speaker 6: along the way you see more and more ev companies
Speaker 6: in China are going bus and I think that's where
Speaker 6: the consolidation will come in. And of course there's the
Speaker 6: more solid company, the companies at bid. You know, they
Speaker 6: will continue to be, you know, a key player in
Speaker 6: the global market.
Speaker 2: And and and that's a competition.
Speaker 6: Competition is in China on any sector super competitive, super
Speaker 6: super competitive.
Speaker 5: Well, I mean China basically went hyper capitalist, you could argue, right,
Speaker 5: I mean you went from this an older system, a
Speaker 5: more traditional system of governance and societal developments and dynamics
Speaker 5: to this hyper capitalist environment right now. And that's why
Speaker 5: the economy is.
Speaker 2: Doing so well.
Speaker 5: I mean, capital breeds excellence. Competition breeds excellence. And when
Speaker 5: you do it, when you don't have competition, that's when
Speaker 5: things slow down and you do not get a lot
Speaker 5: of innovation. I mean you see this in organizations too,
Speaker 5: Like the more competition a certain company has the harder
Speaker 5: they have to fight to get their market share, right,
Speaker 5: real quick, we got one minute in the segway, go ahead.
Speaker 6: Right, I mean it is it is, it is what
Speaker 6: it is. I mean the you know, innovation in China
Speaker 6: is given. It's not like innovation has to be something
Speaker 6: that we that that people are being taught what innovations
Speaker 6: is given and and and the only way to fight
Speaker 6: competition in China is innovation, no other way. And that's
Speaker 6: why when you look at all the all the auto manufacturers,
Speaker 6: in all the cars that's been designed, right, every single
Speaker 6: one of them will come up with you know, very
Speaker 6: gimmicky features and so forth, right, just to.
Speaker 2: Out compete each other.
Speaker 6: And and and then you multiply that with one hundred
Speaker 6: and sixty five manufacturers.
Speaker 2: It's painful.
Speaker 6: And that so so so I mean short, right, that
Speaker 6: has caused a whole disruption to the auto industry, pushing
Speaker 6: out the Japanese brands. Right, Some of the Japanese brands
Speaker 6: are exiting the market already, some of the some of
Speaker 6: the American many manufacturers like GM are closing closing down
Speaker 6: factories now they're all getting hit and German brands like
Speaker 6: the Mercedes and BMW are also getting hit as well,
Speaker 6: and it's painful because China is a market that car
Speaker 6: manufacturers cannot afford to lose.
Speaker 2: It's like, it is the largest auto.
Speaker 6: Market in the world, right and it's a market that
Speaker 6: it cannot afford because there's no way that you can
Speaker 6: replace that lost revenue. And this is exactly what's happening
Speaker 6: in China right now in the auto sector.
Speaker 5: That's crazy. Well, folks, don't touch it. Dow Or will
Speaker 5: be right back with the legendary Alvin Fou. You're listening
Speaker 5: to Inside Analysis.
Speaker 4: Welcome back to Inside Analysis. Here's your host, Eric Tavanaugh.
Speaker 5: All right, folks, back here on Inside Analysis talking to
Speaker 5: Alvin fu your host here, Eric Kavanaugh. We're talking all
Speaker 5: about innovation and how China has one hundred and sixty
Speaker 5: five manufacturing companies for cars. I mean, that's just crazy.
Speaker 5: Here in America they talk about the Big Three and
Speaker 5: even they're having trouble and they've been subsidized and given
Speaker 5: all sorts of money. And you know, I drove a
Speaker 5: maz to me out of myself two thousand and one,
Speaker 5: a six speed. It's a beautiful car. I don't think
Speaker 5: there'll ever be another car as beautiful as my car.
Speaker 5: To be honest with that, I'm selfish. But Alvin, you
Speaker 5: are a lawyer by trade. You studied law and I
Speaker 5: just gave a keynote this morning where I basically said,
Speaker 5: in the not too distant future, and this mayread be
Speaker 5: happening somewhere around the world, you, as a plaintiff, are
Speaker 5: you going to have the option to go with an
Speaker 5: AI judge and jury or a real judge and jury.
Speaker 5: And if you do the AI judge and jury, You're
Speaker 5: just gonna load your lawsuits. You're gonna load all your evidence.
Speaker 5: You're going to talk to a camera for an hour
Speaker 5: or two and answer questions. The defendant's going to do
Speaker 5: the same thing. And once all that information is in there,
Speaker 5: the engine's going to open, read through it and say
Speaker 5: we find in favor of the plaintiff. Here's what you
Speaker 5: have to do. I think that's going to happen. And
Speaker 5: think about this, because you can, even with the ability
Speaker 5: to model these days, you could even you talk about
Speaker 5: a jury of your peers, you could scrape data from Facebook,
Speaker 5: from Instagram, from other social platforms, and a particular geography
Speaker 5: and then create jurors based upon the personalities in that geography.
Speaker 5: Then you could even have a random jury selection. You
Speaker 5: can do the whole thing through AI. And you look
Speaker 5: at the legal world today, well, what is law really
Speaker 5: boiled down to? It boils down to the practice, the rules,
Speaker 5: and what you can do at certain points in time.
Speaker 5: Emotion to dismiss, for example, is something you can do well.
Speaker 5: Right now, You've got to pay people a lot of
Speaker 5: money to do all that stuff, and they have to
Speaker 5: know how to do it. Then you have to get
Speaker 5: them to do it. I've had only one experience with
Speaker 5: a lawyer in my life, but he was very lazy.
