Jared Quincy Davis

@jaredq_

Founder and CEO, Mithril (@mithrilcompute). Orchestrating Compute. Fmr Research Scientist @GoogleDeepMind, Deep Learning Team. CS PhD @Stanford ML, Systems

Palo Alto, CA | London, UK

Joined July 2022

1,226 Following

1,830 Followers

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Jared Quincy Davis
@jaredq_
Nov 1
i recall once reading someone explain the distinction between *precision* and *accuracy* in investing precision without accuracy is analyzing the Macy's or Blockbuster org charts and financial statements in great depth to form an investment thesis without seeing Amazon and
Shaun Maguire
@shaunmmaguire
Nov 1
I hereby challenge @UnstructuredCap to a public debate How about today at noon PT? Consider this a financial duel
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UnstructuredCap
@UnstructuredCap
Oct 31
This is the type of model ur summer intern who won’t get a return offer builds. No taxes or change in working capital. Partner at Sequoia tho. Honestly I think what this really shows is the gap between the way VCs think about businesses vs how a bottoms up PE firm/HF thinks.
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Jared Quincy Davis
@jaredq_
Oct 28
Cool work, Albert and team!
Albert Gu
@_albertgu
Oct 28
I've always believed that intelligence should come from simple, general building blocks that learn their own abstractions directly from raw data; in other words, the bitter lesson. I think we're finally seeing a real step towards AI that can learn from all data. Language
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Jared Quincy Davis
@jaredq_
Sep 16
Pretty funny, but an overly simplistic take. Scaling requires capital. Scaling → smarter models → smarter models can be easier to align. Part of the reason Dario’s original safety team at OpenAI pursued scaling was that they thought you needed smarter models to be able to
Boring_Business
@BoringBiz_
Sep 16
If you truly believed in a 10% chance of human extinction in 3 years, you would not be spending your time selling and integrating it into a B2B CRM SaaS platform Watch what they do, not what they say
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Marc Benioff
@Benioff
Sep 15
Welcome Dario to Dreamforce!
Jared Quincy Davis
@jaredq_
Sep 15
For those who think AI progress is a force for good and are belligerent toward the safety community for pushing for caution and “pacing,” I want to note that the deep learning scaling revolution largely has the safety community to thank. A lot of the seminal scaling-laws work
Jared Quincy Davis
@jaredq_
Sep 15
Worth reading their full research blog. Fine-tuning open-source models to reliably outperform flagship closed-source models on specific tasks isn’t trivial. Deep ML, systems, and domain expertise on display here. Naive fine-tuning can look good on benchmarks but still be
Liam Fedus
@LiamFedus
Sep 15
We built high-throughput materials labs in Menlo Park to create a loop between experiments and models. The labs generate fresh data, the models learn from it, and then help us decide what to try next. Using only 1,300 H200s, plus months of our experimental data, we mid-trained
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