Bloomberg Audio Studios, podcasts, radio news bringing out to that special conversation that we mentioned at Bloomberg in Vest, Gary Coheneweischer, IBM and Bloomberg's Matt Miller.

Bloomberg Audio Studios, podcasts, radio news bringing out to that special conversation that we mentioned at Bloomberg in Vest, Gary Coheneweischer, IBM and Bloomberg's Matt Miller.

Let's watch and listen live. Yeah, we have right now.

Let's watch and listen live. Yeah, we have right now.

During that period of time, you had to pre program a huge database with all of the answers because we didn't have the real time connectivity to the data around the world. Today, if you were going to play Jeopardy, you would completely do it differently. You would just allow the AI machine to go get the answer instantaneously. Forty years ago, you had to sort of put the answers in the room and hope that Jeopardy asked the questions in the categories you wanted. It was easier to program all the chess moves. Today, you know, AI has evolved dramatically and I think we're all living through this. I would say evolution. I'm not sure it's a revolution evolution of AI. You know, we've gone from the concept and if you look at sort of CEO surveys or corporate surveys, you know, a year or two ago, I think it was ninety about ninety percent of CEOs said, they, you know, clearly we're going to be involved in use AIAI. And of those ninety percent, less than ten percent could actually tell you what they were going.

During that period of time, you had to pre program a huge database with all of the answers because we didn't have the real time connectivity to the data around the world. Today, if you were going to play Jeopardy, you would completely do it differently. You would just allow the AI machine to go get the answer instantaneously. Forty years ago, you had to sort of put the answers in the room and hope that Jeopardy asked the questions in the categories you wanted. It was easier to program all the chess moves. Today, you know, AI has evolved dramatically and I think we're all living through this. I would say evolution. I'm not sure it's a revolution evolution of AI. You know, we've gone from the concept and if you look at sort of CEO surveys or corporate surveys, you know, a year or two ago, I think it was ninety about ninety percent of CEOs said, they, you know, clearly we're going to be involved in use AIAI. And of those ninety percent, less than ten percent could actually tell you what they were going.

To use it for.

To use it for.

They just felt like they needed to talk about using it. Today, I think the amount of CEOs they are using AI continues to grow, but more importantly, they actually know what they're going to use it for, and the definitional outcomes of where AI can enhance your business is becoming clear. That's where they are today. I think it's going to continue to evolve to where you can use AI in your business and where the paybacks are and how you create.

They just felt like they needed to talk about using it. Today, I think the amount of CEOs they are using AI continues to grow, but more importantly, they actually know what they're going to use it for, and the definitional outcomes of where AI can enhance your business is becoming clear. That's where they are today. I think it's going to continue to evolve to where you can use AI in your business and where the paybacks are and how you create.

Real productivity growth.

Real productivity growth.

I won't geek out on productivity growth, but at the end of the day, you know, if you want to grow GDP and you want to grow your economy, it is all about getting more productivity, getting more units of work your labor force.

I won't geek out on productivity growth, but at the end of the day, you know, if you want to grow GDP and you want to grow your economy, it is all about getting more productivity, getting more units of work your labor force.

So I think about this a lot in a competitive sense. If you're a big business and you haven't figured out how you're going to.

So I think about this a lot in a competitive sense. If you're a big business and you haven't figured out how you're going to.

Use AI yet, are you too late? Have you lost out?

Use AI yet, are you too late? Have you lost out?

You're never too late. You're never too late. You know what you may be late is you may be at a competitive disadvantage to your nearest competitor because they may be able to do certain things more efficiently than you, But you can catch up quickly, so you're not that far behind. So you have to sort of figure out where the opportunities are in your business. And it depends on size, scope scale of your business, so like a very obvious place where in a bigger company. And this is something we did at IBM, and we've talked about it. We like being client zero for all of our products. You know, we did something relatively simple. It sounds simple, but it was not that simple, an HR chat pot.

You're never too late. You're never too late. You know what you may be late is you may be at a competitive disadvantage to your nearest competitor because they may be able to do certain things more efficiently than you, But you can catch up quickly, so you're not that far behind. So you have to sort of figure out where the opportunities are in your business. And it depends on size, scope scale of your business, so like a very obvious place where in a bigger company. And this is something we did at IBM, and we've talked about it. We like being client zero for all of our products. You know, we did something relatively simple. It sounds simple, but it was not that simple, an HR chat pot.

You think of what most people use.

