Interesting direction from Huawei at ISCAS 2026. The proposed “τ Scaling” approach moves beyond traditional transistor shrinking and focuses more on reducing latency and improving efficiency across chips, interconnects, and AI systems. Concepts like LogicFolding, hybrid
COMPUTING
-
300K AI Builders Share Hardware Profiles on Hugging Face
By
–
300,000 AI builders filled their hardware profile on @huggingface and we're sharing the results: http://
hf.co/hardware. Excited to see how it evolves in the coming months especially with the explosion of local AI! -
AI Programming in Azure HPC Pipeline at Scale
By
–
That's AI programming in Action! Applied to Azure HPC pipeline using infrastructure loop, parallel processing, and optimized cloud pipeline to gain performance at scale! Not just math!
-
RDUs deliver high tokens per kilowatt-hour for AI inference
By
–
AI infrastructure doesn’t have to mean massive power draw.
— SambaNova (@SambaNovaAI) 22 mai 2026
Our RDUs deliver the highest tokens per kilowatt-hour, helping reduce deployments with ~10kW average power consumption.
More inference. Less energy. 🦾
Learn more: https://t.co/v6jPztJPFp pic.twitter.com/dUM5bB3T5kAI infrastructure doesn’t have to mean massive power draw. Our RDUs deliver the highest tokens per kilowatt-hour, helping reduce deployments with ~10kW average power consumption. More inference. Less energy. Learn more: https://
sambanova.ai/products/rdu-a
i-chips?utm_source=x&utm_medium=organic
… -
Apple’s OS/Hardware synergy could extend to LLM performance
By
–
Just thinking aloud: Apple systems performance is better because they own both the OS and hardware. Likewise if they own llm + harness layer, performance might improve.
-
AI lab writes kernel code autonomously
By
–
I met an AI lab that said their AI is now writing kernel code. So expect to see even that part of the OS eaten into.
-
Stanford and partners announce 2026 Conference on Physics and AI
By
–
The Center for Decoding the Universe teams up with @APSphysics
's Group on Data Science and @NeurIPSConf
's Machine Learning and Physical Sciences Workshop team to present the 2026 Conference on Physics and AI (PAI26). Learn more about this year's agenda: https://
datascience.stanford.edu/PAI26 -
Compute limits will favor agentic AI over chatbots
By
–
We are quite short of compute, and that is going to result in compute becoming very expensive for complex agentic workflows even as single-turn chatbots get cheaper. So the richest companies & most pressing use cases will use AI agents & everyone else will be stuck with chatbots?
-
Cerebras Inference Speed Performance Across Model Types
By
–
"As people began integrating AI into their day-to-day work, speed became fundamentally important. And we were just crushed with demand. Is Cerebras inference faster for specific use cases? No, it's faster across the board. Big models, small models, U.S. models, Chinese models,
-
SambaStack offers high-performance AI inference infrastructure
By
–
AI infra shouldn’t be complicated SambaStack gives teams a full hardware + software stack built for high-performance AI inference, whether you deploy on-prem or in the cloud. Learn more: https://
sambanova.ai/products/samba
stack?utm_source=x&utm_medium=organic&utm_campaign=enterprise
…