BUILD AI TALENT

“If you have a train that's about to get faster and faster and go exponential, the only thing that you really need to do is get on it. And once you get on it, you'll figure everything else out along the way. And so to predict where that train's gonna be and try to shoot a bullet at it or predict where that train's gonna be and it's going exponentially faster every second and go figure out what intersection to wait for it, that's impossible. Just get on it while it's going kinda slowly and go exponential along the way.”

“You're talking to somebody who represents the American dream. My parents didn't have any money, sent us over here. We started from nothing. You guys know I, you know, bust tables, wash dishes, clean toilets, and here I am. This is the American dream. President Trump knows that. We want legal immigrants.”

“I think companies that have built software poorly and just sell that software are very vulnerable. The bar for quality of software is going up rapidly. If you really hate some piece of software that you're using and it's just software, it doesn't have some deep sort of proprietary data, proprietary source of value, it will get replaced. Like, there's no reason why not. It's long overdue to get rid of bad software.”

“Lareina, I live in San Francisco, and this is a little bit about the way the technology trends feel. You sort of have to look back because things become so normalized so easily. So there are a bunch of autonomous vehicles driving around San Francisco, and it used to be like, wow, that car has no driver, right? And I've told this story before, but our young daughter saw a taxi go by, and I had to explain to her what a taxi was. And she said, oh, that's like a Waymo with a driver.”

“this week, I spent doing store visits and distribution. And part of the thing which I found very useful is that, you know, it makes it very easy to connect with people. The live translation capabilities, like if I do this a decade ago, then I would always be accompanied with the translator, now I'm just accompanied with my phone with super cool translation abilities. And I'm able to connect with the nations who don't speak English. And I'm able to understand essentially how the business process is running, with instructions which are all written in Bahasa, as same as in India.”

“if you look at the future of bioengineering, for instance. Now, by the way, that's not just life sciences companies, it's not just pharma and cynical companies. I mean, the amazing thing is when you can program life, you can start to create new materials. And so what does that mean? Everything from apparel, artificial spider silk in order to create fabrics, to agriculture, again, incredibly important all across Asia, for instance, and whether or not it's being able to develop crops that can deal with climate change and or just increase the nutrition and as well as the taste of different crops.”

“did we find some things that really popped this year that we, for example, added agentic AI? Again, we don't think this is just going to be a one-year thing, but I think all of us have been talking about agents a lot quite recently. And we think we're just starting on that journey and many of our clients are just starting on that journey. So certainly while AI has been with us all the years that we've been studying trends, this year the idea of agents, this idea of foundation models acting in the world, doing things that are more autonomous and more multi-step, that's something that clearly came to the surface here as well.”

“I think the net IQ of the world is about to go up like 50 points. Like we're surrounded by people—not in Silicon Valley, of course—where the average IQ is still 100. I think the average IQ with AI in your ear at all times is about to go up to 150, which is like north of the genius definition. Very, very soon, the willingness to put up with random, obnoxious things like low quality or crappy terms or products that pretend to be something they're not is just going to get flushed out very quickly.”

“Majority of American banks derive a disproportionate percentage of their income from late fees. A late fee was obviously conceived as a means of slapping your wrist and saying, like, if you're going to be late, I'm going to remind you. At some point, someone said, wait a second, that's 100% gross margin product. It's better if you're late a lot, because then I'll make more money, and it cost me nothing to create that revenue line. Affirm was founded in many ways to fight all of that and destroy the ridiculous and the exploitive.”

“With LLMs, the barrier to entry into an area of programming that you've never done before is nil. This time around, I'm like, well, I can just ask my favorite agent to go research this stuff and set it up for me, and then I can just focus on exactly the functionality that I want and the implementation quirks that I'm interested in. Reconciling this opportunity where coding is fun again and easy again with the need to run a big company is a lot of fun.”

“Of the 25 sell side analysts on Wall Street who cover your stock, if I look at the consensus estimate, it basically has your growth flatlining starting in 2027. 8% growth 2027 through 2030. That is the 25 people in their only job. They get paid to forecast the growth rate for NVIDIA.”

“Don't wait on the sidelines. A lot of times business leaders say, wow, that's really interesting. Maybe I'll watch someone else run that play first, and then I'll be a fast follow. Quite frankly, there have been many technology eras where that is absolutely and has proven out to be the right thing to do. But in this instance, over the last couple of years, really since Chat GPT was released, I don't think you can wait on the sidelines. So you just got to get in the game and run the ball, and you got to compete to win.”

