(Honestly I'm still salty about that time you renamed the deepseek-r1:8B to point at DeepSeek-R1-0528-Qwen3-8B when it had previously pointed at DeepSeek-R1-Distill-Llama-8B)
OPEN SOURCE
-
Metis enables easy AI edge deployment with ONNX and PyTorch
By
–
AI at the edge shouldn’t be a trade-off between performance, accuracy, or usability. Metis lets devs deploy, optimise & benchmark with ease using ONNX, PyTorch, YAML & GStreamer. What's even more exciting is it's all available now via @Rutronik →
-
Chinese AI Labs Release Major Models: Kimi, GLM, Qwen
By
–
July has been a truly incredible month for model releases from China – Moonshot (Kimi K2), http://
Z.ai (GLM-4.5) and 5 new releases from Qwen I think it's undeniable that the best available open weight models now come from the Chinese AI labs -
Neo: First Autonomous ML Engineer Agent Released
By
–
The first autonomous ML Engineer Agent has been released by @withneo! Neo is a multi-agent system that thinks, learns and builds like a real engineer.
— 🚨 AI News | TestingCatalog (@testingcatalog) 30 juillet 2025
– Perform analysis
– Finetune Llama and Gemma LLMs
– Prepare a visualisation
– Prepare training and evaluation pipelines https://t.co/1vvK4ddytw pic.twitter.com/PXN8WnRvYCThe first autonomous ML Engineer Agent has been released by @withneo
! Neo is a multi-agent system that thinks, learns and builds like a real engineer. – Perform analysis
– Finetune Llama and Gemma LLMs
– Prepare a visualisation
– Prepare training and evaluation pipelines -
Meta Developing Personal Superintelligence
By
–
BREAKING : Meta is building Personal Superintelligence! “Over the last few months we have begun to see glimpses of our AI systems improving themselves. The improvement is slow for now, but undeniable. Developing superintelligence is now in sight.”
-
Building AI Systems with Open-Source Models Only
By
–
Yep! You can even do it entirely w/o any closed-source models in the loop! In the demo above, it was powered entirely by Kimi, Deepseek, and Qwen.
-
AutoRL: Train AI Models for Any Task via GitHub
By
–
If you'd like to try it or contribute, check out the Github repo and notebook: https://
github.com/OpenPipe/ART/t
ree/auto-rl?tab=readme-ov-file#-autorl-train-models-for-any-task
… -
AutoRL: Simplest Way to Train Task-Specific LLMs
By
–
Introducing `AutoRL` 📈
— Matt Shumer (@mattshumer_) 30 juillet 2025
The world's simplest way to train a task-specific LLM with RL.
*Just write a SENTENCE describing the model you want.*
A chain of AI systems will generate data + rubrics and train a model for you.
Powered by ART, it's open source.
Link in thread: pic.twitter.com/OVxe2hWTZYIntroducing `AutoRL` The world's simplest way to train a task-specific LLM with RL. *Just write a SENTENCE describing the model you want.* A chain of AI systems will generate data + rubrics and train a model for you. Powered by ART, it's open source. Link in thread:
-
AutoRL: Automated Reinforcement Learning for Model Generation
By
–
How AutoRL works, in a nutshell: – The user describes the model they want
Ex: "A model that detects spelling and grammar errors" – OSS models generate a system prompt that will be used a) to generate, and b) for RULER to rank outputs – We generate input data, and RL a model!