You think of what most people use.

HR for after the day one hiring experience of what they want is, you know, they go buy an apartment, they go rent an apartment, they get some they need a reference letter, they need a reference leative. What day did I start working? How long have I worked here? What was my last year's conversation? What was my bonus? And you want that scent like that minute. And you know in a year, a year or two ago, used to call someone in HR, used to give them the information. You said, tell them where you want it sent, and you hope and pray they send it out quickly. Today you're at IBM, you will type it into a HR chatbot and in a minute you said hit send, the letter will go out. So people are actually very happy. Oh my god, I get what I want. I get all this information. You have information about your benefit and information about your healthcare. We do it all real time. We cut six hundred people out of our HR department. Now we didn't fire them, we redeployed them to places where they can be more useful.

HR for after the day one hiring experience of what they want is, you know, they go buy an apartment, they go rent an apartment, they get some they need a reference letter, they need a reference leative. What day did I start working? How long have I worked here? What was my last year's conversation? What was my bonus? And you want that scent like that minute. And you know in a year, a year or two ago, used to call someone in HR, used to give them the information. You said, tell them where you want it sent, and you hope and pray they send it out quickly. Today you're at IBM, you will type it into a HR chatbot and in a minute you said hit send, the letter will go out. So people are actually very happy. Oh my god, I get what I want. I get all this information. You have information about your benefit and information about your healthcare. We do it all real time. We cut six hundred people out of our HR department. Now we didn't fire them, we redeployed them to places where they can be more useful.

And our satisfaction scores for.

And our satisfaction scores for.

Our employees using HR has gone up dramatically because they get real time answers. So it depends what you're trying to achieve in your company. You know, there's a lot of people using AI today and.

Our employees using HR has gone up dramatically because they get real time answers. So it depends what you're trying to achieve in your company. You know, there's a lot of people using AI today and.

Code assist in writing new code.

Code assist in writing new code.

So if you're in a big code writing shop or writing new code is important to you, and you're at a disadvantage.

So if you're in a big code writing shop or writing new code is important to you, and you're at a disadvantage.

Because your competitors are using a.

Because your competitors are using a.

Code assist program and you're you're at a competitive disadvantage. You take a lot of people here on financial services industry, most banks happen to know what banks do. Most banks historically build a technology infrastructure on a sort of as needed basis, and if you go pull back the covers. They've got lots of different systems in a variety of different languages, and when you try and integrate them and have them talk to each other, it's very difficult. So every bank during the course of the last decade or twenty years tried to think, how do I get all of my software? How do I get all my systems on a common language. It was an arduous task that was cost prohibitive. Today it's not cost prohibitive. Today you can get a code assist bot to basically port one language over to another pro another language, and it's pretty flawless and how it happens. So there's a lot of places evolving today where AI is very useful, and it.

Code assist program and you're you're at a competitive disadvantage. You take a lot of people here on financial services industry, most banks happen to know what banks do. Most banks historically build a technology infrastructure on a sort of as needed basis, and if you go pull back the covers. They've got lots of different systems in a variety of different languages, and when you try and integrate them and have them talk to each other, it's very difficult. So every bank during the course of the last decade or twenty years tried to think, how do I get all of my software? How do I get all my systems on a common language. It was an arduous task that was cost prohibitive. Today it's not cost prohibitive. Today you can get a code assist bot to basically port one language over to another pro another language, and it's pretty flawless and how it happens. So there's a lot of places evolving today where AI is very useful, and it.

Depends on your I think your circumstances.

Depends on your I think your circumstances.

I want to ask you about the cost because I think the reason it was so daunting in my mind, especially for a information technology company, is I was looking at open AI and thinking, you've got to invest one hundred billion dollars to create a large language model, and only a few of these giant hyperscalers in Silicon Valley can do it.

I want to ask you about the cost because I think the reason it was so daunting in my mind, especially for a information technology company, is I was looking at open AI and thinking, you've got to invest one hundred billion dollars to create a large language model, and only a few of these giant hyperscalers in Silicon Valley can do it.

Now.

Now.

Obviously, Deep Seek, although there are questions about how exactly they did it how much it costs, shows that you can do it for far less.

Obviously, Deep Seek, although there are questions about how exactly they did it how much it costs, shows that you can do it for far less.

Well, thank you the Chinese Deep Seek for proving out what a lot of us knew in this country but no one wanted to listen to. So if you look at what we've been doing at IBM, you look at what met has been doing, you look at a lot of companies here in the United States been doing. We've been building small models.

