The WebMCP Standard is an open web standard that lets browser‑based AI agents call JavaScript functions directly on a site. It improves speed,, and developer experience by providing a typed, structured API.
A step by step guide to llm self training that covers memory-first workflows, embeddings, safety checks, and tools like OpenCrabs and Neura ACE.
OpenCrabs 0.3.19 brings native OAuth for Codex, an external embedding API, and a lightweight memory mode for VPS. The release is ideal for developers, researchers, and small businesses that want to run AI agents on their own servers.
A clear guide on self adapting llms that explains how models learn at runtime, safety checks to add, and a step by step plan to run safe updates.
A clear guide to subquadratic models, why they matter, and how to test and build systems that handle very long AI inputs.
A clear guide to Agentic Workflows covering design, tools, safety, and scaling. Includes a checklist and examples to get started.
Qwen 3.7‑Max‑Preview introduces a 1M token context window, enabling large‑scale text processing and smarter AI workflows.
A practical guide to using 1M context AI models for long running agents and deep document work. Includes patterns, architecture, and a step by step build plan.
Fast‑Slow Training is a new training method that keeps AI models from forgetting old tasks while learning new ones. It uses slow weights for core knowledge and fast weights for quick adaptation.
A clear guide to context pinning that explains how to store long prompts once, reuse them safely, and cut token cost in AI applications.