This dataset was crafted with a fine-tuned @NousResearch Hermes 4.3 36B model run on a RTX 6000 Blackwell Server Edition. (We simply love @NousResearch but this, by no means, does it signify a partnership) PMI-relevant results: 60.6% TruthfulQA (Delta: +11.7% vs Qwen3.5-4B) & 71.5% HellaSwag on a 4B fine tuned model.

Stanford just tested whether LexisNexis and Thomson Reuters’ AI legal research tools are really “hallucination-free,” as they claim. Spoiler: not even close. Here’s what the study found. https://t.co/lb2CekFeWn

Spark 2.0 is here! 🚀 We’re redefining what’s possible on the web with a streamable LoD system for 3D Gaussian Splatting. Built on Three.js, you can now stream massive 100M+ splat worlds to any device from mobile to VR using WebGL2. All open-source. Dive into the tech 👇 https://t.co/VOd6V0Wz1s

Thanks @_akhaliq for sharing our work! Try and put your robot in today at: https://t.co/i5HkcE1dqs https://t.co/A1P8QRsMhQ

Our most expressive and steerable TTS model yet! Designed to give builders granular control over AI-generated speech, Gemini 3.1 Flash TTS is really fun to play with! Available in preview today - for devs via the Gemini API & @GoogleAIStudio + for enterprises on Vertex AI

OpenClaw now has end-to-end testing for Telegram 👀 Uses the brand new Telegram bot-to-bot communication mode: https://t.co/RDEj1i0zwa 🦞 https://t.co/LWSn4PCr6N

Many are running @NousResearch Hermes Agent now. Here are some practical tips that help a lot, especially if you're coming from OpenClaw: 1. Nightly skill evolution is worth setting up. Link: https://t.co/qPs3QPIYgW Pro tip: Add a second cronjob to evaluate the changes so you don't have to. Make sure it stops anything that tries to game the optimization loop. 2. Install Honcho if you're hitting memory issues. It gives proper cross-session recall, memory synthesis, and better long-term storage. Helps avoid repeating the same mistakes or pulling too much context (and wasting tokens). 3. Consider changing the default session timeout and expiry. Especially useful for threads you don't use every day, prevents the agent from losing context unnecessarily. For those migrating from OpenClaw: 4. Expose your OpenClaw agents as OpenAI-compatible endpoints. This lets you run both side-by-side with zero disruption while you transition. Hermes can call them directly, and your existing crons keep working. 5. On day one, start populating your USER.md and MEMORY.md files. Note for OC users: Hermes has a much smaller character limit than OpenClaw, so populate and curate thoughtfully, don't just dump everything in. Quality over quantity helps it learn you faster. 2,200 for memory and 1,375 for user. Hermes works especially well once you integrate it properly into your workflows. Last tip, don't start changing your skin till your agents are actually doing work. You might never stop and go down the rabbit hole... 🤣

Most Physical AI models recognize patterns. They don’t understand the world. That’s why they fail on edge cases. BADAS 2.0 is a V-JEPA2 world model trained by @getnexar on real-world videos. We used the model to find what it didn’t understand, then trained on that. It generalizes. And we built lite versions so it runs on edge devices, even CPU. Understanding is the only way this scales. See how it performs on your own videos. Link in first comment.

Was able to use ollama with qwen3 14b locally on my laptop to troubleshoot internet connectivity issue on a cruise ship wifi @ollama @Alibaba_Qwen Found answer in < 5 mins. I'm running it on a Macbook Air M4 24GB. You all should keep a model locally handy to use https://t.co/xM4LOhzHj6

hermes agent @NousResearch is fucking insane i know literally NOTHING about coding. ZERO. and i just built a fully functioning web app in minutes http://localhost:3000/ check it out @Teknium https://t.co/H0uvfhoNX5