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How Google’s 'internal RL' could unlock long-horizon AI agents
Researchers at Google have developed a technique that makes it easier for AI models to learn complex reasoning tasks that usually cause LLMs to hallucinate or f...
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The 2M Token Trap: Why 'Context Stuffing' Kills Reasoning
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AI Agents: Mastering 3 Essential Patterns (ReAct). Part 2 of 3
Article Part 1 The code for these patterns is available on GitHub. Repo “Tool‑Using” Pattern Article 1 We gave the AI hands to interact with the outside world....
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Implementing Vibe Proving with Reinforcement Learning
How to make LLMs reason with verifiable, step-by-step logic Part 2 The post Implementing Vibe Proving with Reinforcement Learning appeared first on Towards Data...
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Understanding Vibe Proving
How to make LLMs reason with verifiable, step-by-step logic Part 1 The post Understanding Vibe Proving appeared first on Towards Data Science....
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My Google AI Agents Intensive Experience — Day-by-Day Reflections
🗓️ Day 1 – Introduction to Agentic AI The first day reshaped how I viewed AI. I learned that an agent is more than a model — it’s a system that can perceive,...
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Thinking Tokens Are Not Created Equal: Why Benchmarks Can't Distinguish Between 'Search' and 'Insight' (A PCP Experiment)
Experiment Overview I’ve been running experiments to understand how different “reasoning” models actually spend their thinking budget. The results suggest that...
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🚀 Gemini 3 Is Changing the AI Landscape — And OpenAI Can Feel It
2025 is shaping up to be the year of Gemini 3. Google’s newest flagship model hasn’t just caught up with OpenAI — many developers argue it has leapfrogged GPT‑4...
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[Paper] Escaping the Verifier: Learning to Reason via Demonstrations
Training Large Language Models (LLMs) to reason often relies on Reinforcement Learning (RL) with task-specific verifiers. However, many real-world reasoning-int...