Is AI Our Greatest Ally or Our Biggest Threat? Inside Scoop from a Tech Billionaire!

Published Oct 25, 2024, 11:42 PM

Is AI Our Greatest Ally or Our Biggest Threat? Inside Scoop from a Tech Billionaire! Explore the dual nature of artificial intelligence with us as we delve into whether AI is humanity’s greatest ally or its biggest threat. Joined by a renowned tech billionaire with decades of experience in the industry, this video promises to uncover the deep impacts, potential risks, and staggering benefits of AI. What You'll Learn: The Benefits vs. Risks of AI: Understand the transformative power of AI and the potential dangers it poses to society. Expert Insights: Hear firsthand from a tech mogul who has been at the forefront of technological innovation and why they believe AI is a critical issue for our future. Navigating the Future: Discover actionable steps and policies that can help balance AI's risks with its rewards, ensuring it serves humanity positively. Whether you're a tech enthusiast, a concerned citizen, or someone curious about the future of technology, this video is your gateway to understanding AI beyond the headlines. Join us as we explore essential questions and offer expert insights that could define the future of artificial intelligence. Don't forget to like, subscribe, and click the bell icon to get notifications for more thought-provoking content!

Is AI an existential threat to humanity? Or is it a tool that's going to revolutionize businesses, give us new productivity and efficiency. Well, this is a big rating topic and debate, and so I am going to bring on an AI expert today, Hamad Shabazi. We're going to talk about many things in AI, and he is somebody we should listen to. He's been a tech investor tech founder for over twenty years. He founded TiO Networks, which was required by PayPal for over three hundred million dollars. He's done over seventy m and a deals, died over two billion dollars, and now he's the founder and CEO of well Health, which is using AI to revolutionize healthcare. Maybe what I see is the potential biggest opportunity we have. So we're going to talk about is AI an exsidential threat to humanity? Will governments are regulated out of existence? Or how should they manage that? Our large language models llms really AI or not. We're going to look at what are the biggest areas, the biggest disruptors that AI is going to make. We're going to look at health care problems. Health is one of the biggest problems in the United States and the world really for that matter, how can AI really help solve that? And as you probably know, the really two areas I focus on investing is bitcoin and AI, And so from an investing lens, how should we look at AI companies to make huge potential returns inside stepping all the risk. It's a conversation I've really been looking forward to. I'm so happy to have him oud on. So let's just go ahead and just jump right into it. We're going to talk about this. Come on, Thanks so much for joining me today.

Mark, it's a pleasure to be with you.

Yeah, so big topics, you know, something that I mean has kind of caught the whole world by storm over the last couple of years since open Ai came on the scene. Something I definitely focus on. My main areas of focus is sort of bitcoin and AI, and I'm really interested in let's just start, man, Let's just dive right into the deep end of this, because we kind of have like two different camps here, and I feel being a tech investor and someone who studied technology cycles really at the next real revolution, we had the led eye and the Ledites were people that were afraid of the power loom because it was gonna take away jobs, and so we always have every time there's new technology, there's the leadites, the people that are afraid of the technology. You're working with AI, And the big question we have is is AI this existential threat to humanity or have we all just grown up watching the terminator and we have this fearful, you know, vision or view of that. What's your take?

Yeah, look, I think it's it's both of what you said.

I think it is.

I think it can be existential threat, and I think it can be an incredible boost and productivity that that supports humanity and provides societal value. I think that if we don't regulate this amazing thing that not everyone truly understands, it does have transformational potential.

In positive and negative ways.

And this is no different than what we've seen in terms of of you know, regular internet technologies.

They've created vast improvements.

And productivity for us, but also they've created new attack vectors that people are using to steal our information and cause havoc in the world. I don't think the eyes any different. I think it just creates a much bigger potential, just given how intelligent it really is. And how and the potential that it has in order to to to do incredible things and to wreak even more havoc in our lives, you know. So so yeah, I'm I'm a big proponent. I suppose I support you know, the thesis that guys like Elon Musk have out there where they're very, very worried about how quickly this is developing. But also you know, there's a recognition that it that it can do an immense good in the world too and drive productivity.

So you look at technology as more of a tool, and a tool can be used for good or bad. I can use the screwdriver to fix a car, or I could stab somebody with it. Right, It's like, I guess that's what you're saying.

Absolutely, you know, I think I think that's fundamentally what technology. And each time one of these things comes along, I think it drives a lot of transformation in our in our lives and our and and work and even how we how we operate, uh, you know, as as private citizens. And and that productivity uh is something that you know, both can be used for good or bad. Those tools can be and so it's unfortunately we can't just reserve those those tools and that productivity for for the for the good guys. Unfortunately, the bad guys also get access to that.

You know.

For example, I think cybersecurity plus A I I mean, I mean, I mean cyber threats plus AI is A is a big and challenging issue.

You know, before what would happen in terms.

Of cyber threats is that you would have these sort of dumb robots going around the Internet and trying to open doors and seeing if if if if network administrators left something open or had you know, easy passwords, and they would just you know, and if and if something opened, they would they would go in and see what's going on and see.

If there's any data for them.

