The Exchanges

Q the core bottlenecks. We said they're about electricity and we said they're about semiconductors. Yeah. I think when we look at like the build out of data centers today, as you said, regulation has been a big part of Preventing that in a lot of ways. Do you think Trump has done more to help or to hurt the progression of AI in the United States from an infrastructure perspective?

A Over the last few years, the US federal government has done some good things and some less helpful things. Um, I feel like clearing out unnecessary regulations has been a very good move. Um, even last year, the, uh, bipartisan Schumer AI Insight Forum, I, I, I think there are a lot of people lobbying the US government to pass stifling regulations. You know, there are a lot of hyped up AI safety narratives saying AI could lead to human extinction, which is kind of ridiculous statement. Um, uh, To try to get stifling anti-competitive regulations passed often to try to shut down open source, open weight. Fortunately, we'll beat back a lot of that, but I think the bipartisan Shroom Insight Forum did a really good job digging into the truth and concluding that America should be investing in AI rather than, you know, passing unnecessary regulations to slow it down. Um, I think Trump, uh, did a good job, um, uh, and then his whole team, David Sachs and Christian and so on, did a good job clearing out unnecessary regulations. Uh, on the flip side, one of America's huge competitive advantages has been this ability to attract talent, uh, including high school talent, as well as, you know, frankly, young talent that may not currently be high school, but could be high school in the future. And so I think, um, to the extent that America is, uh, Uh, uh, not investing as much in attracting ta…

AI assessment note: “I think Trump, uh, did a good job... clearing out unnecessary regulations.”

Q With the commoditization of the model layer, though, and the kind of opening of it, it actually increases the premium on manufacturing and the ability to manufacture at scale, which China have a much greater ability to do than the US. Do you not think that actually leads a lot of their thinking around why they want to remove the strength of US models?

A In addition to, um, increase innovation and circulation of knowledge, which the open way models helps with, um, I think that open way models is a tremendous source of geopolitical influence. So, for example, if, um, someday, you know, some kid in some developing nation, um, ask a question about a politically sensitive topic or ask, Hey, where are the national borders in this case? Or what's the history of this event or that event? The, the country of origin of the model they end up using will be delivering some answer and, you know, whether the answer is used towards one nation's values or another nation's values is actually a tremendous source of influence and soft power. Like it or not, open-weight models are a key part of the AI supply chain, and, um, uh, China releasing, you know, free, uh, uh, low-cost or free models into that key part of supply chain means it's, Really starting to build up a lead, right, in, in build up a commanding user base, and that too will be a source of, and this is why I think nations, um, with a strong media and entertainment industry. It turns out South Korea has vastly proportionate, disproportionate influence because of their leading entertainment industry. So people listen to whatever, you know, K-pop or whatever, and that buys the nation a lot of influence. Hollywood was a tremendous source of soft power For America. It paints a certain visio…

AI assessment note: “I think that open way models is a tremendous source of geopolitical influence.”

Q When does a sign turn into a big concern for you with these?

A I think, ah, you, ah, you mentioned the Sequoia article on the six hundred billion dollar problem of AI. Um, I am concerned about that. But, but it's interesting, my, my, my concern for different layers of the stack is different. So what I'm seeing is for the application layer, there is very clear ROI. I think it's fantastic. So someone else trained these models who can build applications for, you know, a 100,000 dollars or a million dollars and start generating ROI. And then I think it is, uh, calibrating to the right level of infrastructure investment that is tricky. But having said that, it is also the same time very clear that we do need more electricity, more data centers, and more semiconductors. That too is very clear. So we should be investing a lot. Uh, uh, and I'm glad we are. Uh, but what exactly is the right amount to invest? I think that's the tricky question. It should be a lot though.

AI assessment note: “my concern for different layers of the stack is different”

Q When does a sign turn into a big concern for you with these?

A I think, ah, you, ah, you mentioned the Sequoia article on the six hundred billion dollar problem of AI. Um, I am concerned about that. But, but it's interesting, my, my, my concern for different layers of the stack is different. So what I'm seeing is for the application layer, there is very clear ROI. I think it's fantastic. So someone else trained these models who can build applications for, you know, a 100,000 dollars or a million dollars and start generating ROI. And then I think it is, uh, calibrating to the right level of infrastructure investment that is tricky. But having said that, it is also the same time very clear that we do need more electricity, more data centers, and more semiconductors. That too is very clear. So we should be investing a lot. Uh, uh, and I'm glad we are. Uh, but what exactly is the right amount to invest? I think that's the tricky question. It should be a lot though.

