dreams do come true 🥹. excited to see our work (w/@JonSaadFalcon, @HazyResearch, john hennessy and @Azaliamirh) feat. in a major way in @FT. the world is becoming increasingly less dependent on centralized cloud ai. we are just getting started 🚀🌖
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had a blast writing this with @JayaGup10 & @JonSaadFalcon. it’s time to start righting sizing 🫵 intelligence spend and maximizing your revenue per watt (s/o @BenBajarin)
don’t overpay for intelligence 🙌🏽
couldn’t agree more @BorisMPower
This is likely to be the new Moore’s law, and the right thing to measure.
So far it seems to be much more aggressively growing than Moore’s law, as it combines hardware and software improvements in a multiplicative way!
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18x improvement in intelligence per joule in 16 months is a insane @amasad.
The interesting part is a lot of this improvement has been attributed to model efficiencies.
A good chunk of it will be hardware, given that the chip you run the model on sets the floor for joules per token before you write any optimization. Look at May 2024
IMO, the next order of magnitude on this chart over the coming years will come from purpose built inference hardware, not just better kernels.
Great research from @Avanika15 and @JonSaadFalcon.
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🚗💨 pull up to see @JonSaadFalcon talk all things local ai, local-cloud harnesses & @OpenJarvisAI
Signup below for next YC Paper Club - "Harness Edition"
Killer Lineup:
- @sethkarten - Prime Agent @PrimeIntellect
- @beyang / @sqs - @AmpCode
- @josh__france - QM @ycombinator
- @JonSaadFalcon - OpenJarvis
- ?
One more slot for speaker. Who should I ask?
8.26 5pm-9pm MV
Also, fresh look for paper club!
100% credit goes to @eve_bouff!
Aiming for: ... 2am, full team, in lab, tryna meet May 6, 2026 AoE deadline, paper not compiling-kinda vibe..
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Intelligence-per-joule is increasing quickly because models and chips are improving and the gains compound. Though demand for inference is growing even faster.
@Avanika15 @JonSaadFalcon @HazyResearch
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ipj and ipw ftw 🙌🏽. lfg @elonmusk
Intelligence/Joule will keep improving
hard agree with @amasad —@JonSaadFalcon and my research indicates that intelligence efficiency (intelligence per watt) is rapidly improving and we will definitely *not* need data center scale compute to run agi!
links to research in comments below 👇
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ipw ftw 🙌🏽 .
@JonSaadFalcon and i have been studying this for a hot sec. links to research in comments below 👇
Intelligence per watt is all that matters asymptotically
pushing the limits of intelligence per gigawatt🥹. lfg.
I believe everyone should have access to superintelligence, and I wrote a long piece about Meta's philosophy and values for building a positive future for everyone.
lfg @finkd! hyped to supercharge my local @OpenJarvisAI agents with glimmer 🙌
let your local agents cook 👨🍳 ->
Today we're also opening the weights for Muse Glimmer, a great 30B parameter dense model that can run locally. Soon we'll also release the weights for Muse Spark 1.2, our latest foundation model. Meta is a strong supporter of open source and I'm proud of these releases. Congrats to @alexandr_wang and the MSL team for all your great work on these models.
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on a mission to make intelligence too cheap to meter 🚀🌖
@JonSaadFalcon and i had a blast talking about ipw and intelligence efficiency w/the 👸🏽 @JayaGup10
link to full podcast in comments below
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