CATL targets small-scale production of solid-state batteries by 2027: report

those same extensions can pose a risk.

Metas MTIA v2 doubles the amount of on-chip memory to triple performance on AI tasks.Also: Nvidia CEO Jensen Huang unveils next-gen Blackwell chip family at GTCMeta said it has designed a rack-mount computer system running 72 MTIA v2s in parallel.

Artificial Intelligence I asked Gemini and GPT-4 to explain deep learning AI.more advanced hardware (including next-generation GPUs) that we may leverage in the future.an 8x8 grid of processing elements (PEs).

doubled the on-chip SRAM and increased its bandwidth by 3.It is seven times faster on AI tasks that involve sparse computation.

MTIA v2 architectural diagram.

MetaThe chip is built in a 5-nanometer process technology developed by contract chip manufacturing giant Taiwan Semiconductor Manufacturing. Pau and Aymone found that replacing back-propogation with simpler math could reduce the amount of on-device memory needed for the neural weights by as much as 94%.

which is called federated learning.Some scientists advocate for splitting up the training task among many client devices.

where it could be intercepted by malicious parties.Also: Machine learning at the edge: TinyML is getting bigEfforts have been underway to conquer that computing mountain by doing things such as selectively updating only portions of the neural nets weights or parameters.