AI assessment note: “calibrating to the right level of infrastructure investment that is tricky”

Q How should I think about that insatiable need for more compute and the improvements that come from it with the recognition that many people say GPT-V was the example that scaling laws have been reached to a certain extent and a focus on efficiency has been a transition. How should I balance this suit to seemingly differing opinions?

A So it is true that, um, token generation is getting more efficient and cheaper. In fact, um, If you look at OpenAI's, uh, open weight model, the, the, the, they actually, um, are released models that are very efficient to run. So I think they did a good job with, um, was it like a 120, hundred plus twenty billion parameters or something with, I think, 5.7 billion active. So this is a very efficient model to run. Um, but despite the cost of token generation falling, uh, our demand for it is, you know, insatiable. One interesting thing that's happened in AI is if we look at where the buckets of value, one of the big buckets of value is AI-assisted coding, and I think this harkens back to an earlier era. In a previous generation, I think Google came to dominate, you know, horizontal information discovery like web search, but there's room for lots of verticals when the internet was being built. So we wound up with, you know, Travelocity and Expedia, Fortile for travel, Bunch of folks thought out in retail, a bunch of others thought out in transportation, social media, and so on. What we're seeing now is, um, ChatGPT has such a strong consumer brand. ChatGPT seems to be the dominant player in the new, new gen horizontal information discovery. Although I think Gemini with this channel advantage through control of Android and Chrome, you know, is a serious player as well. But if that'…

AI assessment note: “despite the cost of token generation falling, uh, our demand for it is, you know, insatiable.”

Q You do a lot of interviews, Andrew. You speak to many journalists. I'm not a journalist. I've never actually had a job. Do you find the quality of interviewers that ask you questions good?

A I think media has an important role to play to curate and distillate knowledge. I think the quality of questions that reporters are asking has been very clearly trending up over time, ah, but there is still the hype element of it that keeps on distorting the information ecosystem. Unfortunately, there are financial incentives and, you know, regulatory capture and legislative benefit types of incentives to certain types of help, to certain types of hype. And it's actually one pattern that I've seen. I won't name any companies, but I find that, um, The companies with something to lose whose statements over time have become more moderated. So, you know, I, I find that as your established company, you just say more sensible things, but there are some companies that I think are at greater existential risk. Um, and I find those companies, some of those companies that I don't want to name to be the worst sources of hype because you've got less to lose. Let's just say a bunch of random stuff.

AI assessment note: “the quality of questions that reporters are asking has been very clearly trending up”

Q the core bottlenecks. We said they're about electricity and we said they're about semiconductors. Yeah. I think when we look at like the build out of data centers today, as you said, regulation has been a big part of Preventing that in a lot of ways. Do you think Trump has done more to help or to hurt the progression of AI in the United States from an infrastructure perspective?

A Over the last few years, the US federal government has done some good things and some less helpful things. Um, I feel like clearing out unnecessary regulations has been a very good move. Um, even last year, the, uh, bipartisan Schumer AI Insight Forum, I, I, I think there are a lot of people lobbying the US government to pass stifling regulations. You know, there are a lot of hyped up AI safety narratives saying AI could lead to human extinction, which is kind of ridiculous statement. Um, uh, To try to get stifling anti-competitive regulations passed often to try to shut down open source, open weight. Fortunately, we'll beat back a lot of that, but I think the bipartisan Shroom Insight Forum did a really good job digging into the truth and concluding that America should be investing in AI rather than, you know, passing unnecessary regulations to slow it down. Um, I think Trump, uh, did a good job, um, uh, and then his whole team, David Sachs and Christian and so on, did a good job clearing out unnecessary regulations. Uh, on the flip side, one of America's huge competitive advantages has been this ability to attract talent, uh, including high school talent, as well as, you know, frankly, young talent that may not currently be high school, but could be high school in the future. And so I think, um, to the extent that America is, uh, Uh, uh, not investing as much in attracting ta…

AI assessment note: “Trump, uh, did a good job, um, uh, and then his whole team”

Q Can you talk to me about the constraints around semiconductors that you think are most pressing that most people don't realize?

