Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...
Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
Detailed in a recently published technical paper, the Chinese startup’s Engram concept offloads static knowledge (simple ...
NVIDIA Boosts LLM Inference Performance With New TensorRT-LLM Software Library Your email has been sent As companies like d-Matrix squeeze into the lucrative artificial intelligence market with ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...
MLCommons, the open engineering consortium for benchmarking the performance of chipsets for artificial intelligence, today unveiled the results of a new test that’s geared to determine how quickly ...
Morning Overview on MSNOpinion
AI’s next wave: new designs, AGI bets, and less LLM hype
After a breakneck expansion of generative tools, the AI industry is entering a more sober phase that prizes new architectures ...
I’m getting a lot of inquiries from investors about the potential for this new GPU and for good reasons; it is fast! NVIDIA announced a new passively-cooled GPU at SIGGRAPH, the PCIe-based L40S, and ...
Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback