AI Cannot Be Slowed Down – With Ramy Taraboulsi And Kirk Spano

Summary:

• An erudite and thoughtful conversation about AI with Ramy Taraboulsi, CFA and Kirk Spano.
• Neural networks, hype and building something we don’t understand.
• Major problem with AI is lack of computing power. What stocks make sense?
• Lockheed Martin’s quiet AI work; bearish on Google.

Listen to the podcast above or on the go via Apple Podcasts or Spotify.

• 3:00 – Singularity – the interconnection between 3 key areas of tech: nanotechnology, genetics and artificial intelligence
• 7:10 – AI won’t be slowed – military investing more than any company
• 13:30 – Neural networks, AI hype and building something we don’t understand
• 28:20 – Major problem with AI is lack of computing power. What stocks make sense?
• 50:25 – Lockheed Martin’s (NYSE:LMT) quiet AI work; Ramy bearish on Google (NASDAQ:GOOG).

Recorded on June 1, 2023

Check out Kirk Spano’s Investing Group, Margin of Safety Investing

Follow Ramy Taraboulsi, CFA

Transcript

Kirk Spano: Hello. I’m Kirk Spano with Seeking Alpha. And today, I am interviewing Ramy Taraboulsi, who wrote an article recently, describing how the singularity, the merger of humanity with machines and artificial intelligence, and all the consequences, benefits, all the negatives that could come from that.

It was maybe my favorite article that I’ve read this year on Seeking Alpha. So I do recommend that everybody read this article, take all the links that are in it and go and visit some of the links, and really consider where we are in history and whether or not it’s accelerating as fast as Ramy suggests that it is.

Ramy, how are you doing today?

Ramy Taraboulsi: I’m doing perfectly fine, Kirk. Thank you for inviting me to that conversation. I really appreciate that. I am currently in Hyderabad, India. So – and I’m originally residing in Toronto, Canada, but I’m on a trip to Hyderabad right now. So interesting how the technology right now has taken us. You’re currently in the United States and I’m in Hyderabad, India, and we’re talking to each other as if we are next door to each other practically.

KS: I ran a string across the ocean. So, we could talk. Yes, it is kind of amazing. I remember early in my career talking to people in Europe or Southeast Asia or India or wherever we are talking and the telephone connection would crackle or we’d have that split second echo where we had like pause to hear what was coming back over and it’s pretty amazing to me that this is so easy right now. As I told you off air and we’ll get back into this conversation.

Way back in the early 90s, when I was finishing up college, I wrote a paper about, maybe I’ll get to see all of the things that are happening now in my lifetime. I drew heavily from Lewis Thomas who had written about genetics way back in the 1970s and I read your article and it just brought a lot of that back. Why don’t we get started here and just describe in your own words and thoughts, what is the singularity?

RT: If you ask 10 different people what is singularity is, most likely you’ll get eight different answers, most likely.

KS: That’s better than asking 10 economists, because then you’d get 12 answers.

RT: Yes, I guess so. I guess so. If you look at what Ray Kurzweil has said, the singularity is basically the interconnection between three key areas of technology, which are nanotechnology, genetics and artificial intelligence. When these three areas reach a certain point where they can interact with each other and produce a particular entity that is superior to the human being, we’ll get what we call the artificial super-intelligence or artificial general intelligence, where a machine is capable of doing things that the human can do.

And when we reach that level generically, you’ll find out at that point that we don’t know what will happen. Why did we call it singularity, because it comes originally from the concept of a black hole. All the mathematical rules, all the physics rules fail at the point of the singularity which is in the center of the black hole. After you pass the event horizon, how do things operate? Some physicists think that they have some theories, but these theories the mathematics behind it fails.

What will happen at the singularity when we have these three areas of technology merging together? That’s what people don’t know. And that’s why we called it a singularity, because we don’t know what will happen in there. And whatever we’re saying, the only thing I can tell you is that it might be correct, it might not be correct. And whoever says that they know what will happen, they don’t know. So did I give you an answer to that one?

KS: Yes, I think that everybody has ideas about what happens. And my name is Kirk. Yes, it’s not taken from Star Trek, but I became a huge Star Trek fan. And if you’ve watched all the shows and all the movies from Star Trek, they explore this idea a number of times. And we see the negative things that could happen, the Borg, the Borg try to create the singularity the way that they want to and it becomes oppressive.

You have other societies, maybe the Vulcans, who are looking for it and it ends up lacking emotion. And then there’s other incarnations and ultimately you have the Utopian one, where we could put it altogether well and it allows us to advance humanity without sacrificing the things that make us human. I’m optimistic that we can pull that off over a few generations. However, my fear and I tell my subscribers and clients this all the time, my fear is that we blow it up in the meantime, and kind of thinking Planet of the Apes, right?

I cite science fiction all the time, because science fiction, Jules Verne, Carl Sagan, you go back and you’ll take a look at some of the things that have been in science fiction, decades and decades ahead of reality and a lot of it comes true. So, we have control over this at this point. How do we get to a place that’s better and not worse?

RT: That’s a very difficult proposition, how to get to a place that’s better and not worse. There’s a big potential that we can reach a Utopian state like you’re suggesting and that’s my big hope. We can do that. Some people are suggesting that we have to slow the AI down. We cannot do that. We cannot slow it down. When you think…

KS: Why can’t we?

RT: The reason for that is that, there’s a huge race that’s happening right now. From my perspective, I see many companies that are advancing in AI. Think about NVIDIA (NASDAQ:NVDA), for example, it’s doing lots of things on AI, OpenAI, Microsoft (NASDAQ:MSFT), and so on. I think personally that the investments of these companies in AI build compared to the investment of the military around the world in AI.

I want you to think about something. The United States, for example. It has a budget of around $800 billion for its military, which is as much as a 10 next countries combined.

KS: Right.

RT: But the number of soldiers in the United States has been dropping by around 5% over the last 10 years every year, year-over-year dropping by around 5%, and the budget is going up. So is it the soldiers that are making more money, or they’re investing in something that we don’t know? I just wanted to go to Lockheed Martin Company (LMT), for example, which is one of the biggest contractors and look at their motto. Their motto and their case theme for what they’re doing, they’re trying to automate everything.

And how will they automate it? They’ll automate with AI. So the military is spending huge amounts of money, and I don’t think that the military will be in a position to stop its progress of fear of other militaries doing that. So, I don’t think that stopping it will be a possibility anytime soon, primarily because of this. Yes, you can stop the companies, but you cannot stop the military.

KS: Right. Well, and Eisenhower warned us about this in his farewell speech when he said beware and be careful of the military industrial complex. And while we certainly want a military and to feel safe, at what point does the military make us less safe? You know, that’s something explored in fiction all the time, right? The military…

RT: It is, it is.

KS: …takes an idea that could be good and they turn it into war. Is there a spiral that we could, I mean, that’s the thing I worry about, right? I just said that a minute ago. I do worry that we have that spiral. What do you think we can do to prevent that?

