Tensormesh taps Nvidia, AMD and CoreWeave for funding to fix AI model memory problems
Tensormesh Inc. has hit upon a way to make artificial intelligence inference more efficient by eliminating the need for redundant computations, and its technology is so convincing that several of AI infrastructure giants are backing it with $20 million in funding.
Today’s round saw the participation of Nvidia Corp., Advanced Micro Devices Inc. and CoreWeave Inc., as well as the venture capital firms Valley Capital Partners and Laude Ventures. It brings Tensormesh’s total amount raised so far to $24.5 million, and it coincides with the launch of its flagship software-as-a-service offering, Tensormesh Inference.
Tensormesh’s technology is designed to tackle one of the most glaring inefficiencies of graphics processing units, which have to reprocess the same data over and over again given their limited memory caches. It’s a design challenge that stems from the way large language models work. Typically, LLM deployments treat each new request or prompt they receive as a brand new task. So even if an AI chatbot is engaged in a long-winded conversation with someone, or analyzing a document it has seen before, the GPU will need to reprocess the entire context window from scratch.