Speaker 5: I mean, we we worked out, everything worked out fine,
Speaker 5: but he was very lazy and he just didn't really care.
Speaker 5: And that's when I learned, Oh man, when you hire
Speaker 5: a lawyer, make sure you get one who's going to
Speaker 5: actually work for you and care about your case, because
Speaker 5: even that's difficult. But what do you think about this
Speaker 5: prediction that AI is going to revolutionize juris jurisprudence.
Speaker 6: Well, I think AI it's not just going to replace,
Speaker 6: you know, the current you know, legal system, the potentially
Speaker 6: is going to also revolutionary the healthcare industry and so
Speaker 6: many other industry right now, now, going back to what
Speaker 6: you have just said, I do believe, I do believe
Speaker 6: in a very very near future you're going to have
Speaker 6: a situation where you know, it's going to be an
Speaker 6: AI judge, it's going to be an AI lawyer. I
Speaker 6: mean it, it's doable because you can, you know, machine
Speaker 6: train them, you can and and they can continue learning,
Speaker 6: right and you and and the thing is that now
Speaker 6: they can do they can work twenty four hours a day, right,
Speaker 6: human human cannot work any four hours a day. And
Speaker 6: they will know everything. The judges and the lawyers will
Speaker 6: know you know some of this stuff well, but not everything.
Speaker 6: But your AI just will know everything every single sat
Speaker 6: statutory law, all the all the proceedings and so forth.
Speaker 2: Right, So so.
Speaker 6: He's going to be a much more knowledgeable, knowledgeable lawyer now.
Speaker 6: But but but having said that, right, there's one part
Speaker 6: of the legalism, the law that requires you know, some
Speaker 6: some some deep you know, some critical thinking, especially into
Speaker 6: the facts of the case. Now on the law you
Speaker 6: can change, but the facts of a case right, sometimes
Speaker 6: can be very subjective. I think this is where uh,
Speaker 6: I'm not saying human will play better at all, but
Speaker 6: suddenly human can think better well right now, as far
Speaker 6: as far as the next you know, five ten years,
Speaker 6: right until really it comes to day where you know,
Speaker 6: a g I is is you know, becomes a reality
Speaker 6: where where you can't even out compete or are you
Speaker 6: an out talk and in AI, I think that's where
Speaker 6: a g I comes in, right.
Speaker 2: But I think in a short period of time you're
Speaker 2: going to get.
Speaker 6: AI lawyers, a I a I judges, but they are
Speaker 6: they're just going to play They're going to play a
Speaker 6: very element elementary role of a judge. Right, So basically
Speaker 6: very simple cases, right, very straightforward cases.
Speaker 2: Right.
Speaker 6: I think for for cases that require that s more,
Speaker 6: there's there's more that requires you know, critical thinking and
Speaker 6: for for or even on a few cases right that
Speaker 6: you probably need, right, a human judge.
Speaker 2: Right. I don't think this would this would they would
Speaker 2: be replaced.
Speaker 6: In in the far in in the future, but at
Speaker 6: least I think the magistrate court, you know, the very
Speaker 6: low low, low level judges or likely be replaced by AI,
Speaker 6: including very low level lawyers as well.
Speaker 2: Yeah, I think similarly, yeah.
Speaker 6: Similarly, similarly to the healthcare and medical medicare, where the
Speaker 6: GPS are going to be replaced right, right, what's going
Speaker 6: to be left by the specially because what people want
Speaker 6: to talk to, they want to talk to specialists, they
Speaker 6: want to talk to experts, right, But AI can do
Speaker 6: that that that that's very straightforward jobs.
Speaker 2: So I think that's where that's.
Speaker 6: Where AI is going to play a huge role in
Speaker 6: replacing very general roles, even for lawyers and doctors.
Speaker 2: Yeah.
Speaker 5: Well, and I'll tell you what. One other topic I'd
Speaker 5: love to get your opinion on is transparency. So open
Speaker 5: AI originally was open and now it's a black box.
Speaker 5: So I joke they should change their name to close
Speaker 5: the AI because they're not open anymore. But there is
Speaker 5: this all mode that just came out which is true
Speaker 5: open and they even give you access to the training data.
Speaker 5: And from my mind, I believe transparency will be crucial
Speaker 5: for auditability and for fairness with these models, because if
Speaker 5: they're not transparent, if they are a true black box,
Speaker 5: then there's no real way to audit them and the
Speaker 5: truth be told, the complexity of these things is so
Speaker 5: tremendous that even if it's completely open source, it's still
Speaker 5: not like the average person could come along and understand
Speaker 5: what the heck it's doing. These are very very very
Speaker 5: complex systems, and they're all different. Now, I try to
Speaker 5: explain that there is no limit to the number of
Speaker 5: ways you can set up a deep learning module, how
Speaker 5: you define the parameters, how many parameters you have, how
Speaker 5: many inference layers you have. You could even make them dynamics.
Speaker 5: So there's really there's no limit to how complex they
Speaker 5: can be. Not the complexity necessarily equals better value or
Speaker 5: better efficiency, because it doesn't. That's why I think these
Speaker 5: small language models are going to become fairly prevalent. But
Speaker 5: what do you think about transparency in code and architecture?