RT: Well, think about the following. Let’s go back to the human beings from basics. You take one person on their own, how much can they progress? Very limited. You take a computer on its own, how much can it progress? Very limited. There is something called APIs, which is a way for computers to communicate with each other. I don’t think that we can stop the program of AI in general. But what we can do, we can impose certain controls for how the computers communicate with each other. That’s one thing that we can do.

And if we impose such a control on how the computers communicate with each other, we can control the amazing, incredible speed by which AI is progressing. It’s progressing faster than anyone can manage right now. And the only way that I personally think that we can control it is through controlling the way that computers communicate with each other. How can we control this item? But I don’t see that we can stop people from creating new neural networks or stopping the research on that particular area, that’s not possible. Can we impose control on the communication on the APIs?

I think that it’s more feasible to do something like this? How to do it? I don’t know. Some technical experts might be in a better position to do something like this or maybe we need a brainstorming session to discuss how we can control the APIs between computers that are AI-driven. I think that this is the only way that I can think of the way we can control it.

And actually, you’ll be surprised, Kirk, but I have not heard anyone talking about that as a prospect of controlling AI. Have you heard of that before?

KS: I’ve heard the discussions, particularly I’ve been paying attention to Europe because I think that they usually are pretty close to a good idea and almost everything when it comes to kind of social aspects of regulation. I don’t know that I’ve heard that controlling the way that they communicate through the APIs, but I have – heard of controlling the dataset. So, if you control the dataset, you can teach the AI in a better way.

One of the things that I’ve worried about is the AIs that are out there and the data that they’re scraping from the Internet, some of that data is just factually wrong, which lends itself to the hallucinations that AI has. And that’s a – I don’t know if everybody knows that term, but AI hallucinates, because it gets bad data and it doesn’t know what to do with it and it spits out a bad answer.

RT: Yes.

KS: To give an example, I play in the World Series of Poker and I’m actually going to be leaving in a couple of days. And I asked ChatGPT a bunch of statistical questions, and I knew the answers going in. Unless I phrased the question just right with the right amount of detail, it gave me like six wrong answers in a row. And it became a challenge for me to ask the question in a way that it could access the correct data to give me the right answer. And it just kept spitting out bad answers until I kept amending the question, which I’ve learned in life.

I think the hardest thing to do, when you’re trying to figure something out is ask the right questions, so you get the relevant answers. So I’d be curious, if the regulatory bodies can get ahead of this, which is almost never the case, they’re almost always behind. And they’re behind on cryptocurrency, they’re behind on – they’re probably behind on technology issues from 20 years ago. Certainly, I think they’re struggling with the issues of genetics. I wonder what will they do with Neuralink when Neuralink works, because it’s going to eventually?

RT: But I hope it works. I hope it works. The first thing that they are targeting right now is spinal cord injuries.

KS: Right.

RT: And if it works, it will be a huge blessing. That’s an example of how AI can actually help us.

KS: Right.

RT: With Neuralink, for example, they put the implant in your brain through Bluetooth, it will communicate to a computer or a phone. And this phone will be adjust – connected to a motor or some sort of electrochemical signal that will send signals to your muscles that your muscles can move. And that will be trained through the AI.

KS: Right.

RT: So something like this can solve one of the biggest problems, which is spinal cord injuries, which we cannot solve medically right now. So, I hope it will work. But at the same time, we’re talking here about receiving data from the brain. What about and putting data into the brain?

KS: There you go, that’s where I was going to go.

RT: You can get data. If you can get data, why not put data in?

KS: Right.

RT: And if you put data in the brain, how can you control that? Will we get to the point where we have telepathy among the people? Possibly, that’s a positive part or maybe another part will be that someone will be controlling another person through these implant?

KS: Make somebody pick up a tool?

RT: For example, it’s a little bit farfetched, but that’s a possibility. Fast enough, it will be a possibility. Like Elon Musk said once, he mentioned – well, he was talking about something else. But just imagine 45 years ago, the first computer game that ever came was Pong. Remember that game.

KS: Yes, all right. Thank you for that?

RT: 45 year ago, that’s 45 years ago – see how much it progressed to the games that we have right now. Just imagine another 40 years or another 45 years where would we be?

KS: Right.

RT: From Pong to where we are right now.

KS: Right.

RT: From where we are right now another 45 years? And imagine the progress that we had over the 45 years mostly happened over the last five to 10 years, that’s it. The curve went up like this, exponentially, in terms of the progress.

KS: Right.

RT: And this exponential growth is not expected to abate by any means. The difference in what we’re experiencing right now compared to other industrial revolutions is that the other industrial revolutions, the machines were not improving themselves. They required us who are limited to improve the machines. Right now, you can have a neural network that creates another neural network.

KS: Right.

RT: A neural network, creating it up effectively, it is becoming a species right now. Because the definition of species is that it can procreate and its procreation is the same image. A neural network is creating another neural network in its same image. That’s a species that we have right now, at least following the definition of the species. So what will happen after that? Kirk, your question is not easy to answer.

KS: What, the women in my life have always told me that I’m simple?

RT: And I’m sure that they know better than me.

KS: So there’s a lot to unpack there. One of my first mentors on technical trading and quantitative trading was a guy named Murray Ruggiero. And he was a legitimate rocket scientist who decided to start building neural networks, I believe in the 1990s for the financial industry. And I learned a lot from him. I have a very intermittent contact, so I say mentor, it’s very loose. But I learned a lot from him early in my career. I was lucky to get introduced to him in the early 2000s and then I worked with another entity, another financial outfit that we bumped into each other in like 2016 or something.

And I bumped into him again out in New York at a traders conference. Those neural networks, building them seems like rocket science to everybody, right? But once it’s done and the AI learns how to do it, now all of a sudden, I think it becomes a question of making sure that the AI doesn’t create something evil for lack of a better word, right, and keeps it in its lane. Most AIs are task-driven, correct? They’re not the super-intelligence. So, we’re still a level away…

RT: We’re not there yet.

KS: …from Skype app and things like that. So where do you think we are and I’ll frame this with a conversation I’ve had with my subscribers probably 50 times now. When I went to CES, Consumer Electronics Show in 2020, a lot of the things that are just getting invested in now, the AI hype, that was a big theme three years ago and now it’s an investment.

What is the evolution and the speed that you’re seeing to go from the generative AI that we have now and how it solves various technological problems like with energy control, controlling the grid, things like that. How do we go from where we are now to the things that people are doubting are going to happen in the next five years with decarbonization or pick a topic to the super intelligence. Do you really think that can happen in a decade?

RT: I think it can happen in a decade, but there’s one big problem that needs to be resolved first.

KS: Okay.

RT: People need to understand how the neural network operates. If people think about neural network, what is a neural network? A neural network is simply, I’ll just talk technical a little bit right now. It’s simply an approximation of a nonlinear multivariate regression problem. It’s a regression problem.

KS: That sounds like something I got wrong in calculus.

