AI4Research: Mapping the State of AI Science. Engineering the AI Ecosystem: Local LLMs, Hardware, and Model Support. Agentic AI, Multi-Agent Memory, and Model Context Protocols. Hybrid Models, Inference Optimization, and Multimodal Pipelines. Multilingual and Domain-Specific Models: Local, Specialized, and Culturally Tuned AI

Open Source Model Distribution at a Crossroads. Local LLMs: Edge Devices, Embeddings, and Quantization. Local-First AI Workflows: Privacy, Search, and Agents. Command-Line Utilities and Automation for Developers. Research and Foundation Models: OLMo, VideoPrism, and Beyond

Local AI Agents and Privacy-First Productivity Tools. Local LLM Usability: Interfaces and Mobile Breakthroughs. Small Model Training, Quantization, and New Architectures. Model Context Protocol (MCP) and Hugging Face Integration. AI Safety, Evaluation Awareness, and Deception Risks

Hardware, Model Selection, and Local LLMs. Open Source Ecosystem and UI Debates. Model Innovation: MoE, Fine-tuning, and Research Tools. Retrieval, RAG, and Evaluation Datasets. Kernel Optimization and Hardware Enablement

Hardware and Model Speed: Why Commercial LLMs Are So Fast. OpenAI’s Open-Source Pivot: A New Frontier Model?. Specialized LLMs: Medical, Multilingual, and High-Precision Tasks. Local LLM Frameworks and Tooling: Beyond Ollama and LangChain. MCP: Upskilling LLMs with Modular Abilities

Model Size, Performance, and Local LLM Choices. Local LLM Interfaces and Ecosystem Tools. Security and Ownership in Personal AI Systems. Acceleration and Research: dLLM-Cache, Context Engineering, Multimodal Data. AI Applications: Video, Audio, and Document Processing

Multi-LLM Coding Workflows Emerge. New Techniques for "Human-Like" Code Generation. Local AI Tooling: Ollama and Beyond. Hardware Choices and Model Selection for Local LLMs. OCR, Math, and Code: Limits of Small Models

Local LLMs: Continuity, Privacy, and Usefulness. Hardware for Local AI: DGX Spark and DIY Upgrades. Local LLMs, Remote Access, and Open Playgrounds. LLM Agents, API Discovery, and Monitoring Advances. Research: Diverse LLM Architectures and Methods

Open-Source LLMs: Local Coding, Model Formats, and Tooling. Local LLM Tooling: Agents, Voice, and Protocols. Research: Efficient Tuning and Multimodal Reasoning. AI Ecosystem: Commercial Moves and Hobbyist Culture. Security and Science: Wallbleed, Poisson Geometry, and GRBs

Kyutai TTS Redefines Real-Time Voice AI. Local LLMs: Hardware, Frontends, and Multi-User Agents. Retrieval-Augmented Generation: Local RAG and Offline Knowledge. AI in Code: IDEs, Rule Engines, and Agentic Learning. AI for Science: Curie and Domain-Specific AutoML