Speaker 5: I know that goes against the grain of traditional capitalists
Speaker 5: thinking with intellectual property, but let's face it, these models
Speaker 5: have kind of they've absorbed all this intellectual property and
Speaker 5: then now they have it trained in their systems. So
Speaker 5: it's like, is I P even a thing anymore? What
Speaker 5: do you think about about legislation to mandate that AI
Speaker 5: models be transparent in their code and in their training data.
Speaker 6: I think I think the the regulation around this area
Speaker 6: is coming uh and and I think we need regulation
Speaker 6: around it because if not right, then how how do
Speaker 6: you define transparent?
Speaker 3: Right?
Speaker 6: So what what what is transparency? And how much is
Speaker 6: being transparent right?
Speaker 5: Right?
Speaker 2: And and the.
Speaker 6: Models that you just talk about what what what what
Speaker 6: can be defined as a good model, And that's that's
Speaker 6: the same problem that was saying that if you want
Speaker 6: to build an AI model, then you've got to make
Speaker 6: sure that whatever that you input into the model is
Speaker 6: making sure there's a.
Speaker 2: Lot of truth to it, right, because it's all about
Speaker 2: truth right, right.
Speaker 6: And and if if you only if you only teach
Speaker 6: or input models and data that you want it to
Speaker 6: model that way, then it becomes biased.
Speaker 2: Right.
Speaker 6: Now, imagine if if the lawyers are being the AI
Speaker 6: lawyers or AI doctors are they are being skewed towards
Speaker 6: the pharmaceutical industry, just like how the pharmacies the farmer
Speaker 6: the farmer companies are lobbing the government. Can you imagine
Speaker 6: right that the AI doctors or AI lawyers are being
Speaker 6: skilled biased, right, and that that will.
Speaker 2: Not work for all of us? Right? So so what
Speaker 2: you what you teach the model? Right?
Speaker 6: I think that needs to be that needs to be
Speaker 6: defined right now, there's no there's no regulation and also
Speaker 6: because it's is we're moving so fast, right and and
Speaker 6: as I'm sure you know, regulation always play catch up role. Right,
Speaker 6: Just like how it's playing a catch up role into
Speaker 6: digital asset, it's also playing a catch up role to AI,
Speaker 6: and everyone's trying to learn and as much as we
Speaker 6: we we are trying to understand it's better, you know,
Speaker 6: the the transparency, privacy, cybersecurity and so forth. There's so
Speaker 6: many areas and even copyrights when we look when we
Speaker 6: look at generative AI, every single image that's being generated
Speaker 6: on generative AI.
Speaker 2: Is a copy of something.
Speaker 6: Else, right, right, and usually uh, that's something else being optimized.
Speaker 2: But you know true AI, right.
Speaker 6: So what what levels of of of of optimization right
Speaker 6: then you need to do before it becomes a new
Speaker 6: a new image or a new copyrighted material.
Speaker 2: So right now nobody, nobody has a definition.
Speaker 6: So so basically what we are all doing is copying
Speaker 6: each other, right and it could be an image of
Speaker 6: a cartoon on the Disney or that could be a
Speaker 6: copyright of Marvel and whatever that may be. So so
Speaker 6: we all are taking these images, right and then you know,
Speaker 6: repurpose them.
Speaker 2: But what about copyright?
Speaker 6: So so I think regulations will catch up, and we
Speaker 6: need one because if we don't have one, right, then
Speaker 6: which standard and which center are we following right? And
Speaker 6: what is right to you may not be right to
Speaker 6: to me, or what's right to one one country may
Speaker 6: not be right to another. So I think I think
Speaker 6: they need to put this in place so at least
Speaker 6: there's a more defined role and as to how you
Speaker 6: train your model and what's what's transparency.
Speaker 5: Right, Yeah, I think that then all the right it's
Speaker 5: just up for grabs. I mean, if there's no if
Speaker 5: there are no rules, you know, or if there and
Speaker 5: here's the other side of the equation, you know. I've
Speaker 5: got a very colorful history. And for a couple of
Speaker 5: years I worked for a rush and I often do
Speaker 5: my Russian inmitation. They worked for Alexandri Khananik and we
Speaker 5: kid the post Rasha and he was Boris Yeltsin's financier.
Speaker 5: And he tells me stories that basically way back in
Speaker 5: the day, in what the nineteen eighties, nineteen nineties, basically
Speaker 5: he said, from his perspective, and he became a multimillionaire
Speaker 5: by the age of twenty four or twenty five because
Speaker 5: he got into the construction business and he did commodities
Speaker 5: trading at the very beginning of the internet. So if
Speaker 5: you can see that lumber is one rouble of pound
Speaker 5: over here in ten over there well by Sell, and
Speaker 5: he did that before and he had a first mover
Speaker 5: advantage basically. But one thing he told me I thought
Speaker 5: that was very interesting was that the system back then
Speaker 5: in Russia was set up so that you could not
Speaker 5: not steal. That's how he described it. But you weren't
Speaker 5: supposed to steal from you weren't spposed to steal more
Speaker 5: than your boss, right, Like the senior director can steal
Speaker 5: a lot, the manager can steal a little bit the
Speaker 5: new guy, but it not steal very much. And this
Speaker 5: is this is what he tells me, right. And then
Speaker 5: what I picked up on which I thought was very interesting,
Speaker 5: was that the laws were so complex. And this goes
Speaker 5: I'll tell you what. This goes back to laut Su,
Speaker 5: because I love Chinese philosophy. Laut Su said three thousand
Speaker 5: years ago, when the laws are complex, the bandits will abound.