RT: It’s statistics, yes. And most people get it wrong. It’s a nonlinear multivariate regression, the problems that if you want to solve it using the traditional methods, you don’t have enough time in the universe to solve such problems. So what do we do? We create neural network to approximate such a solution. Using something like stochastic gradient descent and backpropagation, all this crazy stuff, but it’s an approximation. The problem with this approximation is that it comes up with values to the parameters of that particular regression problem.

These parameters are basically what we call the training of a neural network. The problem that people have right now is that if a network has, let’s say, 1,000 hidden layers, which is typical for neural networks right now. People don’t understand these parameters that are out there, which could be in the tens of thousands. What each one means? So, when the neural network comes up with an answer, people don’t understand where this answer is coming from. They don’t know how the computer has come up with this answer. That’s what the problem is.

Until the scientists understand what they have created, it would be very hard to take it and further enhancing it. The only way that people are enhancing neural networks right now, which is a core of artificial intelligence and rate of artificial intelligence in general, the only way that they do it is that they do it by trial and error. They try certain things. If it works, that’s fine. If they don’t try it, they use another activation function, they use another set of parameters or neural architecture and so on. They try different things, so that they can get the proper answer that they’re expecting, based on a training set and the testing set.

People don’t understand what they have created. That’s the problem with AI right now. People don’t understand it. And the interesting thing about it, although they don’t understand it, it’s working right. It’s giving us answers that we’re expecting. We’re getting the answers for something that we do not understand. And I challenge right now any computer scientist out there who’s listening to this tell me how the parameters for the neural network are set what each parameter means.

You have the neural network for 1,000 nodes. How can you figure that out? They don’t know. No one knows. And the researchers are trying to solve that problem and they cannot solve that problem. Once that problem is solved, then we’ll have a better understanding of how to take these neural networks and drive them to something that will be beneficial for the humanity as you’re suggesting. Until then, we’re in the trial and error phase right now. That’s where we are right now.

Right now, the whole AI is trial and error, nothing else. All the research of AI is simply trial and error, and people don’t understand that. They think that the researchers out there who know what they are doing, they are not. People are just doing trial and error right now. And that is a problem because we’re building something that we don’t know.

KS: Right.

RT: We don’t understand how it works. So, can we reach the point where we can actually get to the Utopian state that you’re talking about, where it can control the grid, and make sure that it only generates enough electricity, so that the grid does not overflow and people don’t have blackouts, that’s very interesting problem. Is there a solution for it? Yes. I would say that the solution for it would be more on the quantum computing side, rather than artificial intelligence. There are other things as well that, because it requires lots of processing power and so on.

There are other things that would be more suitable to artificial intelligence, which are more on the services side. And I see that there are huge potentials in there, but I see also there are huge risks as well. So you’re hoping for the Utopian state. I’m hoping for the Utopian state. You’re more optimistic than I am, Kirk. I don’t trust the humanity that much. I don’t trust myself that much as a matter of fact.

KS: I did a podcast the other day and I just told everybody, “Hey, make me the Grand Emperor, and I’ll take care of everything for you. It’ll all work out. I’m that smart. I’m smarter than everybody else. I’m just great.” I understand – it’s like a ride. It’s like a new ride at an amusement park and it hasn’t gone through testing yet, and you’re the first one on, so…

RT: Yes.

KS: You know?

RT: That’s scary, man, that’s scary.

KS: This is going to come off the rails, but we haven’t run it yet. So yes. So when we translate this to, let’s shrink this down to a five to 10-year investment horizon. So that people can and try to look at these things in the nonlinear way and I talk about straight lines and exponential curves all the time, because on the front end of any progression, it looks like a straight line, because it’s kind of flat. And then you notice that first inflection point, like, oh, it’s kind of ramping up. And then like the AI stocks in the last month, they go straight up.

And straight up moves usually aren’t sustainable without some sort of significant snapback. So, I wonder for these companies, are they looking at such a big move in technology that they have a hard time applying it in a way that is profitable. All the trial and error ends up costing them a lot of money. And then what are the ramifications with management, right? They get pressure from shareholders. Does that create mistakes? I would be concerned about different levels of mistakes, not so much on the scientific side, because that’s really a process?

I was – I thought I was going to be a math and science major until I realized that there are people out there like Neo and the Matrix that can pull the numerical bullets out of the air and I couldn’t do that. I had to work too hard to catch up to them. So I’m probably overqualified for what I do, but I couldn’t launch a new giant rocket ship that was a mile away from getting into orbit.

So, I just wonder where do you see the hang ups on the corporate side? I think we all think about the government side and the military side for sure. But at the corporate level, where do they play a role in all of this?

RT: Well, the corporations are competing with each other, of course. We know that and this competition is brutal. And every company is trying to get and edge over the other companies. Now how will they take that particular thing that they have and materialize it into money? That’s a totally different issue and every company is totally different.

The challenge that I’m seeing right now from an investment side is that we are going through a hype state, and people do not understand what AI is. The problem that I’m seeing right now is that people really don’t understand the internals of what AI is, but they know that they are using it.

KS: Right.

RT: How can they take what they are using right now and what will happen in the future? What are the potential of habit, what will happen in the future? Now think about the following right now. How much could the computer power increase over the years? I just did some simple calculation and found out that over six years, the computer power that we have I’m talking about hardware, connectivity, disk, and so on will increase by around a quarter of a million times over six years.

KS: Wow.

RT: So, we’re having quarter of a million time improvement in the power of the computing, computing power altogether worldwide over a quarter of million years. The major bottleneck…

KS: Let me jump in and that’s probably going to accelerate with the recent quantum computer breakthroughs?

RT: Yes, that does not take into – the quantum computer into consideration. But we have to remember as well that quantum computers do not work on their own. Quantum computers is not replacement for the traditional computers.

Quantum computers gives us all the answers for a problem. And then we need the traditional computer to sift through them and get us a proper answer. So quantum computers don’t work on their own, but that’s a different problem.

The challenge that people are not realizing right now is that the major problem with AI is the lack of computing power. That because AI requires supercomputers for the training and testing of data. And so remember, it’s all based on trial and error. So it has to go through multiple iterations to get something right. And most of these iterations are not done scientifically as they are done by trial and error.

That’s the nature of AI right now until we understand exactly how the parameters of the neural networks work. And no one – I don’t expect anyone to know that anytime soon. So until then, the major bottleneck that we have is a computer power, assuming that the computer power will increase one quarter of a million times, 250,000 times over six years. Within six years from now, you mentioned 10 years, I’ll just talk about six years.

Within six years, the amount of AI networks that will be created and tested and trained and ready to go will be increasing more than you could ever, ever imagine. Yes, we might be in the hype right now. And people are saying that this hype is going to – it’s going up right now and they tell us to drop, because nothing goes up forever and we will have to drop. I see that the way the path that it has for going up is much, much more than what we are seeing right now.