Now, the the algorithms that are looking for vulnerabilities are not just checking for doors being opened. They are they're they're taking much more complex approaches to identify you vulnerabilities and in software and and and network infrastructure. And that's pretty devastating considering that increasingly all of our information is online. And so I think the only thing that can really help support that is you know, the AI that that defends us against the AI that's attacking us.

Right, So I think this is definitely a.

Tool that's going to be used on on both sides of that of that equation.

Yeah, I mean in regards to that, you're absolutely right. My account got hacked. My Twitter account got hacked. I was locked out for like five or six months. And you know, these these hackers are so so aggressive but also so advanced today using these AI tools. And it's not just to the point that you said, like going around finding a door. I like that analogy, I find a door to open. But the ability to deep fakes and so everything that we know about cybersecurity, which is send me a picture of your ID, send me a video, all those things, now that those can be completely faked, and so it's really the entire way that we validated is now ineffective. So that's that's interesting. But I want to go back to what you talked about with you know, regulation, you said that I think you said we need regulation. I'm curious to your take on that, just because one ein Ran, who wrote the Atlas Shrugs, says that when you need to get permission to produce for men who produce nothing, and so what do a bunch of bureaucrats who are seventy five years old. Know about regulating AI Number one, Number two. I just listened to this interview with Peter Diel you know obviously you know, but for the audience, you know, prolific VC investor in Silicon Valley. I think it was on trigonometry, and he would saying that I'm much more fearful of the world it would take to try to regulate it, because it would require such an orwell and authoritarian view to try to control this, that that's much more problematic. I'm curious your take on that, and just do the relation.

Yeah.

Look, I don't think it's an easy thing to regulate, but I think there's low hanging fruit and I think this is the area where regulators can get involved. And just and just I agree. I think you need a light touch, but I think you need a touch. For example, you made a great comment about deep fakes. If someone is calling you and you know the performance of these you know, uh, you know, these these voice robots is becoming quite good. It's becoming quite smooth, where it's becoming difficult for you to tell the difference between a human calling you in a robot calling you. I think one interesting area where where people may want to look for regulation is is to is if a robot is calling you, for it to declare that it's a robot. Don't you want to know if you're talking to a robot or to a human. I think that's important to know.

And I think and I.

Think that's just that you know, doesn't mean that that the conversation has to be less less productive, But I think it's an important thing to be able to know that and and and that.

Could be regulated.

It could say, hey, look, anytime you get a call from a robot, because we're having a more and more difficult time discerning between the two, you know, it ought to declare or somehow it needs to identify the fact that it is and and so and so. It's stuff like that to me that I think help help people just just navigate this this this new fangled world that we're dealing with. You know, like like the deep fakes are a really really big problem, right. It's becoming very very difficult to tell whether or not something is authentic or not right. And you know, there there have been fraud that has been perpetrated by virtue of of of entire boards of directors that have been deep faked in order to convince someone to wire money. You know, stuff like that is just it's it's it's it's pretty hard to beat. So I think I think it'd be very helpful, you know, for there to be some of some some of that regulation out there.

Uh yeah, I mean that sounds pretty reasonable. I mean obviously we already have laws around fraud, and so you know, if you're deep faking somebody that's technically illegal already, right that that would be considered fraud. And so having disclosures like that I think would certainly be helpful.

Man.

I could even see the disclosures being needed around you know, the content creation piece. You know, am I you know what am I reading here? Who wrote this kind of thing like that? Pretty interesting? Now, I hear some people talk about and it was a couple of years ago. I got a chance. It was an amazing chance to sit down with the ball. There's a another prolific VS investor from Silicon Valley and this was two years ago, two or three years ago, and he was talking about the difference of narrow AI versus general AI and how this narrow AI is really starting to advance like super super fast. But the general AI, which is you know, where it can sort of have this general intelligence it could grow its own hasn't really advanced at all, and that was a couple of years ago, so maybe that's changed. But I also see people say that really what we have today is really large language models LMS, and really what they've done is they've taken language and broken that down into data and it's not really AI. What's your take on that.

Well, I think there is this kind of notion that there's sort of symbolic AI and generative AI.

Right.

Symbolic AI is essentially, you know, processing and mining vast sums of data. It is then learning how you know what the relationships associated with that data are.

That data is.

Being trained and you're basically looking at this data to find anomalies you know, in rules based order or when you question a piece of data, when you prosecute data and you want to know something, when you have rules and you say, please let me know the values that exceed this because you're looking for something. Sometimes you don't know what you're looking for. You're just looking for what are the anomalies in this data that I don't know, what's the needle in a Haystack. That's where AI is incredibly valuable. That's symbolic AI, generative AI is we have so much data and it starts to inform our view of how to essentially complete, you know, complete a sentence.

You know, when we're writing something. There's so much data, and they've mean able to.

Stitch it together and effectively train it in such a way that where it can actually start to generate responses.

I mean, essentially it's.

All AI because it is it is it is leveraging, you know, uh, the power of data, unlocking the power of data in order to to.

Provide some kind of insights.