Speaker 5: And his point was that bad guys love very complicated
Speaker 5: law because they can navigate it. If they can understand it,
Speaker 5: they can take advantage of it. And I think that
Speaker 5: getting back to this AI overthrow that I'm talking about,
Speaker 5: when you see this permeate the legal industry, healthcare industry,
Speaker 5: financial services, et cetera. It's good for the bad guys,
Speaker 5: but it's hopefully good for the good guys. And I
Speaker 5: think we can start to unwind some of that stuff
Speaker 5: because from a prosecutorial perspective, if everyone's breaking the law
Speaker 5: all the time, then you can be very selective on
Speaker 5: who you prosecute, and that is a bastardization of the
Speaker 5: law and the whole point of having laws. Right, So,
Speaker 5: what do you think about that in general? Because I
Speaker 5: think that we have to get back to basics. And
Speaker 5: you know, I'll give you one last fun quote when
Speaker 5: I describe this to my business partner, doctor Robyn Bloer,
Speaker 5: who is a very very intelligent guy, a British man.
Speaker 5: I explained it two years ago. He goes, do you
Speaker 5: know how many rules Napoleon had? I was like, no,
Speaker 5: He said seven, And he was talking about going back
Speaker 5: to basis, going back to first principles. And I think
Speaker 5: we kind of need that because it's like things have
Speaker 5: gotten so complex now from many different perspectives that we
Speaker 5: have to distill in order to be able to govern
Speaker 5: effectively in the future. We're going to have to distill
Speaker 5: down to core values and rethink all these processes for
Speaker 5: how we do things.
Speaker 7: But what do you think, right, Well, if you if
Speaker 7: you look at most most profession, right, whether that's going
Speaker 7: to be the medical profession, the financial industry, or even laws,
Speaker 7: it's actually quite complex.
Speaker 6: And I think they are complex for reasons. They are
Speaker 6: complex because then everyone has a job, right, everyone gets
Speaker 6: to keep your job right. And if you look at
Speaker 6: the financial sector, it's so so complex to the point
Speaker 6: that that the regular guy on the street right will
Speaker 6: not understand that they need a wealth advisor, that they
Speaker 6: need that they need someone to advise them what to
Speaker 6: do right.
Speaker 2: And that's why there's a lot of roles and jobs around. Right.
Speaker 2: So when you look at when you look at you're
Speaker 2: talking about laws.
Speaker 6: Now, I think in especially technology, uh, you need a framework,
Speaker 6: you need regulation, But at the same time, you need
Speaker 6: a very balanced framework because if the regulation comes in
Speaker 6: and it is complex and how to understand, how to apply,
Speaker 6: or or it becomes so strict that that you then
Speaker 6: then there's no innovation, right because now people have to
Speaker 6: start to think, right now, I can't do this, I
Speaker 6: can't do that, and then I need this license I
Speaker 6: need that license or the cost of even operating it
Speaker 6: becomes very high. Then then instead of you pushing innovation,
Speaker 6: you not having no innovation. So I think they need
Speaker 6: to be a very balanced framework. And I think that's
Speaker 6: that's difficult. Right, So where do you again, when you
Speaker 6: go back to transparency, right, so how do I Where
Speaker 6: do I draw that line? I think that's that's something
Speaker 6: a lot of regulators are having a lot of difficulty,
Speaker 6: and that applies the digital assets. Same thing when I
Speaker 6: look at a lot of new regulations that's been designed,
Speaker 6: especially especially tech related.
Speaker 2: Right, the problem is is where do you draw that line?
Speaker 3: Yeah?
Speaker 5: Yeah, let's pick this up after the break. That's a
Speaker 5: very very good question. Where do you draw the line?
Speaker 5: And how malleable should that line be? When do you
Speaker 5: redraw the line? We'll pick this up right after the break.
Speaker 6: Don't touch.
Speaker 5: I tell you're listening to the Inside Analysis.
Speaker 4: Welcome back to Inside Analysis. Here's your host, Eric Tabanac.
Speaker 5: All right, folks, back here on Inside Analysis with the
Speaker 5: legendary Alpha and Food dialing in from the other side
Speaker 5: of the planet. So thanks for staying up late here
Speaker 5: on my time, and Alvin, I want to ask you
Speaker 5: a question because we're asking these deep, thoughtful questions about
Speaker 5: where do you draw the line with regulations, with innovation,
Speaker 5: with transparency, what are the rules by which we must live?