We’re just seeing the edge of what it’s like. The amount of money that could be made from AI is enormous. Now will all companies succeed? No. Some of them will not, some of them will not. Which one they are? That’s a totally different issue. But some of them will succeed, for example, when we had the dotcom, people are comparing it to the dotcom. Yeah, dotcom people went up quite a lot. The problem with dotcom is that the Internet was not improving itself.

Now computers are improving themselves. AI is improving itself. That’s a fundamental difference in there. And when you think about dotcom, there are many dotcom companies that are still extremely successful. Just think about the company that ends with the dotcom right now. Very popular company, it’s called Amazon.com. The name of Amazon (AMZN) is not Amazon. The name of the company is still Amazon.com.

That’s one company that’s from a dotcom era, and it succeeded, and it thrived. I think that many companies in here will thrive quite a lot. One company that people don’t talk a lot about, one area that’s required in AI that people don’t talk about is disk. The amount of disk storage that’s required for AI is huge. The amount of data that was created over the last two years is as much as the amount of data that was created from the beginning of time until two years ago.

KS: Right.

RT: And the amount of data that will be created in the next two years will be equal to the amount of data that was created from the beginning of time until now. So the amount of disk that’s required is huge. Look at companies like Dell (NYSE:DELL) that owns EMC, a company like Oracle (NYSE:ORCL) that bought Sun and right now is one of the biggest producers of disks and databases in the world, because you need databases as well to store these data. These companies so far have not – the hype did not hit them yet.

And if you’re looking at the company that will be going up, I would look at Dell and I’d look at Oracle. These companies will be going up quite a lot, but they will not be going up exponentially like this, like we’re seeing right now with AI and Microsoft and so on. They’ll be going up gradually. But these are companies that when you put your money into them, you’re putting the money in the bank.

KS: So a Seagate (STX), maybe a Western Digital (WDC) maybe?

RT: Seagate, Western Digital, all these companies that are doing that. I’m thinking about Dell and Oracle specifically, because Oracle as well is very heavily invested in software, including Dell as well, not just the hardware manufacturer. So these two companies have invested a lot in software as well.

KS: All right. So we all saw NVIDIA (NVDA) spike up?

RT: Yes.

KS: And that makes sense the way that you just described it, because everybody’s in a race, so they need the equipment now?

RT: Correct.

KS: Six years from now, maybe NVIDIA, I mean, they’re going to have to reinvent themselves yet again at some point?

RT: Well, NVIDIA right now, the reason that they are doing it is, because remember, we need huge computing power…

KS: Right.

RT: …for the computer to be doing the training properly for the neural networks. And NVIDIA creates their GPUs.

KS: Yes.

RT: It’s called processing units, which is the primary tool that’s used, because you want to run multiple things in parallel while you’re training their artificial, the AI network. Another company that did not spike as much is AMD (NASDAQ:AMD), I don’t know why. That does not make sense to me. Because AMD, yes, it’s gone up, but did not go up as much as NVIDIA. Why? That I don’t understand. I was expecting AMD to be even going up as much if not more than NVIDIA as well because they are also, that’s a key competitor for GPUs in the world right now.

KS: Right. So do you think as these other semiconductor companies make their announcements about what they’re seeing, they could have pretty good rises as well?

RT: They would – I expect so. And I expect that AMD would be one of the top companies, although it went down today by 4%, 5%, but the whole market is down today anyway.

KS: Right.

RT: And so – but again, I would see these GPU processing companies, I think that they will be going up quite a lot. NVIDIA as well, it has an advantage that it’s heavily invested in software as well. So it’s not only hardware, they are doing a lot on the software side as well.

KS: Right, Megatron and whatnot. Do you think – do you have any special insights on Intel (NASDAQ:INTC), are they going to be a monster again?

RT: I don’t know.

KS: Okay.

RT: I just cannot tell right now. I really don’t know about the Intel. I would not invest my money into it at this point. I will hold off a little bit. If I want to invest, I’ll put my money in AMD, not Intel.

KS: Okay, all right. You almost took a Charlie Munger on that and just said it’s too hard. That’s fine. I have a little bit of money in Intel, just because they’re so cheap. And if they get their act together in the next two or three years, they should do extremely well. However, they’ve been fighting that battle a while now?

RT: Well, Intel created something that I think was brilliant at that time, which was a processor called Loihi. They created something called Loihi, which is based on neuromorphic computing. Neuromorphic computing basically right now, if you look at processors, processor have their CPU and they have their data and the RAM or the disk, they’re separated from each other. They try to create something based on their neuromorphic computing called Loihi that will combine them together, which is very much similar to what we are doing with our neural cells in our brain and what the perceptrons are doing in neural networks.

Unfortunately, right now, I think that this project has not progressed as much. I think that if Intel, focuses a lot on Loihi and the neuromorphic computing, they’ll have an advantage over all the other companies if they do it right. That’s a huge advantage that they would have. Will they be able to do it or not? I don’t know. That was something that was three, four years ago when they announced it. And since then, I’ve not been hearing anything about Loihi and the neuromorphic computing that they’re doing. I think that will be, if you see a big announcement about neuromorphic computing from Intel, I’ll put all my money into it. Because that’s basically where you’ll be creating the hardware that will be suitable that will be matching the software.

Right now, the hardware and the software are not matching. We’re using Von Neumann architecture in the hardware. We are using neural networks that require data and processing happening at the same time. We don’t have that. If we have neuromorphic computing, that’s what would happen. Intel has the advantage in the world right now on that particular area, but I don’t know what they have done on that particular project. I haven’t heard a lot from them.

KS: Okay. What about Micron (MU)? So one of the big investors out there, I forget which billionaire it was. It might have been Andresen. I’m not positive. So the Micron is one of the biggest companies to watch here because of their DRAM, because of the memory. How does that play into the AI? How much of that are we really going to have to build out as AI and then all the IoT applications progress?

RT: I have not studied Micron myself. So it would be farfetched for me to comment on it. But if you’re talking about RAM in general and the need for RAM, absolutely, that’s data. The RAM realistically is data and the more data that you have on the RAM, the more RAM you have, the faster your processing becomes. But at the same time, we have to remember as well, that the disk right now are moving to solid state disk, which is not that much different from RAM.

KS: Right.

RT: So, do we really need the RAM or that it’s superfast and so on? And how much difference does it have compared to disk? I have not studied Micron myself and I have not invested in it, because I did not…

KS: So there might be a competition between the SSD and the RAM?

RT: Yes, there’s a huge competition right now. Right now, SSDs are getting as fast as the RAM nowadays.

KS: I didn’t know they were that fast. I bought it….

RT: They are extremely fast. They are – basically, if you compare it to the rotating disk, the fastest rotating disk with 15,000 rotations per – 15,000 rotations, the SSDs are about 20 times as fast, which is quite remarkably fast.

KS: I bought a new laptop last year, a couple of weeks before the World Series of Poker, so I had a nice computer set up while I was out there playing. And I never had an SSD on a laptop before. I was still on a – I think I had a seven-year old laptop, which – I probably shouldn’t have had. And this computer fires up so fast and carries so much at a time. I mean it’s basically a desktop. You should just carry it around.