But you know, I think if you're sort of an AI purist, you could say only the symbolic AI is the true AI. You know, so, so I think it comes just back to your perspective. But to me, general of AI, you know, it looks like magic and it's pretty incredible, but it is dependent on the data inputs in that large language model. So if there's garbage in there, you're not going to get You're going to get garbage out. And and a lot of what's starting to happen is people are producing large language models based on you know, more precise data sets and so you know, the smaller models that are that are specific to particular.

Areas, and you can then get.

Uh, you know, you know, very very interesting kind of opportunities to let's let's say you have all kinds of different medical publications that it would be really hard to go through and read all of them. But then the ability to just you know, question that large language model and essentially get responses, you know, instantaneously, that is something that really unlocks the value of data. And that's what we're starting to see is for the longest time, we've all been sitting on all this data, and companies have been saying that we've got all this data. Everyone's very excited about sitting on the data, but that's all they've been doing, just sitting on it. No one has really been able to unlock the value of data until now and the price of doing that. And that's what's very exciting is that if this has become so accessible to so many and so now we're starting to mobilize all this data. I mean, I work in the healthcare field. Thirty percent of the world's data is generated by the healthcare industry. By next year, thirty six percent there'll be thirty six percent growth compound growth. And all the data that's generated in the healthcare industry, it's an enormous amount of data, and so how are we ever going to unlock the value of it without things like large anguish models or symbolic AI and the complexity of the human body requires that type of data in order to be able to unlock you know, true insights in terms of predictive analytics, in terms of precision health, in terms of all kinds of different things.

Right, I know, you know, as I've used it more and more and more just in my own business, and you know, I go through a lot of financial reports and sec filings and things that are hundreds of pages long. And the ability for me to have these little mini agents built where they can go get the data, bring the data back, go through the data, tell me who you know based off of who I am? What questions I should have? Answer those questions for me? Right, it's not right? I mean I feel like I'm in that movie Limitless when he first takes the drug and then all of a sudden he's like writing and like you see all the data. I feel like I'm like that, Like the ability to go through this data, I do almost feel superhuman, you know. I also talk a lot about bitcoin, and one thing that I'm really interested in is where AI and bitcoin can come together. And the reason why is because bitcoin is borderless, permissionless, and so resistant those things. But it's also personless, and so that means obviously only a person cant a bank account, but now a machine could have a bank account and could go out there and do these economic things, and so like, what does that open up? We don't even know. And it's because that humans are no good to imagine in the future, because we can only imagine better versions of what we have today. But when we have new building blocks, it builds things we didn't imagine, and so I'm just curious. You know, again, as I just said, we're not really good at seeing the future because we don't have these new building blocks. But from your vantage point twenty years in technology and it's a founder, M and a, etc. What do you think are some of the biggest areas or maybe businesses or industries that will be disrupted by AI? You mentioned healthcare. I think that's a big one right off the bat. I'm curious where do you think would be probably the most affected by this AI transition that we're in.

Honestly, I don't think there's an industry that will not be affected. I think that that, you know, there's there's so much administray. First of all, I think all kinds of different administer administrative burdens. I mean, you know, will will will be will be addressed through the.

Use of AI.

I mean I think like a legal professional change dramatically, Like why would you want lawyers to sit there and draft you know, these these these significant documents. They would get paid, you know, significant amounts of of of money in order to do this very complicated and complex work of looking at all the different you know, you know, legal codes and and and covenants that they must you know, respect and and and writing contracts that interact with those changing legal covenants and and and laws and and that's just mind bending work, right, It's it's very complicated and minding.

And now you know the mission.

It's clear that a machine will be able to do that better and make less mistakes than a human would. It's clear that a machine will will will do a better job of interpreting an X ray result than a human would. Now these things are are you know are our truths. I mean that this is what's emerging, but it doesn't mean that humans won't.

Be able to play a role. I'll give you a great example.

You know, we already have a scenario right now where you know, and you know, where we interact with with humans who are administering computers. And we've actually seen this for many years. This is this is when we get into a plane and we fly somewhere, it's actually not the plane, the pilot that's flying the plane, it's the onboard computer.

And that's been happening for.

Decades, right, But but we for some reason, we still feel a lot more comfortable for the humans there, right because we do know that as advanced as technology can be, it can glitch. And that's when you need to have kind of the spatial reasoning and and all all the kind of gifts that humans have in order to be able to integrate information in terms of sanity, checking what's going on and and keeping uh an eye on this on on on on on computers and making sure that they're they're doing what they ought to do. And that's essentially I think what's what's what our rule is going to start to be it's it's not necessarily doing all that low leverage work, but really but really overseeing technology, being almost a concierge for that technology, knowing how to use it, knowing how to unlock its value, and and and also that could that could open up opportunities for for for us to to provide uh, you know, better service. So, for example, if you're a doctor, if you have disease detection algorithms and all kinds of things that are helping you in in that diagnosis, instead of like you know, you know, typing and and and and and taking notes and and and working on an administrative things, you can spend a lot more time looking at your patient and spending time you know, uh you know, looking in their eyes, examining them, you know, touching them. There's been data that's shown that doctors that touch and pay attention to their patients have higher patient outcomes.

I mean, just think about that.