“Everybody's power limited. And let's say, you were able to secure two more gigawatts of power. Well, that two gigawatts of power, you would like to have translate to revenues. So your performance or tokens per watt was twice as high as somebody else's token per watt because you did deep and extreme co design. Blackwell's 30 times. So you've gotta give up 30 x revenues in that one gigawatt. It's too much to give up. So even if they gave it to you for free, you only have two gigawatts to work with.”

“the super app ecosystem nature of Asia. So if you look at China, which has got a large number of super apps, if you look at Korea, which has got a super app, if you look at Indonesia or India with their own versions of super apps, then these are actually driving very significant consumer behavior given the nature of demographics of Asia. The second thing is ultimately AI comes down to, and both Michael and Lareina spoke about this, the chips and the semiconductor stack. Majority of the stack is being built in Asia.”

“The annual release cycle. The token generation rate is going up exponentially. And the customer use is going up exponentially. So the first thing is because the token generation rate is going up so incredibly, two exponentials on top of each other, we have to unless we increase the performance at incredible rates, the cost of token generation will keep growing because Moore's Law is dead.”

“I heard from a Chinese researcher leading one of our leading labs in The US that three years ago, 90% of the top AI researchers graduating from universities in China wanted to come to The United States and did come to The United States to work in our leading labs. And he guessed that today, that's closer to 10 or 15%. So seen a precipitous drop.”

“So I'm gonna start with it's a great start. And the reason for that is this. That implies I don't I hope it's not the end, but I think it's a great start. America has one a singular brand reputation that no country in the world has, and no country in the world is in the position or in the horizon to be able to say, come to America and realize the American dream. What country has the word dream behind it?”

“I think that OpenAI is likely going to be the next multitrillion dollar hyperscale company. K. I think you and I... If that's the case, the opportunity to invest before they get there, this is some of the smartest investments we can possibly imagine, and you gotta invest in things you know.”

“Some of the things I heard, they could never build AI chips. That just sounded insane. Two, that China can't manufacture. China can't manufacture? If there's one thing they could do is manufacture. And three, they're years behind us. Is it two years, three years? Come on. They're nanoseconds behind us. Nanoseconds.”

“That general general purpose computing is over, and the future is accelerated computing and AI computing. And so the way to think about that is there's how much how many trillions of dollars of computing infrastructures in the world that has to be refreshed. And when it gets refreshed, it's going to be accelerated computing.”

“let me take Agent EKIS as an example. It increases complexity in two levels. It increases essentially technical complexity. How do I manage essentially accuracy of a process with multiple agents interacting with each other, each of which is probabilistic and a 1% error may propagate to a 25% error at the end of the process? So how do I organize for this, which is the technical complexity? The second complexity is organizational complexity. We are very excited about agents, but what does the organization structure of the future look like? Like, do we have agents who are acting as employees working together with humans?”

“Socialism sucks. It is terrible. The only people who do well in redistribution of wealth are the ones doing redistribution. It's fundamentally corrupt and there's not enough bad things I can say about socialism. So I think capitalism works exceedingly well, especially when the competition is encouraged and allowed to flourish. We've had thousands of years to evolve a fairly good economic model, and the US is most certainly 1A in the right way to do it.”

“I underestimated. Let me just go on record. I underestimated. We we now have three scaling laws. We have pretraining scaling law. We have post training scaling law. Post training is basically like, AI practicing. Practicing a skill until it gets it right. And then the third is inference. The old way of doing inference was one shot. But the new way of doing inference, which we appreciate, is thinking.”

“when we think about cloud and edge computing, five or six years ago, we spent a lot of time thinking about it. One thing I'd like to say is those scientists and engineers have not stopped thinking about innovation. For example, as we think about GPU-based clouds, AI-based data centers, there's some really interesting advances in liquid cooling. You might say, well, why is that a hidden gem? Well, when you start to have the number of data center growth that we're anticipating, I believe data centers are growing 30 percent year-on-year. I mean, it's an astounding trend of demand, especially if I just think these AI systems are hungry hippos. They need a lot of compute power. That's really hot.”

“For every generation of new frontier technologies, as hard and as fun as it is to talk about the speeds and feeds and all the technology, almost 80% of the challenge is on the organizational side. It is around change management. It is around aligning for digital, for AI. We've talked about rewiring organizations, and it is matching your technology strategy to your corporate strategy. It's having the right talent in place. So the tech stack is important, having the data is important. But then how do you change your incentives? How do you change your culture? How do you change the way you operate?”

“The most important lesson is always the team. It is sort of the Alpha and Omega success or failure of a company is the team. And there's an art form to building a company with it. The corollary to the team is the fact that just having a bunch of brilliant people is not actually enough. You need to organize them, you need to give them a mission, you need to give them a way to pursue that mission that feels true to them, but also aligns them all together, which is kind of what leadership is all about.”