Speaker 5: Because and if there are too many rules, there are
Speaker 5: no rules. I guess that's the argument I was making
Speaker 5: in the last segment. If there are too many rules
Speaker 5: and they're not comprehensible, then there may as well be
Speaker 5: no rules. And also, if you don't understand a rule,
Speaker 5: there's no way that you can consciously adhere to it
Speaker 5: because you don't understand it. And I think some of
Speaker 5: these laws they've come up with, you're like, what on
Speaker 5: earth is this saying? But I will say that these
Speaker 5: beautiful language models are so good at summarization. You can
Speaker 5: take highly complex, draconian language, throw it into a model
Speaker 5: and say what does this mean. It's going to do
Speaker 5: a pretty good job to tell you. But in terms
Speaker 5: of things like copyright and ownership and really understanding providence,
Speaker 5: I think that's a very fascinating use case for blockchain
Speaker 5: because it is immutable. Of course, bitcoin sits on top
Speaker 5: of blockchains, and there's all these complex ways of mining
Speaker 5: for the coins and trading the coins and consensus and
Speaker 5: then we can get all into that stuff. But the
Speaker 5: thing I find interesting is using blockchain as a system
Speaker 5: of record to know who owned what and when. So
Speaker 5: you think about deeds, you think about property, for example,
Speaker 5: and who owned which property? Right now, it's a fairly
Speaker 5: convoluted process that has lots of different players. The title
Speaker 5: company for example, has to come in, the bank, the owner,
Speaker 5: the county recorder of deeds. All these people do stuff,
Speaker 5: and they're bad guys who come in and manipulate that
Speaker 5: system too. But when I think about the future in
Speaker 5: like copyright for example, or whose idea was this, who
Speaker 5: took that photo? I think we can use blockchain as
Speaker 5: a foundational layer to record who did what and when,
Speaker 5: and that's going to be very valuable in the future.
Speaker 2: But what do you think, Well, that's that's the power blockchain.
Speaker 6: I mean, that's that's that's what we are all trying
Speaker 6: espressly the web tree, right, trying to promote decentralization, you know,
Speaker 6: the blockchain. You talk about the benefits of it, right,
Speaker 6: I think that there's a lot of I think every
Speaker 6: sector uh is going to be impacted, right or it's
Speaker 6: going to benefit right from the adoption of blockchain, right,
Speaker 6: you're going to see not just not just you know
Speaker 6: we're talking about copyright, right, it could be supply chain
Speaker 6: where the supplies are coming from.
Speaker 2: Right, it could be music.
Speaker 6: Right, uh, copyright music, copyright movies, or even togonization Like
Speaker 6: togalization is actually a very big sector because a lot
Speaker 6: of things today that we we we have to be
Speaker 6: all physical, right, the physical asset. Imagine being able to
Speaker 6: take all the physical asset in the world, right, all
Speaker 6: the real asset could that that could be properties, you know, companies, equities,
Speaker 6: goal and so forth, and you tognize them and and
Speaker 6: having tokenized them knowingly that you can keep a record
Speaker 6: of all these assets. At the same time you're able
Speaker 6: to trun for the asset seems right anyway, cross border
Speaker 6: right right. So plus, I mean it's a it's it's
Speaker 6: mind blowing and and and that's that's the reason why
Speaker 6: I have I've gone into blockchain some some eight years ago.
Speaker 2: When I when I when I took a.
Speaker 6: Look at the power of what you could do and
Speaker 6: the potential that we can impact business in the future.
Speaker 2: I just I just think that there is massive.
Speaker 5: Yeah, I think you're right, and you so like in
Speaker 5: the risk management world, in the financial services world, clearing
Speaker 5: houses things of this nature. To your point, if you
Speaker 5: have a sophisticated blockchain system underneath a lot of that
Speaker 5: stuff becomes very easy. You could transfer the assets, move
Speaker 5: them all around, and have a record and immutable record.
Speaker 5: I remember Madge, I think the guy's name was, who
Speaker 5: for a short period of time was the see I
Speaker 5: think the CFL maybe for Twitter, and he's the guy
Speaker 5: who testified before Congress, and that from what he had learned,
Speaker 5: any number of developers at Twitter had root level access
Speaker 5: and you could go in and change something. You could
Speaker 5: change data like a in a thread for example, and
Speaker 5: then there's no log file, or you could actually delete
Speaker 5: the log file. And I've heard of that in some
Speaker 5: other instances too, and it's like, well, that's not immutable.
Speaker 5: It's the point is like, that's mutable. Like if you
Speaker 5: can go in and delete the log file and that
Speaker 5: you know, you change something, that's no bueno. Right, That's
Speaker 5: not good, Which is why I think we need some
Speaker 5: level of blockchain to underpin these systems. Right, to have
Speaker 5: the true system of record that keeps check of everything
Speaker 5: that happened, so you can undwind anything. You can run
Speaker 5: an AUDITAI, you could do impact analysis all that kind
Speaker 5: of stuff. That again is another power of blockchain. What
Speaker 5: do you think I mean.
Speaker 6: Government should love this, right, imagine a wall way, imagine
Speaker 6: all the all the invoicing, right, all the revenue big
Speaker 6: capture on the blockchain.
Speaker 2: Right.
Speaker 6: So if you if you capture all the accounting on
Speaker 6: the blockchain, you don't need to do audit anymore because
Speaker 6: it will self audit on his own.
Speaker 2: That's right, right, that's right and right.
Speaker 6: And not only did he sell audit on his own
Speaker 6: automatically the.
Speaker 2: Taxes, yeah right, this is the thing.
Speaker 5: Right, So it's like you look at tax preparation. I
Speaker 5: remember I was, I got QuickBooks, and I'm sitting there
Speaker 5: and banging through all this quickbook stuff and I'm trying
Speaker 5: to do my taxes for corporate taxes, and I realized,
Speaker 5: you know, this should not be that difficult. And you
Speaker 5: see it now in QuickBooks where they you start typing
Speaker 5: in a company name and go, oh is it this company.
Speaker 2: With this address?