If a doctor pays more attention to you and touches you and shows more and directs more of his personal energy or her personal energy towards you, that could elevate your your patient outcomes. So I think there's all kinds of interesting things that will happen as a result of AI, and a lot of them I think could be very good.

Yeah, I can see that. You know, you talk about the legal field. I mean any of these information fields for sure, right, But the legal field, there's so much data to go through. And so I remember my uncle was an attorney, and man, he got so tired of being attorney because he said all he did was read, like you're constantly just digging through books trying to find case law, precedents, things like that. So there's just no way a human can go through that much data and obviously retain it. And same in the medical field. I mean, we have medical fields all over the world and all these different cases, and there's just no way for someone to get all that data. But the machines can, and and I think to the point that you're making sort of it's a tool. So it helps humans do a better job as opposed to replacing humans. I you know, for whatever reason my worldview, I don't think that machines replace humans. I think we always need the human creativity and I don't think machines. Machines are good at data, but they're not good at creativity, and so it'll always be how do humans use the machines? And so I think from that perspective it can help us do much better. Now, the legal field is last night I saw Tucker Carlson and and ourf CAG live and they're, you know, bashing attorneys and you know, these leeches and whatever. But on the medical side, that's like life and death. Man, right, that's like life and death. It's super important. I heard Peter Diamantes, he's an m I T grad, you know, tech prolific, tech tech guy. For everybody listening, Peter Diamantes said that he thinks within five years it would be medical malpractice to practice medicine without using AI. What do you think about that quote.

I think he's got a point.

I don't know what the time scal is, but I do think he's he's right in that, you know, disease detection uh uh. And and just patient care will will improve so significantly as a result of AI technologies. And this will be somewhat dependent on there being enough data on the patient. You know, if if you don't have any data on the patient, then then you're going to have to examine them and you're you're going to need to rely on those skills that you learned in med.

School and whatnot.

But you know, the data footprint on a per patient basis is increasing so much and and and most of us have a lot of medical history. You know, tons and tons of PDFs, you know, lab reports, hospital pronouns, all kinds of stuff, all that is coming into a patient record.

And and you.

Know, you know, our company heal Well a I which is a which is an investee of Well It's it's uh uh, it's a company that that we have a strategic alliance with and have a path to control with.

You know, is able to.

Use that that EHR data to actually identify, you know, the stage of cancer that you may have or detect very low, very rare, uh, you know, cancers. And I mean the kinds of things that we've been able to do and now you know written in in in medical publications esteemed medical publications is pretty incredible. And so I would agree that if you at a certain point are not using these you know, medical co pilot technologies AI co pilot technologies, you are you are probably providing a vastly inferior.

Quality of service, especially as.

These things come of age and they're coming very quickly.

I can imagine, I mean to your point, right, So it's like go through your medical history and a second, like I already kind of referenced. I mean, I used, I'll download like sec violings and just loaded in, and I mean the amount of data get is incredible, So like it could like instantly gobble up your entire health history and give you that, but then you could go out and go, what is this specific thing, this specific cancer, this specific ailment against everybody else that has your blood type or your diet or your like, and what does it have to say? And there's no way human can do that. So I'm really interested in how it solves healthcare because you know, I'm pretty pretty into health, not so much through pharmaceuticals and doctors, but more natural But you know, I'm interested that RFK said last night that when his uncle was president in the sixties, chronic health problems in the US were six percent, and today they're sixty percent. And he said that in the US in the sixties spent zero dollars on chronic health, and today the US spends four point three trillion on chronic health. So being able to solve some of these is really big. So you founded a company, heal Well right to kind of go address this, and I'm guessing, you know, I believe as an entrepreneur, we solve problems. So what are these big problems in healthcare that you're really trying to focus on with heal Will.

Yeah, So heal Will is really just doing what we just talked about before is taking vast sums of data and it is essentially creating, you know, insights for two groups of people, you know, clinicians and doctors who are operating in clinics and the pharmaceutical industry. So you know, we talked about one of them. They're creating you know, physician co pilots, cardiology copilots basically copilots that help detect disease based on what's in the patient record, provide notifications and what we call risk stratify patients.

So basically can say, hey, look, you know.

These are these these are people who are at high risk UH in your patient record.

Mister doctor.

You know, we've scanned your roster and we've identified, you know, people who at higher risk.

Of of of of of of.

UH co op D or you know, chronic kidney disease UH. And we notice that the dosage that you're using for that critic for that person. Let's let's say that they're identified as someone who has chronic kidney disease, but they're but they're kind of underdiagnosed, meaning that they should be on a much higher dose. It'll just sort of identify those things, you know, just like the engine light, uh, when, when when A when A when a pilot is flying a plane. Uh, And and it seasoned notifications saying oh, okay, I'll clear that notification, thanks for letting me know that same thing. You know, Like these these notifications are popping up and the physician can take action.

There's so much data, there's so many things to look for.

It's very difficult for a physician to actually be able to to proactively go into the health record and identify all these things by themselves. So this is what heal Well is doing. It's identifying those types of things.

On the pharmaceutical side, it.