Well, thank you the Chinese Deep Seek for proving out what a lot of us knew in this country but no one wanted to listen to. So if you look at what we've been doing at IBM, you look at what met has been doing, you look at a lot of companies here in the United States been doing. We've been building small models.

What we have found and Deep Seek sort of proved this out. The small models are much.

What we have found and Deep Seek sort of proved this out. The small models are much.

More efficient, they compute faster, they take less power, but they're not a model that can do everything. They're sort of targeted models. So the things that I was talking to you about, we have small models that are used for specific targeted goals. I think that is the future. We think that is the future of AI. We think most companies will engage with as many small models as they need to get done what they need to get done where they're using AI, and it will be vastly more efficient, vastly more cost effective for them. And I think this is the future where we're going. Look, will there be some large language models out there that are effective, Yes, but they will sort of be the catch all models for everything, so.

More efficient, they compute faster, they take less power, but they're not a model that can do everything. They're sort of targeted models. So the things that I was talking to you about, we have small models that are used for specific targeted goals. I think that is the future. We think that is the future of AI. We think most companies will engage with as many small models as they need to get done what they need to get done where they're using AI, and it will be vastly more efficient, vastly more cost effective for them. And I think this is the future where we're going. Look, will there be some large language models out there that are effective, Yes, but they will sort of be the catch all models for everything, so.

It still costs a lot of money to invest. I think Moody's estimated it's going to be two billion dollars in investment over the next five years, which doesn't seem that far off when I look at the kapex plans of these mag seven companies. You and I both lived through the Internet bubble and watched so many companies put money into paying down fiber cable and build the infrastructure the data centers of Web one point zero for a lot of CAPEX when they weren't getting a lot of return on investment, at least not for years if they ever did.

It still costs a lot of money to invest. I think Moody's estimated it's going to be two billion dollars in investment over the next five years, which doesn't seem that far off when I look at the kapex plans of these mag seven companies. You and I both lived through the Internet bubble and watched so many companies put money into paying down fiber cable and build the infrastructure the data centers of Web one point zero for a lot of CAPEX when they weren't getting a lot of return on investment, at least not for years if they ever did.

Do you see real parallels here? Yeah? Yes.

Do you see real parallels here? Yeah? Yes.

Look, as you're building technological infrastructure and backbone, you're building it based on the available what's available today.

Look, as you're building technological infrastructure and backbone, you're building it based on the available what's available today.

In what you know today, the whole.

In what you know today, the whole.

AI backbone infrastructure, compute technology, it's moving very fast. But you can't wait for version two point zero or version three point zero, version four point oh, you have to build based on what's build what's available today. What's available today will be obsolete a lot of it before it gets built, and it will get replaced.

AI backbone infrastructure, compute technology, it's moving very fast. But you can't wait for version two point zero or version three point zero, version four point oh, you have to build based on what's build what's available today. What's available today will be obsolete a lot of it before it gets built, and it will get replaced.

By newer and newer versions.

By newer and newer versions.

So there is a bunch of money being spent today, they'll have very low returns to no returns. But if you don't start investing, you'll never start.

So there is a bunch of money being spent today, they'll have very low returns to no returns. But if you don't start investing, you'll never start.

So you sort of have this.

So you sort of have this.

Prisoner's dilemma that I have to start building this data center and I think I'm going to be putting x y z chip in, but by the way it gets built in two years, I may not be putting most likely will not be putting that chip in, And the amount of power I think I need to run that data center may be dramatically less because the next chip I bet is going to be a lot more efficient than the chip we have today. So a lot of this build you can't wait for the efficient frontier because someone's.

Prisoner's dilemma that I have to start building this data center and I think I'm going to be putting x y z chip in, but by the way it gets built in two years, I may not be putting most likely will not be putting that chip in, And the amount of power I think I need to run that data center may be dramatically less because the next chip I bet is going to be a lot more efficient than the chip we have today. So a lot of this build you can't wait for the efficient frontier because someone's.

Always going to be out there.

Always going to be out there.

You have to keep building, and there will be a lot of waste to get there. I just think it's inevitable. And then you know, these AI models themselves are going to build upon themselves, and they're gonna get smarter and smarter, and they're going to optimize and re optimize, and everything's going to get better and faster and quicker, and ultimately the AI of this of the data center is going to tell you how to build better data center, how to build better connectivity, how to optimize the optimization.

