Hulme thinks it's better to think about AI systems as goal-directed adaptive systems—a cybernetics-inspired concept that gained traction in the 1980s by applying systems theory to how AI can learn and adapt through experience rather than static code.
MACHINE LEARNING
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Matrix Transpose Simplification: From Complex to Elegant Solution
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TFW you flip so many matrices that you wind up with:
C = (A.t @ B.t).t
And realize you can just do:
C = B @ A -
LLMs Learn Reasoning Without Correct Answers Study
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LLMs don’t need correct answers to learn reasoning. A new study shows: 100% wrong answers? Only 3.2% accuracy drop 67% random digits? 4.3% drop 100% missing reasoning keywords? 3.3% drop Structure > Correctness. Full breakdown: https://
bit.ly/44rkxW0 -
RF-DETR: Real-Time Object Detection with Transformer Models
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🚀 Explore RF-DETR: Real-Time Object Detection
— Satya Mallick (@LearnOpenCV) 16 avril 2025
Enhance your object detection capabilities with RF-DETR, a sophisticated transformer-based model designed for high accuracy and efficient real-time performance.
In this comprehensive guide on LearnOpenCV, you will learn about:… pic.twitter.com/bIDsfBivRDExplore RF-DETR: Real-Time Object Detection Enhance your object detection capabilities with RF-DETR, a sophisticated transformer-based model designed for high accuracy and efficient real-time performance. In this comprehensive guide on LearnOpenCV, you will learn about:
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LLM Post-Training: Deep Dive into Reasoning Models
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LLM Post-Training: A Deep Dive into Reasoning Large Language Models Kumar et al.: https://
arxiv.org/abs/2502.21321 #ArtificialIntelligence #DeepLearning #MachineLearning -
Cohere CEO on AI Self-Scaling When Human Data Gets Too Expensive
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Intéressant :
— VISION IA (@vision_ia) 16 avril 2025
Le PDG de Cohere, Aidan Gomez, affirme que lorsque les données humaines deviennent trop coûteuses, l’IA apprend à s’auto-scalabiliser.
Pourquoi embaucher 100 000 médecins quand 100 suffisent ? Il suffit d’entraîner l’IA sur des signaux fiables — puis de générer 1… https://t.co/vcR0DH1REoIntéressant : Le PDG de Cohere, Aidan Gomez, affirme que lorsque les données humaines deviennent trop coûteuses, l’IA apprend à s’auto-scalabiliser. Pourquoi embaucher 100 000 médecins quand 100 suffisent ? Il suffit d’entraîner l’IA sur des signaux fiables — puis de générer 1
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Claude is better at coding than 90% of AI models
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This is a fact. Claude is better at coding than 90% of the AI models out there.
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Long Chain of Thought Reasoning: Comprehensive Guide and Resources
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Page: https://
long-cot.github.io
Paper: https://
arxiv.org/pdf/2503.09567
Github：
https://
github.com/LightChen233/A
wesome-Long-Chain-of-Thought-Reasoning
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Chain-of-Thought Survey: Comprehensive Guide to Reasoning LLMs
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Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models
They cited over 900 papers in this survey—easily one of the most comprehensive reads you'll come across this year. If you're diving into the field, this is your new textbook. -
Clean Slate for Offline Reinforcement Learning Research
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A Clean Slate for Offline RL
Paper: https://
arxiv.org/pdf/2504.11453