So the SSDs have just been to me remarkable, because I remember waiting to hear all the different sounds on my desktop computer pretty much, and then the fan goes and finally, after about a minute, the software loads and now you can use your computer, right? I mean, it’s – and I know that the kids out there who are listening, they don’t remember the Internet when it started, right?

RT: I remember that. I’ve used it quite a lot actually.

KS: Yes, so I mean it’s – it really is moving pretty fast.

RT: I have a question for you, Kirk?

KS: Okay.

RT: Would you play against a computer in poker or not?

KS: So I have. And there’s a poker theory called Game Theory Optimal. It’s basically risk minimization with selective aggression. And if you play perfect, you should be able to grind out a very long-term draw against anybody anytime even if you’re getting bad cards. So think of it as a stalemate in a chess game, that goes hundreds of moves instead of dozens. I’ve played against the computers and at some point, that’s what it gets to. It’s a draw unless you’re just overaggressive.

And because you can get frustrated against the computer, the computer never gets frustrated, and you make a bad bet and you lose. So the computers that play poker now are basically super GTO is what it’s called of poker players you’ll know what that is Game Theory Optimal. And it’s almost impossible to beat them, but you can hold your own for a very long period of time. Until my little human brain just says, I’m tired, put me away?

RT: I see.

KS: So that’s where it is right now. If the AIs and poker learn intuition, if the AI vision can see me, oh, man, I don’t think I’d be able to beat them. I don’t think it’d be possible?

RT: Have you heard about poker bot called Libratus?

KS: I don’t know if that’s what I used or what I played it. I don’t know the name. No.

RT: Libratus in 2017 won a big poker competition.

KS: Oh, okay.

RT: And then the U.S. military went and bought the company for $10 million.

KS: Oh, okay. So some guy created it in the military. So hedge funds, hedge funds will get down to the finalists of who they’re going to hire in a couple of hedge funds at least two, three that I know of?

RT: Yes.

KS: …will make them play poker, right? It’s risk management with selective aggression. When are you going to put your chips in the middle?

RT: Correct.

KS: And yes, I just bought a – and it is $19 a month. I haven’t played it in over a year.

RT: Yes.

KS: But basically it’s super Game Theory Optimal. And I suppose, because it can collect the data on the hands you’re betting, it figures out your patterns, right? I mean, it just figures it out.

RT: But also, I’m curious about why the military bought such a computer, such a software.

KS: Yes. I guess to try to figure out if the bad guys are doing something bad, right?

RT: Yes. It’s just – I’m just curious about it. But anyway, this software was based on AI.

KS: Wow, yes.

RT: And we’re talking here about something in 2017 a long time ago, a very long time ago, talking about something six years ago before the hype.

KS: Yes, I get it.

RT: So, the world is changing extremely fast nowadays.

KS: Right. I’m looking at your article and you have a list of some of the AIs that are out there. You got Google’s (GOOG) (NASDAQ:GOOGL) got two of them, Facebook (META), Microsoft, Amazon, I don’t know even Alexa. So Amazon has Alexa and Lex.

RT: Yes.

KS: I’ve known about Watson with IBM (NYSE:IBM) a long time. Interesting here, IBM just announced that they’re going to get rid of 8,000 jobs and outsource it to AI. NVIDIA, Megatron and Triton, Salesforce (CRM), Einstein, you just go through this list and you can see it’s an arms race?

RT: It is and it will continue. A new software is coming up on a daily basis. Now, that’s the list of the big companies and how they are competing on the AI side. If you scroll down a little bit on the article, you’ll find out there are other software that’s already available right now.

KS: Right.

RT: For example, Replika. I don’t know if you heard about it or not.

KS: Is that the one where I could take my face and make me look handsome instead of, like I have a face for radio?

RT: Not exactly, Replika.

KS: Okay, they have that, too.

RT: Yes, they have things like this, yes, but if you’ve seen the movie Her H-E-R.

KS: Oh, yes.

RT: That is what Replika is.

KS: Okay.

RT: And Replika does exactly the same thing and it’s damaged so many marriages as a result of that. So I’m just thinking about it. The science fiction that we had in 2013 was Her. Right now is reality.

KS: Right.

RT: And at that time, it was science fiction. But that’s only 2013, that’s only 10 years ago. That’s how fast it progressed to become reality right now with something like Replika.

KS: So, going back to the singularity issue just, because it popped into my brain that’s wandering, we’re older. I’m in my 50s, and I wonder how does this impact the younger generations who unfortunately people in general don’t have a great respect for history. And I worry that people will think that the spot that they’re in, in time. It’s just the way that it always was and they won’t develop and I think I’ve seen this already. They won’t develop some of the communication skills, coping therapies, diplomacy, which I think is going to be vital in the future.

If you read, the guy that wrote the book about The Next 100 Years, Friedman. You wonder, if we don’t learn the skills, because we get lazy. And we just have the AI write all our term papers, and we never go out and play in the sun. I could see a lot of negative things from that. What do you think? How do you control that? Just have to tell parents to kick their kids out?

RT: I think there are huge social issues, but it’s not only related to AI, it’s related to computers in general.

KS: Yes.

RT: For example, the phones that we have right now. At one point, we thought that these phones are something that will enhance us. We became connected to it. It’s not enhancing us. Can you leave the house right now without your phone? Just imagine it. Whoever is listening right now, leave the house and leave your phone for one full day. How would you feel? You’ll start having withdrawal symptoms and start shaking and I’m missing something. I’m not complete. That’s what is happening.

But the other thing as well is that our relationships will be very, very, very much changing towards advancements of technology. I’m not talking only about AI. I’m talking here about overall technology. The technology will change our relationships in a way that we could never imagine. Right now, I see people, a couple, a young couple, most likely they’re dating each other. And they’re sitting on a table, and each one is holding the phone.

KS: Right.

RT: And most likely they are chatting with each other.

KS: …my phone.

RT: And they are – most likely they are chatting with each other on the phone with a table across each other.

KS: Right.

RT: That could very well be the case. But so our relationships are changing. Are they getting better or are they getting worse? The good thing about it when you’re doing chatting, for example, instead of talking to people, you have the opportunity to think and you write something and you cancel it and so on. So you cannot – there’s a possibility that you will not be hurting people as much as you’ll be doing while you’re speaking.

But at the same time, whatever you write is written in stone. It’s not the same as what you’re speaking. So that might be another impact that’s happening in there. Technology is changing us so fast, Kirk. I don’t know where it will end. I really don’t know. And anyone who says that they know what – how it will end, I’m sure that they might be wrong as well.

KS: Right. Yes, no. I hear you. I’m wondering where a lot of things go. And I think ultimately, it depends, and I think COVID gave me a clue. I think ultimately it ends with us making choices that we just think are healthy. And my goal during COVID, because I knew I was going to be on my own and just with my fiance, 24/7, was to work a lot and go outside and exercise and get in much better shape.

