What if your AI agent could train itself by exploring thousands of real-world services and automatically finding its own weaknesses? Renmin University of China and ByteDance Seed introduce Agent-World, a self-evolving training arena. It works by having the agent discover new
AI
-
Students build AI financial service using custom Mac Studio cluster
By
–
Un groupe d’étudiants chinois a acheté 7 Mac Studio sur eBay pour un total de 3 600 $, les a reliés via Ethernet pour former un seul système, puis a ouvert un cabinet financier basé sur l’IA directement dans leur chambre universitaire.
— Jouhatsu | AI Influence Operator (@Jouhatsu_ai) 10 mai 2026
Leur premier client payait un conseiller… https://t.co/INA2WhAhlc pic.twitter.com/ovdfcIOJlNUn groupe d’étudiants chinois a acheté 7 Mac Studio sur eBay pour un total de 3 600 $, les a reliés via Ethernet pour former un seul système, puis a ouvert un cabinet financier basé sur l’IA directement dans leur chambre universitaire. Leur premier client payait un conseiller
-
Hermes Agent and Codex Goal Tracking
By
–
Codex /goal With Hermes Agent is life-changing.
— Shubham Saboo (@Saboo_Shubham_) 10 mai 2026
I updated my Hermes agent skill to give Codex a goal on the fly using Telegram and track each one of those codex goals in a Kanban board.
It has been really insane to see and track Codex execute goals in the wild. pic.twitter.com/9FEoZ7J0TwCodex /goal With Hermes Agent is life-changing. I updated my Hermes agent skill to give Codex a goal on the fly using Telegram and track each one of those codex goals in a Kanban board. It has been really insane to see and track Codex execute goals in the wild.
-
Local AI surges with GGUF models
By
–
Local AI is experiencing a major boom! Here’s the number of new GGUF models created each month over the past 8 months, along with insights from our internal HF agent (May data is partial): – 176,000 total public GGUF models on HF – Two distinct phases: Oct–Feb averaged ~5.1K new GGUF models per month
-
Engineer’s switch to HTML increases token usage 2-4x
By
–
Thariq Claude Code engineer just wrote a whole post about why he switched from Markdown to HTML for agent outputs. His own admission: it uses 2-4x more tokens. Dont know if this is the best advice looking at my rates rn 😀
-
Impact of Token Reduction and Context Engineering on AI Models
By
–
Exactly. At 98.7% fewer tokens, you're not tuning the same system. You're running a different one. And agreed on context engineering. The model that wins isn't the smartest one. It's the one that sees only what it needs, when it needs it.
-
Using Claude Code to automate email API integration
By
–
Thanks man, it's great. I think a few things, the way it's set up with Workers etc is confusing. Luckily Claude Code figured out quickly it could just do a POST to a URL with a token and send emails. I'd look at other email sending companjes to see how they do it Usually it's
-
Shifting from RAG to LLM Knowledge Compilation
By
–
RAG is already becoming the “old way” The future of AI memory is not retrieval.
It’s compilation. Here’s the shift in one sentence: From searching information To structuring knowledge The new model? LLM Wiki Instead of: Chunking documents Running similarity -
Examples of fine-tuning LLMs in practice
By
–
Asking because about once every six months I put out a call for examples of fine tuning LLMs working in practice and, aside from the obvious examples like Cursor, I don't often get many great answers
-
NVIDIA and Corning Partner to Advance AI Infrastructure Manufacturing
By
–
Corning – NVIDIA and Corning Announce Long Term Partnership To Strengthen U.S. Manufacturing for AI Infrastructure! $500 million – Strategic investment NVIDIA is making a major strategic investment in Corning to secure advanced optical connectivity for AI infrastructure.