Learning to Reason from Feedback at Test-Time This new paper proposes a new paradigm called FTTT (Feedback-based Test-Time Training) that enables LLMs to learn iteratively from environment feedback during inference. Key highlights include: • Test-time optimization for
MACHINE LEARNING
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Claude 3.7 Sonnet Performance Limitations in Math Competitions
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"why isn't claude 3.7 sonnet better at esoteric competition math problems"
— Alex Albert (@alexalbert__) 25 février 2025
we found it didn't generalize to becoming a pokemon master https://t.co/tjkKnHprQ5"why isn't claude 3.7 sonnet better at esoteric competition math problems" we found it didn't generalize to becoming a pokemon master
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Claude AI Agent Applies Generalized Reasoning to Novel Tasks
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With a few tools to help it see the screen a bit better, Claude acts as an agent, applying its abilities to a novel task. In this, we start to see glimmers of AI systems that tackle challenges with increasing competence, not just through training but with generalized reasoning.
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AI Solves Superbug Mystery in 48 Hours
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#AI solves superbug mystery in 48 hours – after scientists took 10 years
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DUSt3R: Novel Dense Unconstrained Stereo 3D Reconstruction Paradigm
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DUSt3R, a novel paradigm for Dense and Unconstrained Stereo 3D Reconstruction, operates without prior information about camera intrinsics and poses. It performs exceptionally well for in-the-wild scenes and is capable of extending to 3D vision tasks such as depth estimation,… pic.twitter.com/TmOqXZW7Ur
— Satya Mallick (@LearnOpenCV) 25 février 2025DUSt3R, a novel paradigm for Dense and Unconstrained Stereo 3D Reconstruction, operates without prior information about camera intrinsics and poses. It performs exceptionally well for in-the-wild scenes and is capable of extending to 3D vision tasks such as depth estimation,
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Artificial Intelligence’s Role in Predicting Human Rights Violations
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The role of artificial intelligence in predicting human rights violations
#AI #AIio #BigData #ML #NLU #Futureofwork @demishassabis @Ronald_vanLoon @TamaraMcCleary @geoffreyhinton @goodfellow_ian @jeffdean @erikbryn -
TinyML: Machine Learning Power for Tiny Devices
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What Is Tiny ML? A Simple Explanation For Anyone TinyML: Big Power in Small Devices! Explore the world of TinyML – machine learning on tiny, low-powered devices. From smart agriculture to wearable health tech, see how this innovation is revolutionizing AI applications.
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AI Transforming Finance: Predictions, Trading, and Risk Management
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AI is transforming finance! Stock Market Predictions Smart Sales Forecasting AI-Driven Trading Personalized Banking Automated Workflows Fraud Detection & Risk Management Credit & Loan Decisions AI = Smarter, Faster, Safer Finance! Are you
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DeepSeek MoE Architecture for Large Language Models
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Let me add a bit context to the latest DeepSeek code release as I feel it was a bit bare bones. Mixture-of-Experts (MoE) is a simple extension of transformers which is rapidly establishing itself as be the go-to architecture for mid-to-large size LLM (20B-600B parameters). It
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Legal Distinction Between Machine Learning and Human Activities
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It doesn't matter how you try to rationalize machines "learning." There is a legal difference between humans performing activities and machines doing it. The law explicitly makes provisions for machines, because their behavior and impact is not the same.