A First, in my career working in AI, I have yet to meet a single AI person that ever felt like they had enough compute. So, um, you know, get us any amount of compute, we will use it all up and say we still don't have enough. So this is a constraint for the last 20 years or so. But what I'm seeing is, um, with the rise of Gen AI, there are very valuable workloads. For example, AI assisted coding, you know, it's fantastic. It's making us so much more productive. But if you use, Cloud code, enough. Sometimes you get rate limited, and I find that many companies have, really have excess demand, which is a very rare problem to have, but so many people want more OM inference, want more tokens generated, and we just don't have the semiconductors and data centers and electricity to meet the demand. But, you know, there's a lot we could do with AI, um, token generation, uh, and it's frustrating when we can't, when the supply side, we can't supply enough. To people that want it, on the demand side, you know, you, you get very limited if you, if you use too much.

AI assessment note: “we just don't have the semiconductors and data centers and electricity to meet the demand”

Q We don't have Slack. We don't have Notion. Everything is custom built. You know, you're seeing the likes of JP Morgan, Goldman Sachs, absolutely refuse any ChatGPT use, building internal systems, Is that the world that we inhabit for enterprise AI adoption?

A I think we'll get there. Um, uh, so I find that a lot of enterprises are adopting OMS, you know, Chai TV and many others. Um, I think today there's still businesses that are still on-prem rather than on the cloud, but we're making progress and it'll take, actually, one thing about AI, this hype that we have AGI in two years or whatever, I think that's just ridiculous. That's just, I, I, I, for most reasonable definitions of AGI, that's just not going to happen. And just as how long are we now into the cloud era, but we still have an awful lot of on-prem jobs. Um, I think that AI adoption, it will be wonderful. There will be tremendous GPD growth is also going to take much longer than the hype says it will. I actually think that a decade from now, we will still be working to identify Valuable applications and enterprises and building them. Having said that, we will make a lot of progress over the next one or two years, but we're not going to be done, you know, even 10 years from now.

AI assessment note: “I think that AI adoption... is also going to take much longer than the hype”

Q With the commoditization of the model layer, though, and the kind of opening of it, it actually increases the premium on manufacturing and the ability to manufacture at scale, which China have a much greater ability to do than the US. Do you not think that actually leads a lot of their thinking around why they want to remove the strength of US models?

A In addition to, um, increase innovation and circulation of knowledge, which the open way models helps with, um, I think that open way models is a tremendous source of geopolitical influence. So, for example, if, um, someday, you know, some kid in some developing nation, um, ask a question about a politically sensitive topic or ask, Hey, where are the national borders in this case? Or what's the history of this event or that event? The, the country of origin of the model they end up using will be delivering some answer and, you know, whether the answer is used towards one nation's values or another nation's values is actually a tremendous source of influence and soft power. Like it or not, open-weight models are a key part of the AI supply chain, and, um, uh, China releasing, you know, free, uh, uh, low-cost or free models into that key part of supply chain means it's, Really starting to build up a lead, right, in, in build up a commanding user base, and that too will be a source of, and this is why I think nations, um, with a strong media and entertainment industry. It turns out South Korea has vastly proportionate, disproportionate influence because of their leading entertainment industry. So people listen to whatever, you know, K-pop or whatever, and that buys the nation a lot of influence. Hollywood was a tremendous source of soft power For America. It paints a certain visio…

AI assessment note: “I think that open way models is a tremendous source of geopolitical influence.”

Q If I gave you a regulatory magic wand, Andrew, What would you change that would have the most significant needle moving impact?

