Pay attention to this one if you build multi-agent systems. Coordination is as important as prompts or agent architecture. Multi-agent LLM systems fail in production at rates between 41% and 87%. The majority of those failures are coordination defects, not base-model
RESEARCH
-
xAI and Anthropic have opposite compute problems despite large GPU fleet
By
–
The xAI / Anthropic compute story is not about one company having GPUs and the other wanting them.
It's that they have opposite problems. xAI reportedly runs one of the largest GPU fleets in the world. Yet according to The Information, its recent model FLOPs utilization was -
Scale AI publishes a new benchmark for refactoring agents
By
–
Scale AI published SWE Atlas Refactoring Leaderboard, a new benchmark that evaluates agent capabilities of restructuring the code. > It requires agents to produce twice as much lines of code than SWE Bench Pro. > Claude Code with Opus 4.7 tops the leaderboard followed by
-
Research on many-shot prompting limits
By
–
More examples don’t always mean better results. Our team's research explores the real limits of many-shot prompting and test-time adaptation across models and tasks. Read the paper
-
Hugging Face Hub crosses 4,000 public RL environments, largest platform?
By
–
The @huggingface hub just crossed 4,000 public RL environments! Does it make us the largest platform for RL envs or are there bigger ones? Let us know what we can do to improve on the topic, it's early and we're excited to keep growing and support more! https://
huggingface.co/spaces?categor
y=agent-environment&sort=trending
… -
AI’s Extensive Impact on Surgical Workflows
By
–
The impact of AI for surgery (pre-op, intraop, post-op) is going to be extensive
A new review https://
frontiersin.org/journals/scien
ce/articles/10.3389/fsci.2026.1783803/full
…
Our previous review @NatureMedicine https://
nature.com/articles/s4159
1-024-02970-3
… -
AI learns to predict future as neural networks anticipate moving targets
By
–
AI just learned to predict the future, not just react to it.
— AlphaSignal AI (@AlphaSignalAI) 7 mai 2026
A new paper just cracked open how neural networks learn to predict.
Researchers trained recurrent neural networks to chase a moving target.
Some learned to react. Others learned to anticipate.
The difference… pic.twitter.com/zemHjovUqhAI just learned to predict the future, not just react to it. A new paper just cracked open how neural networks learn to predict. Researchers trained recurrent neural networks to chase a moving target. Some learned to react. Others learned to anticipate. The difference
-
Technical history of voice synthesis research and POCs
By
–
Lesquels, par exemple ? Les 3 secondes d’enregistrement, c’est un truc qui était sorti chez Microsoft en 2023. OpenAI avait parlé de 15 secondes en 2022, mais ce n’est jamais sorti. Parce que c’étaient juste des POC théoriques, pas des méthodes réellement utilisables.
-
PhysForge: Generating Physics-Grounded 3D Assets for Virtual Worlds
By
–
PhysForge
— AK (@_akhaliq) 7 mai 2026
Generating Physics-Grounded 3D Assets for Interactive Virtual World
paper: https://t.co/MMb7IduQ9v pic.twitter.com/rkt9gKjzrpPhysForge Generating Physics-Grounded 3D Assets for Interactive Virtual World paper: https://
huggingface.co/papers/2605.05
163
… -
Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation
By
–
Stream-R1 Reliability-Perplexity Aware Reward Distillation for Streaming Generation paper: https://
huggingface.co/papers/2605.03
849
…