RT: Yes.

KS: And it turns out that the media put it in my head that, hey, we need to support the restaurants. Okay. So I started eating out more going through the drive-thrus. And rather than going and get a lettuce wrap somewhere, we have custard stands by me a lot of them. So really rich ice cream. So I didn’t become an alcoholic. I didn’t end up eating fried food. But I eat a lot of custard and gained 20 pounds. I just wonder if there’s similar things that could happen, but I saw lots of other people as I drove to the custard stand on their bike in the park. So it’s going to need to come down to choices.

RT: Yes. It would be. Yes, absolutely.

KS: And I think that normally, Churchill said this about America, but I think it applies almost everywhere. I think humanity generally comes to the right decisions. They generally do the right thing, after they’ve tried everything else. And I just worry that everything else includes a really, really bad thing that, we can’t come back from?

RT: I hope not to, Kirk. I hope not. I don’t think that we’ll end up destroying ourselves as a civilization.

KS: All right.

RT: I don’t reach that level. That’s what I personally believe. But at the same time, I think that some bad things will be happening. I don’t think that will reach a nuclear war, but some bad things could be happening in the world before we get to the better things. So it’s like we’re going up like this. We’ll have to go down a little bit before we go up again. So, we have to basically level or go a little bit down and then we’ll continue going up.

KS: Okay.

RT: So expect some downturn, but how much would it be? I don’t think it would be extensive because, again, what we’re experiencing right now is something that we have never experienced in any of the other industrial revolutions where the machines are improving themselves. That’s something that we’ve never seen before.

KS: So for folks who listen on Seeking Alpha, we’re doing this podcast style. And I can see Ramy. So he basically just made a chart with his hand in the air and it was a – it looked like a secular bull market with cyclical bear markets. So hopefully, we just end up in a better place. We just have to take a step back every now and then.

Are there any other companies that you’re really bullish on or really bearish on? I know that we have a bear list. We’ve put together a list of 20 to 30 companies we think will be disrupted on top of the 50 or 60 that we think will do well. Are there any companies that you really are finding very interesting as we go through all of this?

RT: The one company that I found out extremely interesting and I’m investing in it for a long time is Lockheed Martin (LMT)…

KS: Okay.

RT: …primarily, because the drive that they’re having was artificial intelligence although they don’t announce a lot of what they’re doing in artificial intelligence, I know that they’re doing a lot. And anyone who has just a little bit of a brain will understand that they’re doing quite a lot on that particular area. So that’s one company that I feel has a huge opportunity. The other company that I would be very bearish on, very bearish on is Google (GOOG) (GOOGL).

KS: Really?

RT: Not because they are not good in AI. I think that they are excellent in AI and their AI capabilities are fantastic. But what I’m thinking of is what would happen to Google if and when, maybe when, not if, when ChatGPT and other generative software starts taking advertising money.

KS: Right.

RT: Where will they take it from? 70% of the revenue from Google is coming from advertisement, and the advertising money is limited. It’s not unlimited well. So once these generating software start putting advertisement on their platforms, this money will be coming from Google, and Google will be very, very negatively impacted as a result of that. So once ChatGPT, for example, announces, they’re starting to put advertisements in there.

Let’s assume that they start doing that. They’re a for profit organization and they can do it and they make tons of money out of it. Where does this money come from? It will come from Google. And Google will suffer quite a lot as a result of that. That’s why I would not touch Google. I would not short it either, but I would not invest in it.

KS: So with Google, I’ve been thinking about this, because so much of their revenue is ads, they need AI to just try to keep their slice of the pie. And it’s a giant slice right now. But if all the kids are using ChatGPT to cheat on their tests and their papers, they’re going to see their ads there. And since they’re already there…

RT: Why go to Google?

KS: Yes, why go to Google? So Google needs to make sure that they get into the mindset of the younger people, because they’re tomorrow’s consumers.

RT: They cannot do it. Kirk, I don’t think that they can do it anymore. It’s over. It’s over, because right now the generative software is out there. And what will they do? They’ll create another generative software and put the ads on it. If they start creating another generative software and put the ads on it, they’re inviting other generative software to put ads on it.

KS: Right.

RT: And do they really want that? Because again, we have to remember advertising money is limited, it’s not an unlimited wealth. And the money will have to come from somewhere. Advertisers will take part of their advertising that they have with Google and put it in ChatGPT. Google’s revenue, top line will be dropping.

KS: Right.

RT: It will eventually drop quite significantly. There is no doubt in my mind that whoever is betting on Google, because they have a great AI platform and they do. No doubt about it. Maybe they are far superior to any other company in the world from an AI platform. But they have an Achilles heel in there that the revenue is coming from advertising.

KS: Because it’s so heavy on.

RT: Advertising revenue will be divided through generative software and search.

KS: Right.

RT: I have used ChatGPT three times today. I had questions for some things that I didn’t know. And where did I go? I didn’t go to Google. I went to ChatGPT.

KS: Right.

RT: Because it gave me…I went to Google, it didn’t give me the proper answer in Google either, ChatGPT gave me.

KS: ChatGPT will just answer your question. Google gives you a whole list of things that you now have to go out and read.

RT: No, right now they give you the answer at the top. They try to give you a brief answer at the top, but their answer that they gave me was not correct and it was not elaborate as much as I needed.

KS: Okay, all right. So my thesis on Google has been the value is in the spinoffs and they haven’t moved in that direction yet. So I don’t really know how to play Google from the standpoint of, if they lose 10% of their ad revenue, I mean, that’s a huge hit, right?

RT: Absolutely.

KS: So you don’t have to lose 80% of it. 10% of it is 7% of their revenue. So I mean, that’s a concern. I think that their spinoffs, which I call the baby Googles, are all going to be S&P 500 sized companies. I wonder if this is a mechanism to accelerate the pace of Google spinoffs?

RT: Spinoffs companies like what, for example, spinoff is a Google Docs and spinoff the YouTube and so on. Is that what you’re thinking of?

KS: Yes, yes. So I think that with Paramount and Warner Brothers probably up for sale. Does Google use some of that cash to spinout YouTube and buy a library and studios, the 500?

RT: I think that they might be spinning off Google Docs possibly, because it’s not based on advertisements. But I think it’s very important for them to keep all their advertising platforms together under one single platform, because if I’m an advertiser right now and I am an advertiser with Google, I have the choice of putting my advertising money on YouTube or on Google Search or the network or whatever other platforms that they have. So, I think that they need to keep all their advertising revenue together in one single company. But I think that they have also a company that looks at life sciences right now. Don’t they?

KS: Yes. They have 11 different companies and I think they could spinoff so.

RT: So these would be potential spinoffs as long as they don’t have advertising revenue for them, I think.

KS: Yes. So I also advertise on Google and I do a little bit of ad words, but I’ve been moving towards advertising on YouTube. So it kind of – so, I think I hope people are following here is that AI has impact two, three layers down. And with Google, it might – if they keep Google and YouTube together and all their advertising stuff together, that still means that they’ll need even more content than YouTube, which I think puts them in play for Paramount and Warner Brothers Discovery and other smaller, cheaper things.