You have to keep building, and there will be a lot of waste to get there. I just think it's inevitable. And then you know, these AI models themselves are going to build upon themselves, and they're gonna get smarter and smarter, and they're going to optimize and re optimize, and everything's going to get better and faster and quicker, and ultimately the AI of this of the data center is going to tell you how to build better data center, how to build better connectivity, how to optimize the optimization.

What do you do though as an investor, I mean, you know, as an IBM or as a Microsoft or as you point out, they don't have any choice, They've got to build now. But what do you do as a as a private investor or what do you do as someone who's looking at markets?

What do you do though as an investor, I mean, you know, as an IBM or as a Microsoft or as you point out, they don't have any choice, They've got to build now. But what do you do as a as a private investor or what do you do as someone who's looking at markets?

How do you analyze that? Well, it's interesting if you look at the.

How do you analyze that? Well, it's interesting if you look at the.

History and the history of technology is not that old, and if you look at you know, sort of what's going on here. Ultimately, the bigger companies are going to have.

History and the history of technology is not that old, and if you look at you know, sort of what's going on here. Ultimately, the bigger companies are going to have.

A real big impact in this now.

A real big impact in this now.

It's really and then I'll point out that all the bigger companies that we talk about today, whether it be the Metas or the Googles. You know, I remember when Facebook started, it was a really small company.

It's really and then I'll point out that all the bigger companies that we talk about today, whether it be the Metas or the Googles. You know, I remember when Facebook started, it was a really small company.

And I'm not that old. I'm old enough, but I'm not that old.

And I'm not that old. I'm old enough, but I'm not that old.

So all these big companies, I remind people, start out as really small companies. So there are a bunch of small companies so that are going to be really big companies in less in that path, one of these bigger companies can buy them out. You know, We've now got companies that can go spend on hundred million dollars in buy out a company you know, relatively easily today. So if you were looking at what you think is the most likely path, I think the most likely path is the big I don't know if it's the mag seven, but the bigger companies who are spending the most in CAPEX are the most likely winners, and they will you know, they many will.

So all these big companies, I remind people, start out as really small companies. So there are a bunch of small companies so that are going to be really big companies in less in that path, one of these bigger companies can buy them out. You know, We've now got companies that can go spend on hundred million dollars in buy out a company you know, relatively easily today. So if you were looking at what you think is the most likely path, I think the most likely path is the big I don't know if it's the mag seven, but the bigger companies who are spending the most in CAPEX are the most likely winners, and they will you know, they many will.

Fund some of these startups.

Fund some of these startups.

And almost all of the big companies have huge venture arms because they're trying to spend money in these startups.

And almost all of the big companies have huge venture arms because they're trying to spend money in these startups.

They're trying to get.

They're trying to get.

Opportunities to let creative people create, and then as those products become really valuable, they're just going to buy them and merge them into the bigger companies. So, you know, I guess my investment advice is, like, you can own some of these small companies and most are private, and they're probably interesting to own a portfolio of them. But if you ask me where I think this is going to be a decade from now, I think the bigger companies are going to dominate the space.

Opportunities to let creative people create, and then as those products become really valuable, they're just going to buy them and merge them into the bigger companies. So, you know, I guess my investment advice is, like, you can own some of these small companies and most are private, and they're probably interesting to own a portfolio of them. But if you ask me where I think this is going to be a decade from now, I think the bigger companies are going to dominate the space.

Is that part of what you're doing at IBM? I mean, do you help Arvin Krishna maybe zone in on some targets.

Is that part of what you're doing at IBM? I mean, do you help Arvin Krishna maybe zone in on some targets.

We definitely have a ventures portfolio.

We definitely have a ventures portfolio.

We're always looking for something that's on the cutting edge that fits within our parameters.

We're always looking for something that's on the cutting edge that fits within our parameters.

You know, where there's.

You know, where there's.

Hybrid cloud, open AI, quantum, you know.

Hybrid cloud, open AI, quantum, you know.

But we're very much in the open source.

But we're very much in the open source.

So we're gonna buy open source company if it fits within our parameters and we think it's got an interesting opportunity. It's in our shareholder's best interest for us to get involved in the company early, not late.

So we're gonna buy open source company if it fits within our parameters and we think it's got an interesting opportunity. It's in our shareholder's best interest for us to get involved in the company early, not late.

By the way, a little bit detached from the specific AI conversation, what do you think about the M and I M and A landscape right now?

