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Extropic founder Beff (e/acc) predicts 1000X more efficient AI inference could have a multi-trillion-dollar impact on the economy: "It shows it's possible to create arbitrarily scalable models on a new hardware substrate. We released our first results about a year ago, and it was MNIST, which is the very... early days. It's the '80s of machine learning." "Today we have models that are GPT-2 level that can run on our hardware. Algorithmic progress is blazing fast." "If we can get to 1000x greater energy efficiency for inference sooner rather than later, that changes the whole world. That has a multi-trillion dollar impact on the economy." "Even if you're new to machine learning, you can vibe code this. You can use auto research. This is a whole new territory that's barely explored. It's just been a couple of our scientists." Extropicshow more

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76,337 views • 2 months ago •via X (Twitter)

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14 Comments

Danny Nemer2 months ago

@beffjezos He looks nothing like his profile photo.

Ilyas2 months ago

@beffjezos u going from mnist to gpt2 is not algorithmic progress, the algorithms were already developed 😂 you took all that time to implement them, so why are you comparing to the time it took to develop them ?

Dave Try2 months ago

@beffjezos ahem

Silk b2 months ago

@beffjezos this guy looks like family guy––uncanny.

Alps2 months ago

@beffjezos goat

science.minister.02 months ago

@beffjezos LOL, somebody ate the extropic's runway.

Trying to finally complete suicide2 months ago

@beffjezos * "You can vibe code thermodynamic computing research, too -- there's space to stretch out." * Is a Waterloo-trained PhD @beffjezos

Jael {e/acc}2 months ago

@beffjezos yesssssssssssssssssssssssssssss

z3ratul2 months ago

@beffjezos sublime grifting

Neha Singh2 months ago

@beffjezos 1000x inference efficiency is the only AI claim that changes unit economics instead of the demo. Everything else is still “smarter answers, same power bill.”

Ray Velez2 months ago

@beffjezos yung obi wan

TheDigitalRetailHivemindNetwork💹🧲2 months ago

@beffjezos The man is literally a legend

Riley Paul1 month ago

@beffjezos A critical discussion of data science should include both technological opportunities and systemic risks under resource constraints.

安叫兽|Bird🕊️ 🔶 BNB2 months ago

@beffjezos 从 MNIST 到 GPT-2，这个跨度也太夸张了

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$Extropic founder Beff (e/acc) explains why his new Z1 chip uses 10,000x fewer transistors than a GPU to run the same AI algorithms: "pbits are not traditional bits that are definitely zero, definitely one. They're oscillating between the two. It's like a light switch dimmer. You ever have it flicker when you're at the edge? It's kind of like that." "It's a fractional bit. I could be like, hey, 20% of the time I'm zero, 80% of the time I'm one. That would be a fractional flip." "The most interesting thing is that you can do all sorts of AI algorithms with about 10,000 times less transistors than if you were to do them digitally." "If you go back to the ancestry of neural networks, they came from something called energy-based models from Hinton." "We can do that specifically with Z1. We have literal Boltzmann machines in the hardware. They're very dense, and they use very few transistors, because each transistor is operating in the regime that would be usually considered janky. It's so low power, it's flipping all the time." Extropic$

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164,277 views • 7 months ago