Speaker 5: Like, oh, yeah, actually it is. Well, a restaurant obviously
Speaker 5: sells food. An accounting firm does accounting. You can tell
Speaker 5: by the registration of the companies what they do, and
Speaker 5: that should be also very good for auditing and for
Speaker 5: automating the process of doing your taxes, like this is
Speaker 5: a hard cost for my big business. Take it off
Speaker 5: the bottom, take off the top line. Like, so, I
Speaker 5: think we are getting close to that. But to your point,
Speaker 5: there are a lot of people try to stop that
Speaker 5: from happening because their jobs are going to go away.
Speaker 2: What do you think, Well, well, definitely, definitely.
Speaker 6: This is this is a point that I always said, right,
Speaker 6: technology is a man to make our lives easier, right,
Speaker 6: And and if you don't, if you don't reskill yourself,
Speaker 6: or if you don't relearn something new, right, then you're
Speaker 6: going to have no job period, right right, right right,
Speaker 6: And and there's no no way that you can stop technology,
Speaker 6: no way, right. Blocking will come AI will come up
Speaker 6: to your job, uh and and they will come a
Speaker 6: day where everything is going to be, you know, very
Speaker 6: crackable because now not only that it's crackable, it's also.
Speaker 2: Immutable, right, so every record is being kept.
Speaker 6: So imagine a world where if everything is being tracked
Speaker 6: on the blockchain, there's no money laundering, right exactly where
Speaker 6: all the moneys are being found? Where where are the
Speaker 6: transaction taking place where what time and and and everything
Speaker 6: is trackable and that that day will come, and that
Speaker 6: day will come. Now, of course there's going to be
Speaker 6: a lot of resistance, right, just like you know how
Speaker 6: people are resisting e V, how people once resisted the internet,
Speaker 6: and and I mean it's it's it's common, right and
Speaker 6: now uh, you know you've got people who's also resisting AI. Now, yeah,
Speaker 6: it's going to come after your job, regard like it
Speaker 6: or not, right, you know, they will come at a
Speaker 6: time where many people are going to lose their job,
Speaker 6: and and many jobs have already been replaced, especially in
Speaker 6: the financial sector. Imagine all the analysis that that was
Speaker 6: done by an analyst.
Speaker 2: AI can do that that's right, right, right.
Speaker 6: And and anything that that can can be written, you know,
Speaker 6: the books done by copywriter journalism. Yeah, I can do
Speaker 6: a much faster job. I remember I was just telling
Speaker 6: my friends. You know, in good old days, I need
Speaker 6: like at least you know, a day or two to
Speaker 6: prepare a PowerPoint for presentation.
Speaker 2: Right these days, I can do like twenty in a day. Yeah.
Speaker 6: So if you if you know how to harness you know, technology,
Speaker 6: it can really benefit you and increase your productive productivity
Speaker 6: by by leaps and bound really. But at the same time,
Speaker 6: if you if you if you sit and do nothing,
Speaker 6: it will work against you.
Speaker 5: Yeah.
Speaker 2: It similarly like any other technology.
Speaker 6: I mean, And to me, I I don't have a
Speaker 6: specifically love from any technology because to.
Speaker 2: Me, it's a tool.
Speaker 6: It's a tool to get humanity to the next level.
Speaker 6: And you know, and not only that, it gets the
Speaker 6: next level. So so the next level would mean how
Speaker 6: how that technology and enhance our line and so that
Speaker 6: we can go on and do things that we love
Speaker 6: and leaving those mundane jobs right to the AI to
Speaker 6: do it right, like how it aim takes over the
Speaker 6: job of a judge, right of a low entry lawyer.
Speaker 6: I mean, I think a lot of easy job AI
Speaker 6: will do a much better job.
Speaker 5: Yeah, I think you're right about that. And it does
Speaker 5: the tedious stuff. To your point, you don't No one
Speaker 5: wants to do tedious work. No one wants to pour
Speaker 5: over ten thousand documents to find the seventeen that are
Speaker 5: missing a particular field. And that's something that AI and
Speaker 5: automation can do in seconds, just scan through, Oh these
Speaker 5: are the seventeen. You know, it's going to be very
Speaker 5: good for pointing out what else needs to be done.
Speaker 5: It'll find things. Now Again, these models, depending upon the models,
Speaker 5: they are not perfect and they probably never will be perfect,
Speaker 5: nor will human beings. Human beings aren't going to be perfect.
Speaker 5: But I will say that at least in the old
Speaker 5: days of database technology ACID transactions, as we talk about,
Speaker 5: they were designed to deliver what is in that information
Speaker 5: system or that system of record. So AI is not
Speaker 5: going to take over everything, but it is going to
Speaker 5: be an augmentation an analysis tool, and an automation tool
Speaker 5: and a quality assurance tool. I mean, that's that's kind
Speaker 5: of what some of these other folks are focused on now.
Speaker 5: On the far end of an output from an LM
Speaker 5: is some kind of a QA process. But folks don't
Speaker 5: touch out to podcast ponus segment is coming up next
Speaker 5: on Inside Analysis. All right, folks are back here on
Speaker 5: Inside Analysis. You're truly Eric Kavanaugh with the legendary Alvin Fou.
