A recent clarity that I gained is viewing AI research as a “max-performance domain”, which means that you can be world-class by being very good at only one part of your job. As long as you can create seminal impact (e.g., train the best model, start a new paradigm, or create
MACHINE LEARNING
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DreaMS: Machine Learning Accelerates Discovery of Unknown Molecules
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Nature is full of chemicals that have yet to be discovered. Researchers from @IOCBPrague and @CIIRCCTU have developed a machine learning model called DreaMS, which significantly accelerates the analysis of previously unknown molecules. Describing them could pave the way
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AI Solves 300-Year-Old Geometric Problem in 11 Dimensions
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Une IA a résolu un problème géométrique en 11 dimensions resté ouvert depuis 300 ans.
— VISION IA (@vision_ia) 29 mai 2025
593 sphères qui se touchent sans se chevaucher — dans un espace que l’intuition humaine ne peut même pas visualiser.
L’intelligence sans intuition commence à nous dépasser. Jusqu’où ira-t-elle… https://t.co/KGEjKJXso7 pic.twitter.com/PIwOpmOdd7Une IA a résolu un problème géométrique en 11 dimensions resté ouvert depuis 300 ans. 593 sphères qui se touchent sans se chevaucher — dans un espace que l’intuition humaine ne peut même pas visualiser. L’intelligence sans intuition commence à nous dépasser. Jusqu’où ira-t-elle
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Large Reasoning Models Self-Training Capabilities Study
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Can Large Reasoning Models Self-Train? Shafayat et al.: https://
arxiv.org/abs/2505.21444 #ArtificialIntelligence #DeepLearning #MachineLearning -
Company Recognized as Leader in Gartner Magic Quadrant
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We're honored to be recognized as a Leader once again in the Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms 🎉 pic.twitter.com/Kb813CjXPA
— DataRobot (@DataRobot) 29 mai 2025We're honored to be recognized as a Leader once again in the Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms
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Google AI Breaks 55-Year-Old Matrix Multiplication Record
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Une IA de Google a battu un record mathématique vieux de 55 ans. Sans intuition humaine.
— VISION IA (@vision_ia) 29 mai 2025
Elle a réduit le nombre d’opérations nécessaires à un pilier de l’informatique moderne : la multiplication de matrices.
Un micro-gain ? Non.
Jusqu’où ira l’optimisation sans humains ?… https://t.co/KGEjKJXso7 pic.twitter.com/mCzMrXDrHfUne IA de Google a battu un record mathématique vieux de 55 ans. Sans intuition humaine. Elle a réduit le nombre d’opérations nécessaires à un pilier de l’informatique moderne : la multiplication de matrices. Un micro-gain ? Non.
Jusqu’où ira l’optimisation sans humains ? -
Multimodal Poster Automation from Scientific Papers
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Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers Pang et al.: https://
arxiv.org/abs/2505.21497 #ArtificialInteligence #DeepLearning #MachineLearning -
BARL: Bayesian Adaptive RL for Reflective LLM Exploration
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This Google paper proposes BARL — Bayesian Adaptive RL for Reflective Exploration. What it can do: – Encourages reflective behaviors to emerge naturally during training.
– Guides LLMs to explore when needed, rather than relying on static policies.
– Results in fewer tokens used -
Large Reasoning Models Self-Training Capabilities Study
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Can Large Reasoning Models Self-Train?
Paper: https://
arxiv.org/pdf/2505.21444
v1.pdf
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Self-Consistency Training for LLM Scaling Without Human Supervision
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Scaling LLMs through Reinforcement Learning (RL) usually needs human-crafted verifiers or gold answers, which limits scalability. Can models train themselves, without external supervision? This paper propose: using the model’s own self-consistency (i.e., agreement across