Is doing the same thing. It is taking data, and it is taking both structured and unstructured data same same as as for physicians. You know, this means all the different doctor nods, all the different information that's coming into the patient record, and it is finding out for the pharmaceutical industry how their drugs are doing. You know, once you get FDA approval and the drug gets out there, it's in the wild.

You know, the.

Pharmacical industry starts to it starts to get grainy as to what's actually going on. Is it helping, is it hurting? You know, you know, you know, how does adherents work? You know, So getting that kind of information back to the pharmaceutical industry, helping them find patients, finding patients. You ever noticed that FDA approvals can take an incredible amount of time just go through the process of clinical trials. A lot of that is just finding patients because it's really hard to find them. What if you could just leverage AI technologies to do that?

So those are these are the types of.

Things that Well you know does and can do, and so they have been building the AI copilots that Well Health Technologies, which is the company that I run and founded, uh you know, is using across Canada. We're the largest owner operator of outpatient medical clinics in the country and so we're treating millions of patients and this has provided us with a huge you know, productivity and efficiency and enhancement and I want to go back to something that you were saying about chronic disease. A big part of the growth and chronic disease that we're seeing is behavior.

Right.

And now what's interesting is starting to happen as a result of AI and data is physicians are starting to, you know, provide you with with recommendations on how much you should move and how much you should sleep. And these are the types of things that are contributing to the explosion in chronic disease. So you may notice I'm wearing this ring. This is called an error ring. This tracks my heart rate variability, resting heart rate, you know, and even temperature, even even even even looks at a little uh detects a little bit of moisture, and and it's able to assess you know, my movements, my activity levels, my sleep. This data starts to become a treasure trove of information. You start to now in the future, you asked you mentioned uh, Peter Demantes uh and his commentary around around around data and and and people, you know, doctors not using co pilots. Within five years, imagine being able to take this, you know, this this quality of data and plug it into the health record in addition to all of the other data that you have. This is when things, I think start to get very very interesting because you have this dramatic amount of user generated data but with but with very precise tools like this like this, uh, like this ring that you should see the amount of componentry and electronics.

In this ring.

It's it's frankly amazing. I heard the CEO of this company speak around COVID and he was saying that that his company was able to detect COVID better than some of the tests that that were out there, just basically due to the signature of you know, things like temperature, heart rate and heart rate variability and all those things that they would see.

They could they could they could.

Essentially with very high acuity, be able to identify someone who would have COVID. So this is kind of where we're going, and I think it's pretty exciting. But I think but I think it comes back to you know, you know, you know behavior, you know, everyone's looking for the magic bullet and healthcare the magic bullet is your behavior and so and and I think RFK brings up a good point and how do we how we beat this? Unfortunately has more has less to do with our with our with our with our healthcare ecosystem, and has more to do with our personal you know, commitment to ourselves in order to to to empower ourselves to better health.

And so that's a whole other conversation, but that's.

A great it's a great point though, I mean, we have to take responsibility for our health, and really it starts with us. The problem is the education, and there's no education around that. So I think, if I'm not mistaken, your company heal well also isn't just for doctors to diagnose better, but I think it also maybe helps patients as well.

Is that right?

Or I mean is it something that I could use to get better?

And certainly the yeah, I mean that's right.

Now.

We don't have a direct to consumer site or service, but that's something that that's likely where where we will head at.

Some point in time.

Right now, we're a B to B company that develops these technologies and deploys them to to to hospitals, to clinics, to the pharmaceutical industry. We help them orchestrate clinical trials. Uh, you know, and and are you know, basically modernizing, digitizing and AI enabling clinical trials so that we can speed them up, that we get we can get to that point a lot more quickly. So it's it's really the roadmap kind of applying that vector of AI to a number of different areas in healthcare.

One thing that I study technology, and I study techechnology cycles, and I noticed they always have this like dependable pattern, repeatable pattern of sort of how they roll out maybe what we'd call the diffusion of innovation. And so, you know, you have this disruptive technology, and then there's some you know, people that are against that disruptive maybe like the Ladites. We get over the chasm, and I'm just curious your take on how it's disrupting the medical space. I believe, I mean, you already have people using this, right, I mean thousands of people already using this. I could see where trade doctors would be like, oh, I can't use that AI. I've been doing this for so long. I'm curious, you know, since you already have I believe thousands, Go ahead and correct me if I'm wrong on that, but how has that been getting them to adopt this disruptive technology? And how fast is this growing or you're growing with it?

Really really good question.

So so there there are a couple of different things that I'll unpack here. First of all, there's a lot of change management difficulty with physicians that a lot of that has improved since COVID. You know, doctors were extremely initially, very fearful of any digital technology.

That would review their data.