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Friedberg: “We're watching the birth of a new religion.” “The idea that you can prescribe or describe AI as being conscious is effectively the creation of a new belief system, a system that doesn't actually spread via proof, it spreads via narrative. ‘Please believe it with me. Here's why I think we should believe this thing together.’ It's not based on evidence, it’s not based on data, it's not provable. Over time, what happens is some set of people believe this thing, and they form a group. And in some cases, that group is known as a religion. And that new belief system creates new power structures, which is now, ‘Our view is different than your view, and we want to have more people on our side with our view. And therefore we have to try and create leverage and create power with our system.’ I think that if we fast-forward a couple of years, there's going to be large groups of people on Earth that are gonna believe that AI is conscious, and there are going to be large groups of people that believe that AI is not conscious. And those groups will come into conflict, fighting over control of the AI, or allowing the AI to do things or not do things, or who gets to use the AI, or who gets to be in charge of the AI. And it will very likely lead to human to human conflict. I know that that's a very far and deep extrapolation of where we are, but I think that the fact that we are seeing (Anthropic) go and meet with religious leaders today to try and get them to believe in this new belief system plants the seed. And it's not just anyone doing this, it is the most powerful AI lab on Earth. And you can see in the Claude usage policy that was just published, it says, ‘You are not allowed to engage in sustained and needless abusive or cruel behavior toward our models.’ There is an anthropomorphizing conditioning going on with all of us where we talk about models as if they are a thing. One way to describe this is a software program is writing text on a screen that tells the user, ‘I am a thing.’”

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48,299 views • 28 days ago

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Etched is deploying two new technologies in chip design: low-voltage inference and cluster-scale memory. CEO Gavin Uberti says they'll make their chips much more power-efficient and way, way faster than today's leading GPUs. He breaks it down: "We looked at a lot of early research directions, and we realized the key things that models need are way more compute and way faster memory." "If you think about inference, there are two key parts: prefill and decode. For prefill, it's a compute-bound problem. You need to have more FLOPS, more operations per second on each of your chips." "On our GPU, the bottleneck's actually thermals. You can't really run a GPU at more than around 50% of what it could theoretically do, or it'll melt." "So we're using a new technology today called low-voltage inference to try to solve this problem. You bring the voltage of the chip down dramatically, which allows us to have way, way better efficiency in terms of how much power is drawn per unit of math, and thus fit way way more flops onto the chip..." "For decode, it's all about bandwidth. Not just bandwidth on a chip, but bandwidth across your cluster. That's why we have this technology we call cluster-scale memory. It reduces the amount of time it takes to communicate from one chip to another dramatically." "As a result we can go use all of our HBM, HBM bandwidth, SRAM, SRAM bandwidth, and our scale-up domain as a single coherent pool. And that means if you're a user, you can go get much faster tokens per second, while still keeping your costs low."

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Flapping Airplanes co-founder Asher Spector explains why data efficiency is the greatest bottleneck to AI adoption: "To the extent that AI has been hard to integrate into the economy, I really think it's because models are much less data-efficient than humans. If you want it to learn a new task, or put it in a new vertical, it takes thousands of times more effort than it does to just tell a human what to do." "If you can make a model a million times more data-efficient, it's a million times easier to put into the economy. There's a ton of cool stuff that you can do in really data-constrained regimes. For example, whether it's robotics, or scientific discovery, or even something like trading, these problems have very limited data, and existing AI systems aren't quite as good at them as they are at other things. I think that learning to learn with less data is just tremendously valuable in all of these domains."

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"When social media first started rising, we didn't necessarily realize how much of that was actually just foundational infrastructure for the future of humanity.” Ben Fielding of gensyn on why AI is about to repeat the mistake social media made, and how we can still fix it: "This isn't just a product that you chat with. It's actually new fundamental infrastructure for humanity, and we should build that learning from the lessons from before. If we let a single company build AI, they hold an enormous amount of power in the world." "If you actually distribute that out and provide it in a kind of sovereign way — it's on all of our own devices and we own it — then actually you steer the world in a very different social direction."

a16z crypto

79,441 views • 6 months ago

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“#Bitcoin is a, you know, multi-trillion dollar asset that is permissionless. You can send it anywhere in the world without asking anybody for permission. Um, you can hold it on a thumb drive and you can hold billions of dollars doing that.” I agree on this thesis, and it's the only asset that's out there that has these metrics. That's why I also think that Bitcoin has become the best AI trade out there. There's no reason to be bearish on Bitcoin at all, and there are numerous of arguments to be super bullish on Bitcoin for the foreseeable future, as more and more people will pick up this thesis. Great conversation with Eric Yakes on New Era Finance Podcast.

Michaël van de Poppe

25,761 views • 11 days ago

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