By the way, a little bit detached from the specific AI conversation, what do you think about the M and I M and A landscape right now?

When we came into.

When we came into.

This year, me and Shanali and Katie, we're joking about an opinion writer who said, maybe there won't be that many deals because everybody said this is going to be the year you know that the regulators drop their guard and everybody can get together. Now it's starting to look like that may not be the case.

This year, me and Shanali and Katie, we're joking about an opinion writer who said, maybe there won't be that many deals because everybody said this is going to be the year you know that the regulators drop their guard and everybody can get together. Now it's starting to look like that may not be the case.

Well, that was the total market euphoria from November election January twentieth. Was deregulation, ease of doing business, the FDC, the CFDC, the SEC, everything C is going to get easier and be much more pro business and we're going to have this huge influx, this huge, massive explosion of deals of M and A, deals of IPO deals.

Well, that was the total market euphoria from November election January twentieth. Was deregulation, ease of doing business, the FDC, the CFDC, the SEC, everything C is going to get easier and be much more pro business and we're going to have this huge influx, this huge, massive explosion of deals of M and A, deals of IPO deals.

Look, we're forty five or forty six days into this.

Look, we're forty five or forty six days into this.

I don't want to judge this book by its cover, but the first forty five days we've not had an explosion of deals. In fact, probably based on what's going on in markets right now, in market.

I don't want to judge this book by its cover, but the first forty five days we've not had an explosion of deals. In fact, probably based on what's going on in markets right now, in market.

Multiples, we've probably lost deals.

Multiples, we've probably lost deals.

So I would say the calendar from January twenty today is smaller than it was. That's not a regulatory statement, that's a valuation statement. And you also have to be reminded that some of these commissioners are not in place heads of SEC. Even the FDC doesn't have a full Republican slate, it's got two Republicans too Democrats, so it's hard to get things through on to too. These things take more time, So I think some of that euphoria is still there, but I think more people are taking the approach of Okay, you're going to have to show me. It's a different environment than just trust me. I think we've gone from trust me to show me.

So I would say the calendar from January twenty today is smaller than it was. That's not a regulatory statement, that's a valuation statement. And you also have to be reminded that some of these commissioners are not in place heads of SEC. Even the FDC doesn't have a full Republican slate, it's got two Republicans too Democrats, so it's hard to get things through on to too. These things take more time, So I think some of that euphoria is still there, but I think more people are taking the approach of Okay, you're going to have to show me. It's a different environment than just trust me. I think we've gone from trust me to show me.

I want to get back to regulation in a minute, as it pretends to AI, But you mentioned productivity. You don't want to geek out on it. We haven't seen much of an impact yet from.

I want to get back to regulation in a minute, as it pretends to AI, But you mentioned productivity. You don't want to geek out on it. We haven't seen much of an impact yet from.

A on productivity.

A on productivity.

I actually have a chatbot now open next to my Bloomberg screens every morning, so make you more productive. It's I'm actually getting a lot more detail into my newscast than I would otherwise.

I actually have a chatbot now open next to my Bloomberg screens every morning, so make you more productive. It's I'm actually getting a lot more detail into my newscast than I would otherwise.

I use it as more of a glorified search.

I use it as more of a glorified search.

But we haven't really seen it boost the numbers economically, And I wonder when you think we're going to see that and if it's going to actually have an effect on jobs. You mentioned that you've moved HR people out because you can replace them with in that role with AI. Are we going to see you know, an uptick in or a loss in non farm payrolls because of it?

But we haven't really seen it boost the numbers economically, And I wonder when you think we're going to see that and if it's going to actually have an effect on jobs. You mentioned that you've moved HR people out because you can replace them with in that role with AI. Are we going to see you know, an uptick in or a loss in non farm payrolls because of it?

So we've also created you know, artificial workers, you know, So we now can create artificial workers in certain in our consulting business. We now have artificial workers who you know, will work twenty four hour days, which is.

So we've also created you know, artificial workers, you know, So we now can create artificial workers in certain in our consulting business. We now have artificial workers who you know, will work twenty four hour days, which is.

Kind of nice, just like Doge. Yeah, so.

Kind of nice, just like Doge. Yeah, so.

I don't know if I'm going to make that you made that comparison, I will not own that comparison. So let let's talk about your question. I think your question is, you know, if AI is going to be successful, are we going to see a real impact to labor and employment numbers around the world?