The view from a physician's perspective was I'm going to have some kind of big brother reviewing my work to ify areas where I made mistakes. And when it comes to people's health, that's a very touchy thing and you know, unfortunately, you know, uh, doctors receive a lot of flak for that. So, hey, you made a mistake, you caused a loved one of mine to be hurt, or what have you. So so there was this sort of extreme fear that that that that I don't want my data to be scanned. I don't want anything to do with this thing. I just want to be a doctor. I want to want I want to see patients, and I want to go about my way. I think what happened with COVID is that because we went from you know, you know, very low percentage of telemedicine to very high percentage of telemedicine due to physical distancing requirements, Suddenly physicians needed technology. If they weren't on telemedicine, if they weren't trusting digital systems, if they weren't digitally enabling themselves, they were suddenly not able to practice. So they had to get a lot more entrenched and engaged with digital technologies, and I think that sort of helped them understand these technologies a little bit better and it helped diffuse some of the fears. But I also think, you know, doctors like the rest of us, are consumers of these technologies. So they're using chat, GPT, they're using all these things, and they're starting to recognize that there's enormous productivity enhancements that come with this. And I think it's somewhat generational too. Now we have way more millennial and Gen Z doctors, right, and so they operate very differently than than Gen xers. And so one of the reasons why I started well at the time is that I just I was in twenty seventeen. I was just sort of shocked to see how little digitization and modernization there was in healthcare, and I thought this is really strange. I mean, like most other industries have been entirely disrupted with this technology. And my view is, well, look it's going to happen. It just hasn't happened yet. No industry evades digitization and modernization. And so the entire thrust of the business planet well health technologies was tech enabled care delivery and supporting the healthcare practitioner with tools, understanding that they'll adopt those tools when they're ready, but also understanding that there was a generational shift. A lot of times when we look at that adoption curve, we have to recognize that it's these that these people also change over time, and and there are certain generations that are that are that are probably going to be less receptive to these technologies and certain generations and as we as we move forward, we're just going to have more adoptions just by virtue of the fact that we're consumers of these technologies.

Thinking about it from like an investment lens, I was kind of thinking about this through this as from my VC lens. I've been doing VC stuff. I have a I'm a partner in a in a VC hedge fund, a bitcoin VC hedge fund, and I you know, we're we're looking for obviously areas that are disruptive, and we're looking for sort of this convergence. When I think about back to kind of like rfks talking about like this explosion of health problems and then you have a revolutionary technology like AI that could then come in and help that, and so you sort of have this like massive growing industry that's sort of like recession proof because I mean, when you're sick, you're sick, doesn't matter what the economy is doing. So you have this massive growing industry and then you have this disruptive technology coming in. It seems pretty explosive. That's what I would think about it from a VC level. So I mean, how big do you think like this sector is of maybe this convergence of healthcare and AI.

I think it's incredibly big. I mean, if you think about it, healthcare is typically the largest component of our services economy, of our economy overall in most industrialized nations. So in the United States we're talking about depending on how you size, healthcare can be anywhere between three and five trillion dollars a year, typically with pharmacy being worth about fifteen to twenty percent of that. Right, And so now let's think about three to five trillion dollars. In reference to the defense industry, we know that, for example, the United States spends you know, a significant amount of money on national defense. So national defense is about eight seven to eight hundred billion dollars a year. So we're talking about healthcare being multiples of national defense. You know that what most when when you kind of understand the context of just how big healthcare spending is, you start to recognize that even niches in healthcare are worth you know.

Multiple billions of dollars.

You can you can you can go down rabbit holes in in the healthcare industry and find significant opportunities. You mentioned something earlier that I think I think is going to be a bigger deal and and and that is you know, educating consumers and helping them with their behaviors to improve their health. So once once people start to understand.

That their behavior is of a very big part of their.

Healthcare and and we need more and more tools to empower people to make better decisions. And I think that is a big, big business opportunity. And and I think it will involve your personal data. I think it will involve you know, personal copilots that that will help us run our lives better.

I also think that, you.

Know, we are going to see a significant rise in robotics, you know, you know, back to what you were saying earlier about you know, the disruptive potential of robots and AI, I mean it's there.

It used to be that, you know, people would.

Say, well, if you're a hairdresser or or or a dentists, don't worry.

You're all you're always going to have a job.

There's never going to be a robot that will be able to do that. You know, Sorry, not true. You know, now there's likely going to be and and and robots being developed that can essentially do anything. There's already home cooking robots available. There's already robots that you can acquire that will do housework for you. Tesla is working very hard on on solving those types of problems. But there's enormous vcs and startups and there's going to be some some winners in that space that will create multi trillion dollar companies. So I think it's an incredible space. I think it'll help a lot of people. But I think again it'll be a tool that will be used, you know, for good and bad. So we have to now worry about is my robot going to get hacked and come and kill me? I assure you that will happen. So that's a pretty scary thought, right, right, So we have to start thinking about how do we protect ourselves? You know, again, this is a tool we're going to acquire, you know, tremendous types of robots that are going to help us in all kinds of different aspects of our lives.

And then we're and.

Likely in five or ten years we're not even to drive anymore. There's going to be a robot driving and we're going to get in and we may even you know, just cars will be designed differently. They'll be designed with beds so that we'll be able to sleep if we're going, you know, for for you know, a longer commute, what have you. So, really, I mean, we're at a very interesting inflection point, I think, you know, with all this coming together, and and I when I say this, people say, well, aren't we always at an inflection point?

And say, well, not really.

I mean there are people I've heard Mark Andresen talk about this and a speech of his that had been working on this problem of generative AI for their whole lives, you know, So they went to school, they they did their masters, their PhD. And then they worked for decades working on this problem. And they never saw it come to fruition. And and and they were scientists and researchers and extremely smart people that for decades and decades were working on this and and and then suddenly it came together.