Yes, because streaming is cheap right now. So they could go on and buy streaming if they wanted to. Amazon bought the MGM Studios, because they already have the platform. Apple (AAPL) is rumored to be interested in Paramount. Comcast (CMCSA) is rumored to be interested in Warner Brothers Discovery (WBD). And I think this AI is actually and you mentioned this in the article somewhere it’s going to play a big role in M&A across multiple industries probably?

RT: It would – it certainly would. However, having said that, I’d like to talk about something else, Kirk.

KS: Okay.

RT: Which is the overall economic impact of AI on the overall economy not specific investments?

KS: Okay.

RT: Because that’s the thing that many people have talked about, basically, the potential for unemployment.

KS: Right.

RT: And my expectation is that would be huge, huge massive. I’m seeing that already. I’m not saying that AI will take away jobs, but people who are using AI will replace people who are not using AI.

KS: Correct.

RT: And not everyone will be using AI. So people who are not using it would be out of a job. And people who are using it would be. For example, a lawyer who’s using AI will be producing 10 times as much as a lawyer who is not using AI.

KS: Right.

RT: An ideologist who’s using AI would be producing 10 more reports, 10 times more reports than someone who’s not. For example, so jobs will be lost. How much percentage unemployment are we expecting? During the large depression, we had 24% unemployment. I am actually predicting that within 10 years, we might be hitting something close to 30% to 40%, maybe 50% unemployment. Much bigger than the big depression of the early 20th century after the first World War. That is something that is scaring everyone.

KS: Yes.

RT: And people don’t realize what it is. Politicians are not even talking about it right now. Look at Powell, he does not look at the kind of layoffs that are happening in high-tech companies right now. Every high-tech company is laying-off people. And I put it in the article and I put the list of high-tech companies that are laying-off people. Look at the list and how many there are and that’s only into 2023. And that’s when I wrote the article two months ago. Since that time, many companies – every company is announcing layoffs every week, that’s happening right now.

KS: Where we mentioned IBM today.

RT: Yes. For example, that’s an example in there. But IBM is only one example. And IBM was mentioned there that it’s not the first round of layoffs, they’re having more rounds of it. And IBM is one of the companies that’s invested heavily in AI.

KS: Right.

RT: My expectation is that high-tech companies are laying-off people, because they are investing in AI. And they’re using AI in their operations. And as a result of using it as an operation, they don’t need as many people…

KS: Right.

RT: …For their operations, and that’s why they layoff. Once AI spreads to other industries, we’ll find out that the layoffs will not be only on high-tech, but will be spread throughout the broad industries altogether. All industries will be impacted as a result of that. How can we resolve something like this?

And I tried to mention that in the article. What will happen is that productivity will be going up in leaps and bound, it will be unbounded, the amount of productivity gains. Things will be less expensive. We’ll not have inflation. We’ll have a potential of deflation, which is a disaster for an economic perspective. So you mentioned deflation.

KS: I smiled.

RT: High unemployment.. Yes, go ahead. Go ahead.

KS: I smile there, because my subscribers and clients will know and I have it posted on Twitter somewhere. A year ago I said, in five years, we’ll be talking about deflation again. And nobody wanted to hear it.

RT: Well, I am talking about it right now. It’s already happening.

KS: Yes.

RT: I did some calculations, Kirk. That’s based in Canada, not in the U.S. And I look at the amount of quantitative easing effectively printing money that the Canadian government has gone through. And I did some calculations and found out that the inflation rate in Canada should be around 15% to 20%.

KS: Right.

RT: We’re experiencing 6%, 7% right now. How are we experiencing 6% and 7%? Because of COVID, the amount of money that was printed should have resulted in 15% to 20% inflation. We’re getting only 6% to 7 %. Why? Because we’re experiencing huge amount of productivity gains, huge massive that is happening already. And of course, measuring productivity is almost impossible. You cannot measure it. It’s not measurable. But we’re seeing that happening just before based on the simple calculations that I’ve done.

The problem that we did not have that we are facing inflation is the perfect storm that happened during COVID. Supply chain management that has happened, the increase of the prices, the Russian war, the lockdown in China, all these things happening, I said that was a perfect storm. That’s what resulted in inflation. Otherwise, we would have been facing deflation right now. And that’s why companies were spending money left, right and center, because economists are not stupid. They know that this is happening, but they’re not talking about the right.

KS: Right. Well, I’m glad that somebody smarter than me agrees with what I’ve been talking about with inflation.

RT: I’m not smarter than you.

KS: I tell you, I’ve been writing since 2011 on MarketWatch, telling people that slow growth forever and deflation due to aging demographics and technology were the real problem. The deflation was the boogeyman, not inflation. But you have all these people who are backwards looking instead of forwards looking and they want to scream Weimar Republic and they want to scream scarcity and they want to scream money printing without even understanding the whole quote from Milton Friedman.

So, I look at all of this and I think to myself, A, how can I make a whole bunch of money on it? B, how can I help other people do it? And C, can I have a positive impact on the world even if it’s just my own family and friends? I mean, it’s great if you can impact a larger community, but I think it’s going to take a lot of people to impact a lot of small communities. At the company level, at the investment level, again, since we’re on Seeking Alpha.

At the investment level, one of the things that was talked about at CES 2020 and I keep coming back to that conference, because it was the best conference I had ever been at. They talked about AI wasn’t a risk to people who worked a machine or built things. It was a risk to the MBA who was basically looking over people’s shoulder and shuffling paper. So that’s what we’re seeing right now. And I would use the analogy that in the 1980s, which those recessions in the early 80s were formative events in my life.

I saw a lot of hardworking men in particular lose their jobs to a combination of off-shoring for financial reasons and automation. And I’m in Milwaukee with Rockwell (ROK). So, we get to watch the advance of automation firsthand, right? It’s in our business journal every week. And you start to wonder – all right, how many jobs will literally be lost versus how many will be gained? I have a little bit more optimistic view on the unemployment picture. I think a couple of things will happen.

I think number one, a lot of people who are semi-skilled to skilled will start consulting, opening a second business, because with the baby boomers retiring, we have a shortage of small business people. I think a lot more people get into small business and maybe have two or three small businesses like I do. I’m lucky the two of them pay me full time incomes and I think the third one might eventually. And I take a look at family structure.

In the 1970s, we started to go from one earner families to two earner families to the point where, what was it? 60% or 70% of households in America, I don’t know the numbers around the world. But like 70% – two-thirds of the households in America had mom and dad both working. I think we’re going to get to the point where instead of it being two-thirds of the households, where both the mom and dad are working, it gets down to below half. I don’t know much, much below half.

And because we have deflation and because we’ve loaded the world with debt, you should actually see your work be worth more in a world where inflation disappears. And that’ll be transitory over maybe a decade. I know people don’t think of a decade as transitory, but it really is a blip. If you go back and look at stock charts, it’s hard to pick anything out over a 100 years.