I don't know if I'm going to make that you made that comparison, I will not own that comparison. So let let's talk about your question. I think your question is, you know, if AI is going to be successful, are we going to see a real impact to labor and employment numbers around the world?

Let leonne in the United States.

Let leonne in the United States.

So my pretty bold answer is, and I always say this to rooms, to people like this who usually first question I get is isn't this devastating the economy? I say, look, I'll give you the rest of the time I'm up here, which is very short at this point, so it's not a lot of time. I'll give you the rest time I'm up to come up with a major technological advancement that destroyed jobs, and you can go.

So my pretty bold answer is, and I always say this to rooms, to people like this who usually first question I get is isn't this devastating the economy? I say, look, I'll give you the rest of the time I'm up here, which is very short at this point, so it's not a lot of time. I'll give you the rest time I'm up to come up with a major technological advancement that destroyed jobs, and you can go.

Back and you can take anyone you want.

Back and you can take anyone you want.

And so like, let's just take the internal combustion engine that was supposed to destroy jobs because all those people they cleaned stalls and put.

And so like, let's just take the internal combustion engine that was supposed to destroy jobs because all those people they cleaned stalls and put.

Shoes on horses, they were going to lose their jobs.

Shoes on horses, they were going to lose their jobs.

Well, but all of a sudden, the next day when we started putting internal combustion engines on the streets. We needed mechanics, we needed gas stations, we needed we needed different skill sets, different people. But all of a sudden, there were more jobs created because people could go you know, fifty miles a day or a hundred miles a day versus two miles a day, so their landscape, their business model expanded. It's no different than when the internet. Like I worked at a bank before we had email. We used to have every floor head had a person that printed the memos and put it in your mailbox and told you what time the meeting was or told you what time to go. What happened to that person who delivered the mail on the floor and printed the memos. You know, they sort of disappeared overnight.

Well, but all of a sudden, the next day when we started putting internal combustion engines on the streets. We needed mechanics, we needed gas stations, we needed we needed different skill sets, different people. But all of a sudden, there were more jobs created because people could go you know, fifty miles a day or a hundred miles a day versus two miles a day, so their landscape, their business model expanded. It's no different than when the internet. Like I worked at a bank before we had email. We used to have every floor head had a person that printed the memos and put it in your mailbox and told you what time the meeting was or told you what time to go. What happened to that person who delivered the mail on the floor and printed the memos. You know, they sort of disappeared overnight.

Now we didn't have less people.

Now we didn't have less people.

In fact, every bank, I guarantee you since the invention of email.

In fact, every bank, I guarantee you since the invention of email.

Is double its size.

Is double its size.

Why because we got more productive. We got email coverage, so we could cover more clients. We could cover more people around the world. We could communicate quicker, we could communicate faster. I think AI is the next leg in this evolution of making us more productive. So look, will there be a change in skill sets?

Why because we got more productive. We got email coverage, so we could cover more clients. We could cover more people around the world. We could communicate quicker, we could communicate faster. I think AI is the next leg in this evolution of making us more productive. So look, will there be a change in skill sets?

Yes? Will people do jobs that they hate?

Yes? Will people do jobs that they hate?

No.

No.

The machine can input data. The machine can take codes out of an operating room in a hospital and input them into the insurance reimbursement system. By the way, that job in a couple of hospitals has like forty fifty percent turnover rates because people hate doing that, they shouldn't do it. Those people in that hospital can now do a job where they try and work on recoveries and the hospital gets paid back. So I think you will see like this natural evolution of people out of jobs that they don't like, jobs with load dissatisfaction ratings, jobs that have higher satisfaction rates, that are more productive and grows the economy.

The machine can input data. The machine can take codes out of an operating room in a hospital and input them into the insurance reimbursement system. By the way, that job in a couple of hospitals has like forty fifty percent turnover rates because people hate doing that, they shouldn't do it. Those people in that hospital can now do a job where they try and work on recoveries and the hospital gets paid back. So I think you will see like this natural evolution of people out of jobs that they don't like, jobs with load dissatisfaction ratings, jobs that have higher satisfaction rates, that are more productive and grows the economy.

That's the history of every.

That's the history of every.

Other technological advancement we see. It's not overnight. That's why I call this an evolution, not a revolution. All right, and all this, by the way, we probably won't have time, but AI I believe is just a stepping stone to the real outcome, which is.

