The thing that's really interesting about the AI moment is that, unlike prior technology cycles, the hyperscalers themselves are the ones funding the build-out. So you don't have the same risk of a capital cycle bust that you had in, say, the fiber buildout of the late '90s, where it was funded by debt and then the whole thing collapsed.
China has demonstrated a willingness to forego money in the name of the common good. In the name of protecting workers and protecting labor. And so even if China is more structurally exposed to AI, even if that is the case, my assumption is that the Chinese government will bend the economy to its will in order to protect Chinese workers. What I know about America is that the total opposite is true.
Bezos argued that if AI makes it cheaper, faster, and easier to invent things, employment will ultimately rise because even though you're shrinking the number of people needed by 10x, the technology will create more than 10x as many opportunities.
You'll hear Sundar say he realized he needed to rethink how Google worked a few years ago in response to ChatGPT, and he made a lot of executive changes and big decisions to get the company in a more aggressive posture.
So you have like Tim Cook operationalizing the company, making so much money from the app store, building the business, but at the same time, he just happened to be the CEO during the greatest AI winter ever, basically from 2011 to 2022, 2023 when we started getting LLM, started getting chat bots.
You have this bookending of Siri on both sides of Tim Cook's career where sort of nothing happened in an interesting way, you know, but the stock did fantastically well.
One of these days we think that we might reach what's called the chat GPT moment for humanoid robots. That's when you can give a humanoid robot pretty much any command under the sun. They will think how to fulfill the command and then they'll do it for you. And if we do ever get to that stage, um then we are in a very very different world.
While uh the US spends 12 times more on compute this from the private sector versus the Chinese private sector uh China is spending 42% more on the robotic sector uh than the United States and apparently this gap is going to widen so this is two very different uh I would say modalities but I think that the robotic race, especially the AI component of it, uh, is a really exciting one and it's where China actually has distinct advantages, not just in the hardware, but potentially the software, too.
Your PR team will have many heart attacks uh because you're not in the world of deterministic outputs anymore. So that's going to be a big cultural shift for Apple I think in this uh non-deterministic stochastic uh AI era.
we also talked about Microsoft's relationship with OpenAI, how Mustafa is thinking about all the negative polling and political pushback around AI right now, and whether any of the consumer products are good enough to overcome it.
AI's capex boom is the second largest share of use GDP in history. bigger than the railroads, second only to the I think the Louisiana purchase, and there's the build out of the electrical grid, the highway system, uh the Apollo program, although that wasn't very big, and then the internet and sort of the telco infrastructure.
AI is not built to do that ever. I mean the the the the tool itself is built to give you the most predictable outcome possible, the antithesis of what we're trying to do when we make a TV show or a film.
The big opportunity for us is to use AI to make every single driver a top-rated driver and make every single eater a top-rated eater, because we have data that no one else has. We have 150 million people who are using our platform on a monthly basis, and we understand exactly what they want.
Sinofsky explains why AI may fundamentally change how personal computers are designed, and why local inference could become increasingly important as AI workloads grow.
AI's capex boom is the second largest share of use GDP in history. bigger than the railroads, second only to the I think the Louisiana purchase... unlike past tech booms, Facebook, Instagram, Door Dash, it's fundamentally a supply side story about making chips, building data centers, and powering them. It's money creating demand for energy, not the reverse.
Management is an ability to soften the chaos created by leaders. The notion that your AI is going to bring everybody in and they're not going to need to have contact with anybody else and the AI will manage them, tell them what to do, and at the end of the year give them their performance review and a bonus. Even if that was possible, which I don't think it is, it's a nihilistic, [ __ ] up vision of the world.
today's AI companies are scaling faster than any previous generation of startups, and why the eventual outcomes may be significantly larger than most investors currently expect
For the first time, we have such a common infrastructure powering all of them with our Gemini models and the underlying AI infrastructure. So we are more able to, with intent, do things which cut across things.
the two physical constraints that in Gavin's view will dictate the next phase of AI. On power, he thinks the near-term shortage starts to ease in 2027 and 2028 as new sources of energy come online, and that orbital compute solves it in the long term. On wafers, he explains what is different this time from the dotcom bubble and why TSMC's capacity decisions may be the single most important variable to watch.
This is a story about what happens when you combine real human data with AI, and why that combination might just be the future of how companies make their most important decisions.
AI is making every little step of entrepreneurship slightly easier, like slightly easier to incorporate, slightly easier to create a contract or to hire somebody, slightly easier to create an ad, and then you add all of that together.
The thing that started as like Elon sort of being like I want to buy Twitter is now like a Neol with a massive supercomputer data center and a coding agent and code review for the age of AI because don't forget they own graphite now or potentially will uh and and and a social the space review
the purpose of AI should be to actually help people do things they're trying to do by either augmenting their intelligence or collaborating with them as an intelligence.
The purpose of AI is to empower humans with machine intelligence. As machines get smarter, we get smarter. I call this humanistic AI, artificial intelligence designed to meet human needs by collaborating and augmenting people.
If you can do it and then I can do it and then Tyler can do it and then and then anyone with access to a coding model can build it very quickly we're going to erode each other's markets and trade market cap very quickly
Any system, particularly one that uses AI, will only ever be as good as the data that feeds it. And if they are drawing on a database that is old, the AI, if it's set up that way, can't do anything about that.
It's a move really from the education a lot of us were familiar with, which was everyone sitting on the mat learning together, progressing as one, to actually adapting to the strengths and weaknesses of an individual student.
I think it would be helpful for the industry to refocus some messaging on not AI is going to cure cancer, but humanity is going to use AI to cure cancer and do a number of other things, right?
The speed of which AI is changing we're not adapting our society fast enough... the biggest issue confronting our country today and other countries is the speed of which this change is occurring is society moderating that fast enough?
Compute is still growing exponentially. But AI adoption curves often look like S-curves... there's going to be deceleration. So OpenAI shot up to basically a billion MAU, monthly active users... that curve is slowing down. There's just no way you can be like, yeah, actually, we're expecting 10 billion ChatGPT users next year because there aren't 10 billion people.
The history of technological progress and its accompanying regulatory frameworks teach us that our future with AI and robotics won't only be decided by these large, sweeping philosophical discussions, but through practicality, through the answering of thousands of practical questions that arise from the simple minutia of sharing everyday life.
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