Speaker 5: We're talking all things AI and crypto and blockchain and
Speaker 5: what's coming, what's happening. And I just shared with him
Speaker 5: my thoughts on the death of journalism and my speech
Speaker 5: at the Javit Center earlier this year where I ask people,
Speaker 5: do you know where inflation came from? No one had
Speaker 5: any idea. I showed them a chart where you see
Speaker 5: the price of gas on average in America went from
Speaker 5: under two dollars to over five dollars inside like a
Speaker 5: year and four or five months, which is a shocking
Speaker 5: spike in price. Well, of course that affects everything. Is
Speaker 5: everything has to be shipped around, food products, whatever, is
Speaker 5: a factor. But more than anything, it's monetary policy. And
Speaker 5: when you just go and print money, which is what
Speaker 5: you do with THEAC currency, this is print money. Every
Speaker 5: time you print a dollar, the value of every other
Speaker 5: dollar goes down a little teeny tiny bit. And if
Speaker 5: you print freaking five to ten trillion dollars in a
Speaker 5: short period of time, that's what's going to cause inflation.
Speaker 5: And Alvin, what really pissed me off, to be honest,
Speaker 5: was that the storyline here in America and the American
Speaker 5: media back when this was happening was, oh, inflation is global.
Speaker 5: They kept saying that inflation is global, implying that it's
Speaker 5: not our fault. I'm like, well, you're right, it is global.
Speaker 5: That's a true statement, but it doesn't nullify my statement,
Speaker 5: which is that the printing of money caused the inflation.
Speaker 5: So we did cause inflation, and that hit everybody in
Speaker 5: the world. I was in Belgium in I guess it
Speaker 5: was what it was like two and a half years
Speaker 5: ago maybe, and the cab driver was telling us that
Speaker 5: the elderly people in Belgium, many of them don't even
Speaker 5: drive any they don't go anywhere. They're stuck in their
Speaker 5: homes because they're unfixed income and they can't afford the
Speaker 5: petrol to even go visit their child two hours away
Speaker 5: by car. So this affected everybody. It's not a story
Speaker 5: that the media talks about, which I find bizarre. I
Speaker 5: think it's political, to be honest. But what do you
Speaker 5: think about this, and what do you think about how
Speaker 5: how does that map to blockchains meteoric rise, Because of
Speaker 5: course blockchain is not fiat currency. It does have a
Speaker 5: specific set amount of coins to be mined and as such,
Speaker 5: and I believe it was designed as a hedge for
Speaker 5: fiat currency. That's my theory. And if you look back
Speaker 5: and see when the paper was written and when all
Speaker 5: that stuff happened, well guess what it was like back
Speaker 5: in two thousand and seven eight timeframe. So it was
Speaker 5: either remarkably precient or at least coincidentally timed with this
Speaker 5: collapse of our or near collapse of our financial system.
Speaker 5: But what do you think about all that?
Speaker 6: I think the man, the person who wrote this right
Speaker 6: certainly was impacted by the event, right uh and and
Speaker 6: and because of this event that has impacted him, that
Speaker 6: he lost trust in this in this centralized system. That
Speaker 6: that pushed him right to rewrite the whole concept of bitcoin,
Speaker 6: which is it lives, it lives.
Speaker 2: In the decentralies.
Speaker 6: Well right, Uh, it's defictionary with twenty one million bitcoin
Speaker 6: that's going to be emitted, you know up until it's
Speaker 6: still about maybe a hundred years from now, But every
Speaker 6: four years it's going to half, right, So it's going
Speaker 6: to be less and lesser and less, a big cooin
Speaker 6: along the way. So that's why the concept of bitcoin
Speaker 6: has always been a hedge over year, right, right, Because one,
Speaker 6: on the one hand, you get you get the fats
Speaker 6: who are constantly printing more money I think right now
Speaker 6: is about a trillion dollars every hundred days, right, uh,
Speaker 6: and and and you and you have bitcoin that's deflationary,
Speaker 6: and there's going to be less and lesson bitcoin. And
Speaker 6: that's why you have companies at MicroStrategy accumulating lots of bitcoin.
Speaker 2: And not only my strategy is doing that.
Speaker 6: There are lots of companies UH in Corporate America and
Speaker 6: also now companies in Japan and Singapore and even China
Speaker 6: right acquiring uh a bitcoin and and putting that on
Speaker 6: the balance. Now, if you believe that, that's why it's heading,
Speaker 6: you know, And and I don't think the money supply,
Speaker 6: the money printing will stop ever. So I don't think
Speaker 6: because because unless if they can game change their current
Speaker 6: deficit massively, right, the current interest repayment alone is more
Speaker 6: than a trillion dollars, right, is bigger than the entire
Speaker 6: you know, the annual defense budget of the US. That's
Speaker 6: just interest repayment. So unless I'm drastic, is changed on
Speaker 6: the deficit, you're going to end up keep keeping you know,
Speaker 6: you're you're going to end up printing more money.
Speaker 2: And I think bitcoin is the answer.
Speaker 6: Bit Bitcoin is a solution right to the FIAT prom
Speaker 6: in in the US. And I think that's the that's
Speaker 6: that's probably the only way that I can see. And
Speaker 6: I think my I think Mike Sailor has coined up.
Speaker 6: You know, I'm not going to go to Mike Casaida.
Speaker 6: I think a lot of people must have read about him.
Speaker 6: I think the idea behind it being a digital capital,
Speaker 6: a digital goal as as as as a hedging and
Speaker 6: at the same time, right for potentially using bitcoin that
Speaker 6: to repay the the United States.
Speaker 2: You know that that's been there has been.
Speaker 6: Yeah, I think right now it's like thirty six strellion dollars.