Other technological advancement we see. It's not overnight. That's why I call this an evolution, not a revolution. All right, and all this, by the way, we probably won't have time, but AI I believe is just a stepping stone to the real outcome, which is.

Quantum, which is I'm guessing you also think ten to fifteen years off, No sooner, sooner, and how soon.

Quantum, which is I'm guessing you also think ten to fifteen years off, No sooner, sooner, and how soon.

Five years.

Five years.

The strides that is being made in quantum right now are large.

The strides that is being made in quantum right now are large.

I mean there's a lot more.

I mean there's a lot more.

Look again, there's a lot of private capital going in to quantum.

Look again, there's a lot of private capital going in to quantum.

It's big companies and small companies. It's all about error correction.

It's big companies and small companies. It's all about error correction.

How quickly you can correct their how quickly you can compute the data is pretty interesting right now. So you know, as we have evolve, you know, everything in this technology space is speeding up.

How quickly you can correct their how quickly you can compute the data is pretty interesting right now. So you know, as we have evolve, you know, everything in this technology space is speeding up.

So I'll you know, five years all right, fascinating.

So I'll you know, five years all right, fascinating.

I wanted to ask about regulation because you mentioned AI is going to help us create better AI, and I wonder what else AI is.

I wanted to ask about regulation because you mentioned AI is going to help us create better AI, and I wonder what else AI is.

Going to decide to do for us. Do we need to regulate it?

Going to decide to do for us. Do we need to regulate it?

Do we need to have a heavy hand here, or is it okay to have a few South African billionaires just say like, go, I don't.

Do we need to have a heavy hand here, or is it okay to have a few South African billionaires just say like, go, I don't.

Know, I don't know what you're talking about.

Know, I don't know what you're talking about.

I'll go to chat EPT and ask that what that is.

I'll go to chat EPT and ask that what that is.

So look, the answer is yes.

So look, the answer is yes.

And I sit on a couple of these big regulatory boards around the world, so I'll do this relatively quickly. If it's a regulated activity today, if you use a it should be a regulated activity using AI. So an example of that is if I'm going to call my doctor and tell my doctor that I got a scratchy throat, a headache, a swelling of this d D and he or she puts it in a machine and they're going to diagnose my disease and prescribe me medicine. That's a highly regulated business today. The AI machine that does that and the program that does should be highly regulated. On the flip side, if when I'm working out tomorrow morning, Spotify chooses a bad song for me and I have to hit skip, which they do a lot, you.

And I sit on a couple of these big regulatory boards around the world, so I'll do this relatively quickly. If it's a regulated activity today, if you use a it should be a regulated activity using AI. So an example of that is if I'm going to call my doctor and tell my doctor that I got a scratchy throat, a headache, a swelling of this d D and he or she puts it in a machine and they're going to diagnose my disease and prescribe me medicine. That's a highly regulated business today. The AI machine that does that and the program that does should be highly regulated. On the flip side, if when I'm working out tomorrow morning, Spotify chooses a bad song for me and I have to hit skip, which they do a lot, you.

Know, I'm not sure that needs to be a regulated activity.

Know, I'm not sure that needs to be a regulated activity.

I can get through my workout in the morning listening to one bad song and skipping a bad song. So my view is, Look, we've decided what businesses are regulated. We know what business should not be regulated. We should not use AI as a wedge to regulate more businesses. On the flip side, we shouldn't use AI to take businesses today that deserve regulation and take them out of regulation.

I can get through my workout in the morning listening to one bad song and skipping a bad song. So my view is, Look, we've decided what businesses are regulated. We know what business should not be regulated. We should not use AI as a wedge to regulate more businesses. On the flip side, we shouldn't use AI to take businesses today that deserve regulation and take them out of regulation.

All right, Well, we have one audience question here on tariffs.

All right, Well, we have one audience question here on tariffs.

It's amazing how you got an other question on your card.

It's amazing how you got an other question on your card.

Does this strategy make sense to you as a way to deter illegal immigration and fent and all smuggling from Canada? No, Seriously, we've seen for a couple of days in a row, markets really come down. We've seen rates come down from four eighty to four twenty. President Trump has put twenty five percent tariffs on our two closest trading partners after he negotiated possibly the greatest trade deal in history with them, right, yeah, yes, does it make sense to you?

Does this strategy make sense to you as a way to deter illegal immigration and fent and all smuggling from Canada? No, Seriously, we've seen for a couple of days in a row, markets really come down. We've seen rates come down from four eighty to four twenty. President Trump has put twenty five percent tariffs on our two closest trading partners after he negotiated possibly the greatest trade deal in history with them, right, yeah, yes, does it make sense to you?

