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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. TOOL · dev.to — LLM tag English(EN) · · [2 sources]

    qwen2.5-coder is too slow for Claude Code on a Mac. Here's the fix.

    A user has detailed how to run Claude Code offline on a Mac by pointing it to a local LLM via Ollama, enabling coding sessions without an internet connection. This setup is particularly useful for flights or areas with unreliable Wi-Fi, offering privacy and cost benefits over cloud-based models. The user also shared a more complex project that evolved into a multi-agent system controlled by voice commands, capable of breaking down tasks, recruiting sub-agents, and performing reviews, though it still faces challenges with speaker verification and over-planning. AI

    qwen2.5-coder is too slow for Claude Code on a Mac. Here's the fix.

    IMPACT Enables offline use of AI coding assistants and explores multi-agent voice control, offering flexibility and new interaction paradigms.

  2. TOOL · dev.to — LLM tag English(EN) · · [41 sources]

    Hot To Run LLMs Locally

    This series of guides provides comprehensive instructions for setting up and running large language models (LLMs) locally on Linux systems. It details hardware and software prerequisites, recommends using llama.cpp for its balance of performance and ease of use, and covers model selection, quantization, and API integration. The guides also include steps for setting up systemd services for 24/7 operation, monitoring performance, and optimizing for various hardware constraints. AI

    IMPACT Enables developers to run and experiment with LLMs locally, reducing reliance on cloud services and facilitating custom application development.