RT: Yes.

KS: So I think that the number of people working will go down as a percentage. But because so many of them choose to and they can afford to, I don’t think it has the impact of a giant recession, right? I don’t think it has an impact.

RT: I don’t think it will be a recession. No, no. I never said that it will be a recession.

KS: Well, no, no and I understand that, but I think people hear when they hear 20% unemployment, they think, oh my God, that’s horrible. And I think the labor participation rate comes down.

RT: Yes.

KS: But I don’t think it is the impact of traditional inflation…

RT: I don’t think that the governments will allow us to get to that level of 30%. And I personally believe that the only way around it, the amount of work that’s required from people will be dropping, no doubt about it, because right now, people will be more efficient. People will be more productive. So, we’ll not need as much work from people.

KS: Correct.

RT: The only solution around it to maintain a very low unemployment rate is to legislate less than five day a week work.

KS: I think that’s happening without laws?

RT: It’s happening in certain countries as a matter of fact right now as we’re speaking.

KS: Right.

RT: I think some Scandinavian countries are doing that. I don’t remember which one it is. But they are playing with four-day weeks. And I think it might even drop to three-day week. The only problem with – is that the income will have to be supplemented somehow. Because the companies right now, they do not want to pay the people for the same amount of money for working four days. So this income has to be supplemented. How will they supplement it? Is it a welfare system or maybe it’s going to keep basic income? I don’t know.

And if it’s going to keep basic income or even welfare, how will we fund it? Maybe funding – maybe funding,

KS: I hear.

RT: it will be – just hold a moment. Maybe funding it will be the solution for the deflation.

KS: All right. Well, I hear in certain countries that are a little bit north of the United States that health care ends up not being a problem for too many people.

RT: In Canada, it’s not a problem at all. Anyone gets Universal Health Care.

KS: Right. So, before we get the Universal basic income in the United States anyway, maybe we get to a system where everybody is on Medicare, everybody has to have a certain base level of coverage. You can buy supplemental if you can afford it and you want to go to certain places not in your network. I get it. I understand all the problems. My senior thesis in college for economics was on health care. And I went into it…

RT: And I cannot imagine why it is not Universal in the United States yet. That’s beyond my comprehension. Why are they not doing it? Just you know what? When you think about how much money is required for Universal Health Care in the United States, compared to the military budget that they have.

KS: Right.

RT: Think about that and do the calculation and then figure out what is more important to have as much military as the next 10 countries combined or to have Universal Health Care for all the people. But which politician would be ready to do that?

KS: And I didn’t start there. So when I wrote my thesis in college, I went into it thinking, more competition, better health care cheaper. And by the end of my research of after six or seven months, I mean, it was two semesters, I came up with two conclusions. One, we had to move the Universal Health Care because otherwise the country would go bankrupt and Arthur Laffer was a knucklehead.

I mean, those are the two things I came out a bit with. And I’m 22, 23 years old, thinking this is the way it’s going to be. And then I look at it and I’m like, wow, with the aging of the baby boomers, at some point, I mean, we’re going to have a huge percentage of the people on Medicare anyway in five years as the last baby boomers hit it.

But the way that we’ve developed an oligopoly, people say there’s a lot of competition in health care and there’s really not. There’s been so many mergers and acquisitions. There’s – you have UnitedHealthcare and Blue Cross Blue Shield. I mean, you’ve got like five health care companies taking care of everybody. And you got some nibbles at the edges, right?

Obamacare has been remarkably good for health care in America. And people don’t want to talk about it because they’re all well, I pay $8 more a month or whatever. They don’t want to grasp the fact that we’ve basically stifled health care inflation just with Obamacare. And with AI coming in and helping with diagnosis and treatment plans, one of my major themes right now is we need to find the companies that promote health care deflation because otherwise, in the United States, which is aging rapidly, and Japan is a nursing home practically that are so old, and China is getting older and Europe’s old and they’re a museum, and a lot of the emerging markets actually are getting older now, too. I know India is still very young.

But you take a look at things, like, well, I think the first step is let’s have everybody get good health care and have it be cheap and figure out a way to make that happen. And I think the two things are AI and Universal Health Care. It can’t be necessarily free. I mean, there’s still got to be a financing mechanism, but I can’t see where AI doesn’t have a major, major impact on health care, regardless of what system we choose. And I think that there’s going to be some big money made there.

There’s one company out there that we’re focused on that everybody thinks of as just a purely talk to your doctor on the computer company, the data that Teladoc (TDOC) has and the way that they’re starting to build AI into it, is a big deal. I think…

RT: It is. I’m very strong believer in Teladoc by the way. I’m investing personally in it. And I believe that this is a company that’s going places. Their use of AI is quite remarkable and they have been using it quite actively for the past four, five years, and they are one of the leaders in that particular area.

Now, we have to remember something as well that AI right now is better than general practitioners in diagnostic sequences.

KS: By a lot.

RT: By a lot. You’re absolutely right. You go to a computer, you give them the symptoms that they have, they identify the kind of potential sicknesses that you have and they can recommend a referral for you, which is basically what many general practitioners are doing. They just ask you what questions you have, they send you to do some tests. Then based on the test, they refer you to a specialist. Now, the computer can do that. And then in such a situation, you can imagine that the cost of doing something like this will be dropping quite dramatically. Now, that’s one area.

The other area which has already taken place is radiology. Computers right now are much better than radiologists in identifying and studying X-rays, CT scans, pet scans, MRAs, all kinds of diagnostic medicine. The computer is much better than human beings and that’s one of the major costs of this diagnostic medicine. So these are two areas that AI can play a major part of.

I strongly believe in Teladoc by the way. This is a company that I will be going places. It’s – I don’t know why it dropped that much. It does not make any sense to me because the potential for it is just enormous. That’s my personal opinion anyway, but I’m putting my money on my wallet.

KS: We just started scaling in. I’m going to cut us off here because I think that we could talk through the night and I looked at your resume and work schedule and everything that you do. I think folks should take a look at your profile on Seeking Alpha. When I saw the companies that you worked for, I was like, whoa, there’s a lot of stuff.

So your main gig is you’re a corporate guy who is working with your own company. I believe that’s your company, correct?

RT: VeritableSoft is my company. I’m the Founder of that company. It’s company employee owned.

KS: Okay.

RT: So everyone in the company owns shares, it’s not funded by Venture capital or anything.

KS: So that’s why you were on the ESOP Board. I get it.

RT: Yes. I’m on the ESOP Board of Directors.

KS: Okay. Well, it’s been an awesome talk. I know it’s getting to be late at night by you. You spent a lot of time with us. I really do appreciate it. I hope we talk more.

RT: I hope you as well, Kirk. I enjoyed this conversation very much. I don’t have the chance to discuss these things with people as much I’m discussing – as I’m discussing with you. So for me, it was a great privilege and honor and pleasure.

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