Speaker 6: And if you at the at the trajectory that bitcoin
Speaker 6: is going in value at some point, I think, you know,
Speaker 6: you you could probably use bitcoin right as a payback
Speaker 6: to your debts. And that's that's potentially. That's that's that's
Speaker 6: put that's quite potentially if you look at the jectory
Speaker 6: of what's the value of bitcoin is going to be
Speaker 6: in twenty one years from now where you know, Michael said,
Speaker 6: the sale already even at base right, they have got
Speaker 6: three model, the base model, the bowl case, and also
Speaker 6: the bad case.
Speaker 2: Even for the bad cases about four million dollars.
Speaker 6: Right, the base case is like thirteen million dollars and
Speaker 6: the bowl case is forty nine million dollars.
Speaker 2: So if you multiply the.
Speaker 6: Bitcoin reserve, that trumpet has been has been promoting, right,
Speaker 6: you know, trying that the miss is also trying to
Speaker 6: push through Congress.
Speaker 2: Right, that's going to be like what.
Speaker 6: One million of bitcoin in the next five years, So
Speaker 6: trying to acquire two thousands of bitcoins annually.
Speaker 2: I mean that's doable, right.
Speaker 6: I Mean my thinking is that if America could print money,
Speaker 6: why not print more money and buy more bitcoin? Right?
Speaker 5: That's crazy, right? So wild?
Speaker 2: Yeah?
Speaker 6: And I mean if I can print money out of Tina,
Speaker 6: I would print more money out of Tina and then
Speaker 6: buy more bitcoin.
Speaker 2: Right? Why would I? Right?
Speaker 6: Why why am I printing money and and then giving
Speaker 6: giving to countries you know with lost costs?
Speaker 3: Right?
Speaker 2: I'm not going to name all those countries.
Speaker 6: I mean, I don't want to get too political, but
Speaker 6: the fact is that if they can print more money,
Speaker 6: they should print more money and buy bitcoin and a
Speaker 6: bigcoin you know, price continues to increase. Right, then what's
Speaker 6: what's the problem with printing more money?
Speaker 3: Yeah?
Speaker 2: Right?
Speaker 5: Well, and you know, speaking of money printing, and I'll
Speaker 5: just kind of close on this. I saw this story
Speaker 5: yesterday Javier Malay down in Argentina with his chainsaw and
Speaker 5: all this crazy stuff.
Speaker 2: He was saying.
Speaker 5: He was going to cut government spending and bring down inflation.
Speaker 5: And apparently Argentina now has a surplus. The government has
Speaker 5: a surplus in their budget for the first time and
Speaker 5: one and twenty three years, I mean, wowsers. So we
Speaker 5: are very inn l Salvador too, I think the president
Speaker 5: of El Salvador also invested heavily in bitcoin and of
Speaker 5: course was ridiculed. Well, it's like, geez, he's looking pretty
Speaker 5: good now, rightly, Christmas.
Speaker 2: This is a huge bel.
Speaker 6: Ye, I mean El Salvadore bitcoin holding is now at
Speaker 6: least you know, six hundred million dollars over six hundred million.
Speaker 2: Dollars, right and yet debt crazy.
Speaker 6: Yeah, that that death is about eighty million dollars to IMS,
Speaker 6: so she could easily pay back already. So so there's
Speaker 6: not a non issue, I think at the end of
Speaker 6: the day, right for corporate America, for America, I think
Speaker 6: the way to solve this long term problem bitcoin reserve
Speaker 6: is certainly one one solution, and al Salvado has proven
Speaker 6: that and putting the right leaders around the country like
Speaker 6: Argentina has also proven that.
Speaker 2: So so maybe Trump, as.
Speaker 6: Much as a lot of people may not agree or
Speaker 6: may not like him, but The fact is, I think
Speaker 6: if there's one person who can fix that problem, I
Speaker 6: think I think Trump and his and his team which
Speaker 6: included Elon Mass and I'll just right they they are
Speaker 6: in a position to solve this problem.
Speaker 5: Yeah, I love it. What a great way to end
Speaker 5: the show. Alvin Food. Look this gentleman up online LinkedIn.
Speaker 5: He's got a huge following, something like four hundred thousand followers,
Speaker 5: always sharing excellent fun content, very insightful, very incisive. Loved
Speaker 5: Have you on the show. Look him up, folks, We'll
Speaker 5: talk to you next time. Send me an email info
Speaker 5: at inside analysis dot com if you want to be
Speaker 5: in the show. We'll talk to you next time. You've
Speaker 5: been listening to Inside Analysis.
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Speaker 14: NBC News Radio. I'm Lisa Carton. A holiday season government
Speaker 14: shutdown has been averted. The House passed a stopgap measure Friday,
Speaker 14: with the Senate following suit, passing the bipartisan funding bill
Speaker 14: by a vote of eighty five to eleven. Senate Majority
Speaker 14: Leader Chuck Schumer praised the development.
Speaker 6: There will be no government shutdown right before Christmas. This
Speaker 6: is a good bill.
Speaker 2: It'll keep the government open.
Speaker 14: This capta chaotic week that saw President Electromp and Elong
Speaker 14: Musk cast doubt on whether an agreement could be reached.
Speaker 14: President Biden signed the measure on Saturday. President Electromp says
Speaker 14: the US may take back the Panama Canal. Speaking today
Speaker 14: at the Turning Point USA's America Fest in Arizona, Trump
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Speaker 14: Panama ridiculous and highly unfair. Lisa Carton NBC News Radio