AI High Signal

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Justin Lo @loresjpg · 01:37
Nice DeepSWE score! Does it survive a lowercase filename? Introducing MaxxBench: 89 DeepSWE tasks with small changes to the instructions or starting code. Same engineering problem, slightly different requirement. Models clustered around 74% on DeepSWE end up 23 pp apart. Good
11 relayeurs à 11 · il y a 4 h Voir sur X
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J Julian Schrittwieser” Hamel Husain” Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)” Ofir Press” Lisan al Gaib Mat Velloso”
Ce qu'ils en ont dit
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Julian Schrittwieser @Mononofu a cité · 01:37
Making novel variations of evals is very useful, public evals tend to get memorized!
Hamel Husain @HamelHusain a cité · 01:16
I see some are drawing the wrong inference from this study: they are focusing on this meta benchmark as yet another benchmark for model picking, i.e. open vs closed models, model families etc. That’s too narrow of an interpretation! You need to do your own private evals on
Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞) @teortaxesTex a cité · 08/11 22:00
holy shit, an art form of scientific grift next METR/Epoch/AA employee right here you all need to work on your epistemic hygiene
Ofir Press @OfirPress a cité · 08/11 21:26
GPT-5.6 Sol and Luna were built by roughly the same people using roughly the same infra, I don't think we can blame the 20 point difference in Luna just on memorization. There's something else being tracked here in addition to memorization. Maybe MaxxBench questions are slightly
Mat Velloso @matvelloso a cité · 07/11 21:20
I'm both surprised and also not at all
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Richard Sutton @RichardSSutton · 04:43
Brute force computation is not enough for intelligence. Clever new methods are needed. The science of AI is far from finished. IMHO
incompleteideas.net https://incompleteideas.net/IncIdeas/BitterLesson.html
14 relayeurs à 14 · il y a 42 min Voir sur X
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Stanford NLP Group chansung elie” François Fleuret” M M Saiful Bari (MARUF)” Denny Zhou”
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elie @eliebakouch a cité · 08/11 09:58
i disagree with the first point, there is nothing that says that scaling up current transformer recipe is not enough for "intelligence". you take kimi K3 or your favorite open arch + some stability fixes, you scale it to 50T parameters, you do classical training end to end, you
François Fleuret @francoisfleuret a cité · 08/11 07:44
We need a model that learns *in spite* of its inductive bias, not thanks to it. We have to stop being cross-entropy fetishists.
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M Saiful Bari (MARUF) @sbmaruf a cité · 08/11 07:02
True! This is the era of the RL objective. The biggest economy on this earth (US stock market) runs on subscriptions. Subscriptions require vendor lock-in. Currently, the frontier is pushing “Variance” learning from customer data, like how Google won the search market. But I
Denny Zhou @denny_zhou a cité · 08/11 06:26
The Bitter Lesson 2.0
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John Langford @JohnCLangford · 08/11 03:26
The End of AI Frontiers . There's a bit of a train wreck here that's painful to express. Nevertheless, it's a significant event for me and quite a few other folks involved so I wanted to memorialize a bit.
hunch.net The End of AI Frontiers
5 relayeurs à 5 · il y a 26 h Voir sur X
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Terry Yue Zhuo Zachary Nado Eric Hartford rohan anil” Aaron Defazio
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rohan anil @_arohan_ a cité · 06/11 20:57
I really love the full bandwidth transformer research - One of the beautiful works of art of this year! “For example, the Bytedance experiments suggest a variant of the Full Bandwidth Transformer might be comparable to a model of twice the size, implying significant savings in
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Nous Research @NousResearch · 07/11 23:52
Introducing Arete-27B: Qwen3.8-27B, post-trained to reinforce Western values. Chinese open models are currently the strongest available, but they ship with state-aligned behavior in the weights. We built an 803-prompt eval across seven value categories, including freedom of
5 relayeurs à 5 · il y a 30 h Voir sur X
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Tanishq Mathew Abraham, Ph.D.” clem 🤗 Jacob Lee Teknium 🪽 Zach Mueller
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Tanishq Mathew Abraham, Ph.D. @iScienceLuvr a cité · 07/11 23:52
nous shoulda just called it a wasian finetune and sidestepped all the criticism
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Joël Niklaus @joelniklaus · 07/11 16:58
I burned a shitload of compute so you don't have to. Releasing the Harness Leaderboard. Which harness should you run your open model in? I ran 28,849 trials to find out. The leaderboard compares nine coding-agent harnesses on open models. In each comparison only the harness
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Zach Mueller” clem 🤗 Mario Zechner” Leandro von Werra Teknium 🪽”
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Zach Mueller @TheZachMueller a cité · 07/11 16:58
Is this the largest ablation of harnesses and models ever performed?
Mario Zechner @badlogicgames a cité · 06/11 11:40
neat
Teknium 🪽 @Teknium a cité · 06/11 08:20
Hermes supremacy tweet #9138
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ARC Prize @arcprize · 07/11 03:34
Inkling 2 Small from @thinkymachines on ARC-AGI (Verified): - ARC-AGI-2: 81.7%, $0.27/task - ARC-AGI-1: 96.5%, $0.08/task It outperforms every open-weight model we've evaluated on both ARC-AGI-1 & ARC-AGI-2. Thinking Machines plans to release its full weights next week.
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Victoria X Lin Horace He Soumith Chintala Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)” M Martin Ziqiao Ma”
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Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞) @teortaxesTex a cité · 06/11 21:05
wtf, this is excellent and actually somewhat scary. Thinky did this on a tiny compute and token budget, without any fancy architecture or RL tricks. This is the same level of achievement as 1017. Maybe better. This is FINALLY what can be expected of top-tier ex-Frontier staff.
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Martin Ziqiao Ma @ziqiao_ma a cité · 06/11 20:41
Thanks @arcprize! One of my favorite eval for monitoring RL health🫡