A America is fortunate to have a lot of very smart people wanting to come here, uh, to do really challenging, really tough problems. Um, many of our Lobel laureates are immigrants. Uh, you know, Einstein, for example, was an immigrant. I think continuing to cultivate America, um, as a place to attract great talent, to work together in, in a place In a, in a democratic nation that, that respects the rule of law. I think that would, uh, help us move ahead. Um, I think that, uh, securing the semiconductor supply chain would be very valuable as well. A lot of friends in Taiwan. I love Taiwan. Uh, and also, um, America's dependency on TSMC, uh, is concerning in case anything happens. Um, and then I think making And, and, and frankly, There's one very funny thing that happened in society, which is, um, there was recently a Pew report showing, I think, how much Americans, you know, think AI would be good for them, enthusiastic versus non-enthusiastic. And even though a lot of AI technologies were invented in America, um, a lot of people don't trust or don't like AI.

AI assessment note: “I think continuing to cultivate America, um, as a place to attract great talent”

Q How should I think about that insatiable need for more compute and the improvements that come from it with the recognition that many people say GPT-V was the example that scaling laws have been reached to a certain extent and a focus on efficiency has been a transition. How should I balance this suit to seemingly differing opinions?

A So it is true that, um, token generation is getting more efficient and cheaper. In fact, um, If you look at OpenAI's, uh, open weight model, the, the, the, they actually, um, are released models that are very efficient to run. So I think they did a good job with, um, was it like a 120, hundred plus twenty billion parameters or something with, I think, 5.7 billion active. So this is a very efficient model to run. Um, but despite the cost of token generation falling, uh, our demand for it is, you know, insatiable. One interesting thing that's happened in AI is if we look at where the buckets of value, one of the big buckets of value is AI-assisted coding, and I think this harkens back to an earlier era. In a previous generation, I think Google came to dominate, you know, horizontal information discovery like web search, but there's room for lots of verticals when the internet was being built. So we wound up with, you know, Travelocity and Expedia, Fortile for travel, Bunch of folks thought out in retail, a bunch of others thought out in transportation, social media, and so on. What we're seeing now is, um, ChatGPT has such a strong consumer brand. ChatGPT seems to be the dominant player in the new, new gen horizontal information discovery. Although I think Gemini with this channel advantage through control of Android and Chrome, you know, is a serious player as well. But if that'…

AI assessment note: “One interesting thing that's happened in AI is if we look at where the buckets”

Q If I gave you a regulatory magic wand, Andrew, What would you change that would have the most significant needle moving impact?

A America is fortunate to have a lot of very smart people wanting to come here, uh, to do really challenging, really tough problems. Um, many of our Lobel laureates are immigrants. Uh, you know, Einstein, for example, was an immigrant. I think continuing to cultivate America, um, as a place to attract great talent, to work together in, in a place In a, in a democratic nation that, that respects the rule of law. I think that would, uh, help us move ahead. Um, I think that, uh, securing the semiconductor supply chain would be very valuable as well. A lot of friends in Taiwan. I love Taiwan. Uh, and also, um, America's dependency on TSMC, uh, is concerning in case anything happens. Um, and then I think making And, and, and frankly, There's one very funny thing that happened in society, which is, um, there was recently a Pew report showing, I think, how much Americans, you know, think AI would be good for them, enthusiastic versus non-enthusiastic. And even though a lot of AI technologies were invented in America, um, a lot of people don't trust or don't like AI.

AI assessment note: “continuing to cultivate America, um, as a place to attract great talent”

Q We don't have Slack. We don't have Notion. Everything is custom built. You know, you're seeing the likes of JP Morgan, Goldman Sachs, absolutely refuse any ChatGPT use, building internal systems, Is that the world that we inhabit for enterprise AI adoption?

A I think we'll get there. Um, uh, so I find that a lot of enterprises are adopting OMS, you know, Chai TV and many others. Um, I think today there's still businesses that are still on-prem rather than on the cloud, but we're making progress and it'll take, actually, one thing about AI, this hype that we have AGI in two years or whatever, I think that's just ridiculous. That's just, I, I, I, for most reasonable definitions of AGI, that's just not going to happen. And just as how long are we now into the cloud era, but we still have an awful lot of on-prem jobs. Um, I think that AI adoption, it will be wonderful. There will be tremendous GPD growth is also going to take much longer than the hype says it will. I actually think that a decade from now, we will still be working to identify Valuable applications and enterprises and building them. Having said that, we will make a lot of progress over the next one or two years, but we're not going to be done, you know, even 10 years from now.

AI assessment note: “AI adoption, it will be wonderful... is also going to take much longer than the hype”