Beyond Fast and Slow: Cognitive-Inspired Elastic Reasoning for Large Language Models Paper: https://
arxiv.org/abs/2512.15089
MACHINE LEARNING
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Elastic Reasoning: Cognitive-Inspired Approach for Large Language Models
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Tesla has best world models for training robots
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Yeah, world models are being used to train robots. Awesome, huh? And who has the best world models? Tesla.
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Echo-N1: AI Learns Human Conversation Through Affective Reinforcement Learning
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What if AI could learn the art of conversation like a human? This research challenges a year of focusing RL on logic, showing it’s possible to optimize AI for personality and emotional depth—and the results outperform leading models. Echo-N1: Affective RL Frontier Paper:
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Snorkel Sponsors Community Effort to Reduce Code Quality Issues
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Awesome work @GOrlanski
! At Snorkel, we know quality matters. We're excited to sponsor and support the community working on reducing code slop -
Experimenting with Olmo 3 and DeepSeek V3.2 GRPO tweaks
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Oh yeah you probably will. I am currently running tons of experiments to decide which of the Olmo 3 and DeepSeek V3.2 GRPO tweak I should add in the final version.
No side objective really except I'd do an honest evaluation to make sure that the model actually learns well. -
Model Convergence Shifts AI Differentiation to Data Foundations
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On @TBPN
, Databricks CEO and co-founder @alighodsi joined @johncoogan and @jordihays to discuss how model capabilities are converging, and why differentiation increasingly comes from strong data foundations and reasoning over proprietary data. They also talked about how -
Differentiable Programming: Representation vs Learnability Challenge
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The ability to embed your discrete function on a differentiable curve is a prerequisite for differentiable programming, but it is *far* from sufficient, the hard part is getting GD to find the right function Anything can be represented, not everything can be learned
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OpenAI Prepares Codex Upgrade with GPT-5.2-Codex-Max
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BREAKING : OpenAI is preparing to upgrade Codex, likely with GPT-5.2-Codex-Max. One last leap this year? Caribou
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New Toolkit for Extending Training Data to Different Robot Embodiments
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Excited to release this toolkit for extending training data to different robot embodiments: https://t.co/sqhKr7akE8
— Ken Goldberg (@Ken_Goldberg) 17 décembre 2025Excited to release this toolkit for extending training data to different robot embodiments:
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Gradient Descent Limitations in Discrete Reasoning Spaces
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Gradient descent is a powerful tool for optimization spaces that verify the manifold hypothesis, but the space of reasoning is discrete and combinatorial. GD fails in cliff-like landscapes where a single discrete change (a logical step) alters the entire outcome. Unless…???