AI & IA

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Pushmeet Kohli @pushmeet · 08/11 19:36
Across our projects @GoogleDeepMind, we are witnessing a genuine phase transition in the pace of scientific discovery. You will see a glimpse of this in our releases in the next few weeks.
5 relayeurs à 5 · il y a 9 h Voir sur X
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E echo.hive Dr Singularity” elvis” B Benjamin De Kraker” Demis Hassabis
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Dr Singularity @Dr_Singularity a cité · 08/11 18:30
1000 scientific breakthroughs drop from Google incoming?
elvis @omarsar0 a cité · 08/11 17:08
Been working for this moment for over a decade. What I've witnessed behind the scenes, together with what we have been building, tells me we are about to enter a truly incredible era of AI-powered scientific discovery. It's an incredible time to be doing research. I will be
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Benjamin De Kraker @BenjaminDEKR a cité · 08/11 15:15
What did he mean by this 👀
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Justin Lo @loresjpg · 08/11 22:00
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
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Teortaxes▶️ (DeepSeek 推特🐋铁粉 2023 – ∞)” Ethan Mollick” ℏεsam”
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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
Ethan Mollick @emollick a cité · 08/11 18:33
ℏεsam @Hesamation a cité · 07/11 18:58
dude. this is painful to look at.
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Richard Sutton @RichardSSutton · 08/11 16:18
Brute force computation is not enough for intelligence. Clever new methods are needed. The science of AI is far from finished. IMHO
7 relayeurs à 7 · il y a 22 h Voir sur X
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Tommy” elvis” ℏεsam” Gary Marcus” cocktail peanut” Srini Pagidyala”
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Tommy @Shaughnessy119 a cité · 08/11 16:18
I’ve been actively on the hunt for non LLM based AI models and I’ve invested into one already Looking for totally new designs
elvis @omarsar0 a cité · 08/11 01:26
1000% agree with Sutton here. Having worked in AI for over a decade (pre-LLMs), it's clear we need smarter methods for intelligence to truly compound in the way some of us envision it. To me, Transformers just scratched the surface. This arc is coming to an end; a new
ℏεsam @Hesamation a cité · 07/11 23:55
> “what happened to the bitter lesson?” people are genuinely trying to explain the bitter lesson to the guy who wrote it. it’s called the bitter lesson not the dumb lesson. the bitter lesson says general methods that scale with compute win in the long run. you still have to
Gary Marcus @GaryMarcus a cité · 07/11 23:32
what i have been saying for years maybe now people will listen?
cocktail peanut @cocktailpeanut a cité · 07/11 21:29
Srini Pagidyala @Srini_Pa a cité · 07/11 21:16
Human like learning does it. Implies understanding, concept formation, metacognition, self-directed, goal-oriented, persistent memory, contextual awareness, belief revision, dynamic world models are all part of it. That is Integrated Neuro Symbolic Architecture- INSA.
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Andrej Karpathy @karpathy · 07/11 23:05
Earlier this week Tristan published his top YouTube channels: Which looked excellent so clearly I had to turn it into TristanTube: 47K super nerdy videos +TV mode for laid back watching. (One-shotted with Claude Code in 3 minutes)
karpathy.ai TristanTube
thume.ca My YouTube tier list, six years later
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Dominique Fleury Rahul” MONTREAL.AI
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Rahul @sairahul1 a cité · 07/11 20:07
karpathy is so done with the youtube algorithm he's building his own youtubes now 😭 last week: 6,454 videos pulled from 43M Hacker News comments. ~2 hours. today: turned a YouTube tier list into a 47K-video site. 3 minutes with Claude Code.
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Physical Superintelligence @psipbc · 07/11 20:21
Today Physical Superintelligence PBC is announcing a proof of the Aaronson-Ambainis conjecture, one of the central open problems in quantum complexity, with major implications for quantum computing speedup. Thread 👇
PSI A proof of the Aaronson-Ambainis conjecture A proof of the Aaronson-Ambainis conjecture about quantum speedups on random inputs, with a complete formalization in Lean.
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Machine Learning FLX Peter Xing Dr Singularity”
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Dr Singularity @Dr_Singularity a cité · 07/11 04:54
New wave of AI physics breakthroughs