An unauthenticated RCE PoC for the React vuln (CVE-2025-55182) is now public. Confirmed to work on my test setup (Next.js 16.0.6 with React 19.2.0).
Microsoft just dropped VibeVoice-Realtime-0.5B Open-source realtime TTS AI model that starts talking in ~300 ms Streaming, long-form and insanely fast.
We used Claude Code to train open LLMs. Check out the tutorial. basically, we plugged HF skills into claude code and it was able to train LLMs end-to-end. Best thing, this works on all major coding agents: Codex, Cursor, and Gemini CLI. - You tell the agent to fine-tune a model…
As always, huge thanks to @digitalocean as our hosting sponsor 🫶
Grand scheme of managing @GogsHQ infrastructure on @digitalocean with @PulumiCorp unknwon.io/posts/241215-g…
Agent Starter Pack by Google. Build, experiment and deploy production grade AI Agents in minutes. All of this in just one command.
I still can’t believe this is free. Most bootcamps are charging $3,000 to teach you outdated material. Meanwhile, @huggingface is giving away the state-of-the-art curriculum for $0. • Agents? ✅ • Robotics? ✅ • The new MCP standard? ✅ Check this. Bookmark.👇
This is so good! 🤯 n8n just made it easy to MCPify your agentic workflows. You can search, view, and run your n8n workflows from ChatGPT or Claude Code. Watch how I have started to use it for optimizing my AI agents.
This open-source chat UI brings ChatGPT and Claude .ai features to every LLM. Use any LLM with RAG, web search, MCP, deep research, code interpreter, custom commands, etc at one place. Self-host and deploy in airgapped environments. 100% open-source.
Build AI Agents with Google Agent Development Kit and Gemini 3 This step-by-step course covers structured output, tool calls, MCP, memory agents and multi-agent patterns. 100% Opensource.
In case you missed it, earlier this week we fixed one of the most common frustrations on Claude.ai: hitting context limits mid-conversation. Claude now intelligently compacts earlier context automatically when you're nearing the limit so the chat can keep going.
Meta just solved the biggest problem in RAG! Most RAG systems waste your money. They retrieve 100 chunks when you only need 10. They force the LLM to process thousands of irrelevant tokens. You pay for compute you don't need. Meta AI just solved this. They built REFRAG, a new…
Fine-tune DeepSeek-OCR on your own language! (100% local) DeepSeek-OCR is a 3B-parameter vision model that achieves 97% precision while using 10× fewer vision tokens than text-based LLMs. It handles tables, papers, and handwriting without killing your GPU or budget. Why it…
It doesn't matter what tools you use for AI Agents. I've put together the ultimate curriculum to learn how to build AI agents. (bookmark it) From context engineering to evaluating, optimizing, and shipping agentic applications.
As usual, Anthropic just published another banger. This one is on context engineering. Great section on how it is different from prompt engineering. A must-read for AI devs.
this was based on the brilliant textbook: "Foundations of Large Language Models" by Tong Xiao and Jingbo Zhu (NiuTrans Research Lab) arxiv: arxiv.org/abs/2501.09223… highly recommend it if you're serious about understanding LLMs deeply.
I finally understand how large language models actually work After reading the 2025 textbook “Foundations of LLMs” It blew my mind and cleared up years of confusion Here’s everything i learned (in plain english):
Build a Multi-agent app with MCP using Google ADK without writing a single line of Python Code, in simple YAML. All of this in ~5 mins. Step-by-step tutorial with opensource code:
We are launching a 5-Day AI Agents course on Kaggle. Learn about AI Agent patterns, agent tools, context engineering, memory management, agent evaluations and building production grade multi-agent systems with A2A. 100% free and open to all.
I think we ALL want
📁 Matthew McConaughey says he wants a private LLM, fed only with his books, notes, journals, and aspirations, so he can ask it questions and get answers based solely on that information, without any outside influence.
Introduction to Reinforcement Learning. The only book you need to fundamentally understand how agents learn optimal behavior through trial and error. 100% free to read.
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