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Wednesday, October 29, 2025
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TagsHow to Build a Fully Functional Computer-Use Agent that Thinks

Tag: How to Build a Fully Functional Computer-Use Agent that Thinks

AI

How Exploration Agents like Q-Learning, UCB, and MCTS Collaboratively Learn Intelligent Problem-Solving Strategies in Dynamic Grid Environments

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AI

MiniMax Releases MiniMax M2: A Mini Open Model Built for Max Coding and Agentic Workflows at 8% Claude Sonnet Price and ~2x Faster

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AI

Zhipu AI Releases ‘Glyph’: An AI Framework for Scaling the Context Length through Visual-Text Compression

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AI

How to Build a Fully Interactive, Real-Time Visualization Dashboard Using Bokeh and Custom JavaScript?

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AI

Meet Pyversity Library: How to Improve Retrieval Systems by Diversifying the Results Using Pyversity?

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AI

How to Build an Agentic Decision-Tree RAG System with Intelligent Query Routing, Self-Checking, and Iterative Refinement?

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AI

Meet ‘kvcached’: A Machine Learning Library to Enable Virtualized, Elastic KV Cache for LLM Serving on Shared GPUs

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AI

5 Common LLM Parameters Explained with Examples

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AI

How to Build, Train, and Compare Multiple Reinforcement Learning Agents in a Custom Trading Environment Using Stable-Baselines3

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AI

A New AI Research from Anthropic and Thinking Machines Lab Stress Tests Model Specs and Reveal Character Differences among Language Models

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