So it's a very.

It's we live in a very very interesting world, and it's about to get a lot more intriguing. I mean, as as chat GPT, as open AI drops new releases, we're going to constantly be surprised and and and you know, uh, you know, exhilarated by this. But but but also it's it's going to heighten our we should be heightening our defenses against some of these innovations as well, and and and just trying to figure out how to make them safe.

You know, I always say, like I want the I want the con unions and the efficiency of the technology. I just don't want it weaponized against me. And so there's like trying to find that balance. But going back to what you just said about aren't we always on the brink? And the answer to you said, you said no, And I agree with that. I spent a lot of time talking about cycles, and there's one cycle that I invest along and it's called I call it a quantum leap cycle. It happened about every fifty years. It's kind of more broadly known as a condroidive wave cycle k wave cycle. And about every fifty years, there's a technological revolution cycle generally, where basically there's a cluster of technologies that gets developed that leaps the world forward and drives financial markets. And so there's been five industrial revolution steam engines, railways, electricity, steel, heavy equipment, oil, oil fuels, automobiles, mass production. Nineteen seventy one was the microprocessor, internet, telecommunications, and personal computers. And now we're starting the sixth one right now. And I call this like the investing black hole. The hurdle rate at the rate of debasement is about ten percent plus we have CPI price inflation. The real hurdle rate for an investor is not the three or four percent CPI number that we're being fed. It's really the rate of debasement plus price increases. It's really about thirteen fourteen percent. When you look at all the asset classes in the world, the only ones that have beat that hurdle rate are Bitcoin and the Nasdaq. So basically tech and the reason why is the only place to really invest is in that current cycle like the last fifty years has been dominated by telecom, personal computers, and Internet. Obviously before that it was dominated by four GMG. And so I think really like bitcoin and what I'm calling Bitcoin two point zero, like companies building on around that and AI are really the only places that we should be focusing on. And so that's I write a newsletter that focuses on just the intersection of that and obviously this AI is there. So I'm curious, just from an investor standpoint, Like I said, I pound the table on this is where you want to focus your investments, what are some things that you would look at from being an AI investor, I mean using your company for an example. You know a lot of them are a very early stage. You already have customers and revenue. What are some things that you think of, you know from an investor lens that you know that we would look at through AI companies like yours.

Yeah, look, I think that I think that essentially now AI co pilots for every type of profession, right, I think are are are are going to be incredibly important. I think if you're an investor, you're now looking for, you know, where the gaps, where the white spaces where people have not been building these these these these co pilots that can they can they can take data that can create insights, and then they can they can take those insights into some kind of software and workflow and improve the productivity of someone who's working somewhere important.

I'll give you a great example.

Like insurance. Right, so in an insurance company, someone receiving those insurance claims, someone's processing them, someone's putting eyes on them, someone's making a decision around something. But it's likely related with a whole bunch of frame, a framework of decision making that the insurance company already has. So if I'm an assurance insurance adjuster, I probably processed a certain number of claims every day.

I could probably, you.

Know, significantly increase the number of claims that I could process every day by using some kind of copilot technology that was designed for me that would help improve my workflow dramatically. It's that use case against every single person who's out there doing something that that that creates an opportunity for a startup. And this is what we've seen time and time again, whether it was you know, you know, you know, the mobile computing revolution, whether it was just the Internet altogether, it was any time something new and enabling came up, eventually it started to proliferate and create efficiencies and productivity enhancements in practically any any in every industry. And I think AI is probably a more important one because of its ability to take very complex sets of data and information and create very simple insights.

That can be used by humans.

So so I think that the startup opportunity in in AI is substantial, but I think most of that has been limited to software until now. What we're starting to see is where at this kind of convergence or or or this very interesting point where now.

Robotics is his has progress quite a bit.

Right, And so we've all seen those videos of of of of that robot, uh that that you know now is doing backflips and balancing itself on on on on on beams.

And stuff like that.

Whereas like a few years ago, if you pushed it would just fall down. Right now you could you could basically take baseball bats against it. And it's gonna it's to be just fine, and it's going to balance itself perfectly, and it's going to do a backflip and a front flip and you know, land on one leg and all that is pretty incredible. So think about think about that in addition to all these insights, and you know that that that we're able to to process from data, and in addition to how we can now generate solutions and act on data, and you start to be able to see that it's it's not an unreasonable thought to think that, you know, humans may not be as useful as we were before, and so we start to have to you know, and of course there's enormous wealth creation potential in that right. And it does come back to this point that a lot of people have made in the past. You know, ultimately, you know, decades from from now, will we all be on some kind of you know, universal basic income because it'll just be really hard to compete with a robot.

I mean, it sounds.

Really star fetched, but but it'd be really hard to compete with a really good robot.

Well, it was, it was, it was it was hard for the field It was hard for the field workers to compete with a machine that can come and do the work of five thousand men too. And so you know, every technology cycle we've we've seen that same thing. So, uh, you know, when when those five thousand, when those five thousand jobs in the field were replaced with a machine, we had a problem, what do those five thousand men do? And it turns out what they went and did with science and medicine and technology, right, so what we should be doing is removing lower level tasks and working on higher level tasks and and so that's kind of kind of where I see it. But but you're absolutely right.

