Bay Area Data Science Community: Don’t miss our first #ML Meetup! Join us next Tues at 5pm for food, drinks, and an engaging fireside chat with @DalianaLiu and @w4nderlus7
, CEO of Predibase and founder of @ludwig_ai
. Save your spot:
RESEARCH
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Bay Area Data Science Community ML Meetup Fireside Chat
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Appliance Mode for Training Massive ML Models Introduced
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ICYMI we recently had a developer community meeting where we introduced our Appliance Mode for training massive ML models. You can watch our recording here: https://
hubs.li/Q01rkJ9S0 Want to join our next meeting? Sign up here! https://
hubs.li/Q01rkHTb0 #ML #machinelearning #ai -
Runway’s Journey: From NYU Thesis to AI Leadership
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I've had a front-row seat to Runway's evolution from the time it was just @c_valenzuelab's thesis project at NYU in early 2018. Very few people had the foresight back then to start building towards something like this. Super proud of the whole team for where they are today. https://t.co/cbJihnSo7V
— Gene Kogan (@genekogan) 3 novembre 2022I've had a front-row seat to Runway's evolution from the time it was just @c_valenzuelab
's thesis project at NYU in early 2018. Very few people had the foresight back then to start building towards something like this. Super proud of the whole team for where they are today. -
Empathetic peer review in AI research publication process
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Usually, we think of AC rejections and being cold and uncaring. But this AC was quite empathetic, picking up on a self-critical comment from the author and supporting them in their journey. https://
openreview.net/forum?id=A6O79
ipjlJC
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Paper Rejection Despite Acceptance Scores Highlights Review Process Issues
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The paper was rejected despite all scores being "Accept" or better, because the AC says they didn't compare with some other papers, which were never mentioned before. The AC should have raised this to the authors earlier, or figured out the relevance with help of the reviewers.
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Tom Burns Shares Thoughtful Response to Peer Reviewers
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Tom (
@tfburns
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Model Available in Lean VSCode Plugin for Researchers
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We’ve made our model available through the Lean VSCode plugin to allow researchers to explore the capabilities within the Lean environment. We hope you’ll build on this work as part of our shared pursuit of rapid progress in this exciting field.
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HyperTree Proof Search Advances Neural Theorem Solving
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Using HyperTree Proof Search we created a new neural theorem solver that was able to solve 5x more International Math Olympiad problems than any previous AI system & best previous state-of-the-art systems on miniF2F & Metamath.
— AI at Meta (@AIatMeta) 3 novembre 2022
More in our new post ⬇️Using HyperTree Proof Search we created a new neural theorem solver that was able to solve 5x more International Math Olympiad problems than any previous AI system & best previous state-of-the-art systems on miniF2F & Metamath. More in our new post
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LLMs Generate Convincing but Wrong Completions Often
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this is an issue I also have with copilot. it often very convincingly pushes for long and beautiful but wrong completions LLM as “internet influencers”: surface form trumps content https://
x.com/shortstein/sta
/shortstein/status/1587857803678748672
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Meta Unveils ESM Metagenomic Atlas with 617 Million Structures
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Meta presents "ESM Metagenomic Atlas", a database of 617 million metagenomic protein structures https://actuia.com/actualite/meta-presente-esm-metagenomic-atlas-une-base-de-donnees-de-617-millions-de-structures-proteiques-metagenomiques/
… #AI #artificialintelligence
@Meta