If the useful life of an NVIDIA H100-vintage cluster turns out to really be three years rather than six, the capex cycle's economics invert, and the leverage that looked prudent looks reckless.
Judging by their words, AI luminaries are begging the world to force them to hit the brakes. Judging by their work, these same people are pressing down on the accelerator with every fiber of their being.
The USA has kept dribbling small amounts of military support for Ukraine because it gives the USA a great deal of leverage, the ability to both shape how Ukraine fights its war and even how European states prepare.
So, the lesson here is to bet on a system that's maximally learned and minimally constrained and leverage structure intentionally to boost performance and scaling laws both in training and in evaluation.
I mean I think like if you look at uh my colleagues work on say alpha fold that was a very specific model for uh protein folding and it was highly successful um and was able to really handle that domain quite well so that all of a sudden you now have this amazing tool and model that can give you answers to questions about proteins and their structure um really effectively um but it's not a general model it's a very specific one and there are other I domains where that kind of approach can work really well. Uh maybe in material science or chip design or things like that that uh will enable you to leverage the capabilities of a very accurate but but niche model uh to do things that are hard today.
Yeah, I mean I think if you looked at what is important in AI systems these days, you would want to know things like the bandwidth between you know your main memory system on your accelerator to the onchip memory to the um you know the multiplier unit or whatever. You want to know how much energy does it take to do a single multiplier operation.
And now I actually think with the power of agents um and AI broadly speaking, it's much closer to Goliath versus Goliath. Like I think but maybe the startup is like a Mecca Goliath that is like vastly enhanced by the power of agents and AI and you know, the the large companies are the sort of like more traditional Goliath, so to speak. But I think that startups now like if you properly embrace AI agents and um figure out the way to leverage their strengths in the most like ambitious ways, you can easily outcompete incumbents.
And the plan doc, what was bad about it is it didn't give you leverage. The plan was every single line of code that was going to change like in diff blocks and like all the new stuff to write. And so like people would review these plans. We recommended this. We told people to read the plans. We read all our plans. And then eventually I found myself like I just kind of skimmed the plans.
The governed have something the governors need: labor, tax revenue, military service, consumer spending. This dependency is the source of democratic leverage.
Was it ever the right time? No, it is never the right time to do this. If you put this off, you will eventually find yourself in a situation where you can no longer do it. You will have lost the leverage. Success will not protect you because success is what makes you a target.
because our computers are designed to be operated by other people, anyone who's an operator could buy our systems. Most of these homebuilt systems you have to be your own operator because it was never designed to be flexible enough for other people to operate.
Meanwhile, others like Spotify and Netflix leverage their dominant positions in the market to coerce creators to abandon open podcasts entirely, in favor of proprietary formats that require listeners to be on those platforms — locking in both creators and their audiences so they are stuck as they begin the enshittification process.
and even if you take a generous interpretation of 128 * 8 gig transfers, you're at 128 gigabytes a second for the same shoreline versus 2 and a half terabytes a second. There's a there's an order of magnitude difference in bandwidth per edge area.
you can make your life easier on the biology front by building better engineering tooling and the fact that that's possible is a huge deal. Like that is that is not true for most problems in biology and it gives you a lot of leverage on the problem.
Playground by Richard Powers is a strange and wonderful novel set (mostly) on a remote atoll in French Polynesia that follows the tangled lives of an environmental advocate, a sculptor, a tech entrepreneur, and a brilliant bookworm trying to escape the grinding poverty of Chicago's South Side. The richly drawn characters drive the story, but what I love most about the book is that it's a love letter to the ocean with prose that comes closer than anything else I've read to capturing what it feels like to, for example, dive a thriving coral reef.
the thing that is the biggest competitor for any new accelerator is kind of even the previous generation of Nvidia right I mean in a fleet what I'm going to look at is the overall TCO
The system matters just as much as any given experiment. Probably even more. Right. I think starting with a growth model so you have an understanding of how your company grows in the first place and which channels you're going to leverage is critical. You need to make sure that you are instrumenting your product in and out otherwise you're going to run experiments and have wonky results.
And what’s more, you use your leverage once, and that leverage has a half-life. It becomes a lot less effective the second time around because other countries, other companies are going to try to substitute away. If China uses the rare earth leverage, which I think it is now a little bit, there will be alternatives and substitutes.
So you if you look at the leverage in some of these securitization books and mortgage books if you have 30 times leverage and you're getting 20% of the profits you'll go to 40 times leverage. It's just going to it's literally will add you know 25% to your bonus.
1929, and man, history does rhyme. Too much leverage, too much risk. Everyone thinks it's going to be great. No one thinks it's going to go down a lot.
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