It's uh yeah, I mean I was just reading.

I was just reading that that that more and more surgeries are starting to happen with AI robotics. So think about that same think about something as as as important and as you know, just you're you're vulnerable. You're such a vulnerable state where your body's being opened up, so so something very important can happen, you know, tumor can be taken out, or something can occur as a result of that that operation. And yet you know they're saying that, you know, robots could actually perform some of these surgeries better and make fewer mistakes, right, so you know we're in twenty twenty four, what is it going to look like in twenty thirty four or you know, so you know it's clear where it's going. And so I think I think you know as an investor where you're applying capital. You know, you're looking at this tool and you're saying, what are the good things and bad things that can come out of this tool? And I can sort of that can inform my views of where to allocate capital, where I can see returns. What is interesting to note too, is that teams can be smaller now and achieve much bigger things than before. A lot of people don't recognize that. Like what used to be what you may have in the past needed twenty thirty forty developers with now you may be able to do with three developers just because of the power of eye technology. So that's also changing your adically, the way that investors think about productivity and what they and what they're looking for. And again that ratio isn't isn't isn't a real ratio today, but that's where it could go. It's certainly we're certainly starting to see, you know, developers become a lot more you know, valuable if they're able to leverage a eye technologies, and that's only going to accelerate over time.

Yeah, when you talk about machines doing surgeries, I mean, I mean, how many coffees do my doctor have this morning? How shaky is his hand? Maybe a robot doing that isn't such a bad idea. Yeah, So you know, I want to kind of I kind of want to wrap this up. But you know, like I said, I write this newsletter focusing on bitcoin and AI, and this is this is right there in the crosshairs. Uh. And to your point, part of the reason why I'm so interested investing in this AI stuff is to the point that you made, businesses can be so much more efficient. So you said one guy could do the work of you know, multiple people with this, And so when companies are more efficient, that means they have more profits. And when they trade at high multiples like tech companies do, so highre multiples at profit levels typically means a pretty good return for investors. But yeah, I want to I want to wrap this up. Amad, You've been such a such, such such such a help. I really appreciate all the insights that you've had. Like I said, as someone who focused on this area, I love to talk to the people in the trenches that are building this out. Go ahead and just tell us, you know, for everybody listening where they can follow up with you or the company if they want to, you know, follow what you're doing or learn more about Healwell or in the company.

Yeah.

No, absolutely, Thank you very much. It's been awesome to talk to you, and I share your enthusiasm around UH, bitcoin, crypto and how that converges with business. I actually think a lot of incentive models are going to be solved by by by combining crypto and UH and real world problems, for example, incentives around our health. You know, one of our co founders in the UH, in the Heelwell project, Brian paste Braga, you know, I.

Talked to him about this a lot.

He has a real vision that that that that there may be a token in the future that that we collect as a result of us as a result of basically executing on things that are good for us UH. You know, good good behaviors in our lives, you know, you know, go for a walk, go for a run, go for a swim. We collect tokens and somehow that gives health. But yeah, yeah, yeah.

No exactly.

Well, those types of business models are already proliferating, but I think I think they're going to get even more sophisticated with time. But look, yeah, we're Well Health Technologies.

We are.

You know, our company website is Well dot company, not not dot com, but dot company spelled out. And then heel Well dot a. I I'm the chairman of heal Well and one of the co founders of that, and we're on you know Twitter, uh, you know, Instagram, you know all the different socials.

You know, we've got handles and all those so and and you know, feel free to engage with me.

I'm just Hamid at Well and uh well Hamed at Well dot Company. And you know, it's been a real pleasure to to talk to you. Really really love the way that you approach these problems and think about them and uh you have you have a great podcast, and it's an honor.

To be with you.

Thanks so much. And you're also a publicly traded company on the Toronto Stock Exchange, I believe as well. Right, So that's well w E l l IF.

Yeah I should have mentioned that on on the Toronto Stock Exchange. We trade at as well dot t O uh and heal Well trades at as A I d X dot t O uh so so so y a I d X so a I and then d X is the abbreviation for a diagnosis, So a I d X dot t O and uh. And we we also trade on on the O t C uh so I think, wells is w you h t C F.

And uh.

Here let me for everyone listening, we'll go ahead and make sure link that in the description and the show notes down below. So make sure you go, yeah, we'll put.

In the link there. But but yeah, we trade on the OTC. We'll get you those links, those those tickers as well.

Perfect. Well, Hammad, again, I really appreciate you taking the time to talk to me. I loved, like I said, talking to the founders and the trenches. It's important for me as an investor to kind of get in and dig in. So anyway, thanks so much for for doing that, and and uh and and really just overall, I mean what you're doing to improve health because like I said, it's a it's a massive growing problem, and so I appreciate founders going and attacking a big problem.

Thank you, thank you. I really appreciate that, all right, thanks so much, thank you.

The Mark Moss Show

In 'The Mark Moss Show,' we delve into the intricate worlds of Bitcoin, investing, business, and mac 
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