I mean you were there.

I mean you were there.

So look, I think what we have to understand and I'm not saying I understand this, but I think what we have to try and figure out is what.

So look, I think what we have to understand and I'm not saying I understand this, but I think what we have to try and figure out is what.

Is the objective of the tariffs?

Is the objective of the tariffs?

And that, to me, I think that's where we're a lot of us are struggling. Is the tariffs meant to make foreign products more expensive so the domestic product is cheaper.

And that, to me, I think that's where we're a lot of us are struggling. Is the tariffs meant to make foreign products more expensive so the domestic product is cheaper.

Okay, that's a good use of a tariff.

Okay, that's a good use of a tariff.

The problem is a lot of the things that we import we actually don't make here in the United States. So you can make the foreign product more expensive, it doesn't make the domestic product cheaper because we don't have it. So that's a question I have is the But if we put that tariff on, does that incentivize CAPEX to build the capability to make that product? You could argue, Okay, that's not a bad long term outcome, because look, if we took nothing else away from COVID, we should have taken away from COVID. There are some strategic needs of this country that we are just too dependent on the rest of the world for and we better figure out how to be more self sufficient on necessity goods and items.

The problem is a lot of the things that we import we actually don't make here in the United States. So you can make the foreign product more expensive, it doesn't make the domestic product cheaper because we don't have it. So that's a question I have is the But if we put that tariff on, does that incentivize CAPEX to build the capability to make that product? You could argue, Okay, that's not a bad long term outcome, because look, if we took nothing else away from COVID, we should have taken away from COVID. There are some strategic needs of this country that we are just too dependent on the rest of the world for and we better figure out how to be more self sufficient on necessity goods and items.

So you know, when.

So you know, when.

It's coming to buying personal protective equipment, we have to import it from China. We need sterile gloves and masks from China. Probably something we should manufacture in the United States. If we're worried about you know, toys and games, we can live it at them. I don't think it's a necessity items. So I think we have to figure out what the objective is. If the objective is to raise money for the government, like make that the objective, I'm not sure how you do that, and how do you do that with weighing the effects of inflation on the other side, And I think you have to think about that. So if we're just using it as a revenue raiser, it creates a higher cost of goods. It's a really regressive way to raise revenue.

It's coming to buying personal protective equipment, we have to import it from China. We need sterile gloves and masks from China. Probably something we should manufacture in the United States. If we're worried about you know, toys and games, we can live it at them. I don't think it's a necessity items. So I think we have to figure out what the objective is. If the objective is to raise money for the government, like make that the objective, I'm not sure how you do that, and how do you do that with weighing the effects of inflation on the other side, And I think you have to think about that. So if we're just using it as a revenue raiser, it creates a higher cost of goods. It's a really regressive way to raise revenue.

Because I hate to say it, like it's the.

Because I hate to say it, like it's the.

Reality of it is, poor people or less highly paid people consume one hundred percent of their paychecks. Wealthier people consume a very small percentage of their paychecks, and they have to consume their paychecks. So the things that are being tariffed, they are things that every day people buy and it becomes a really regressive tax system. I don't think we want a regressive tax system. I'm the first guy here that's going to argue for a progressive tax system that be rich people need to pay more in this country. They should pay more, and they do pay more today. I don't think we want to with that around you, terraff. So to me, the question is what is the objective here? Like there may be a real robust, bona fide reason to have terriffs.

Reality of it is, poor people or less highly paid people consume one hundred percent of their paychecks. Wealthier people consume a very small percentage of their paychecks, and they have to consume their paychecks. So the things that are being tariffed, they are things that every day people buy and it becomes a really regressive tax system. I don't think we want a regressive tax system. I'm the first guy here that's going to argue for a progressive tax system that be rich people need to pay more in this country. They should pay more, and they do pay more today. I don't think we want to with that around you, terraff. So to me, the question is what is the objective here? Like there may be a real robust, bona fide reason to have terriffs.

I just don't know what we're trying to achieve, and you would know.

I just don't know what we're trying to achieve, and you would know.

I feel like anyway there's a thoughtful answer, and I appreciate your time.

I feel like anyway there's a thoughtful answer, and I appreciate your time.

Thank you, thank you, thanks so much. Possible

Thank you, thank you, thanks so much. Possible