An analog in-memory compute chip claims to solve the power/performance conundrum facing artificial intelligence (AI) inference applications by facilitating energy efficiency and cost reductions ...
The researchers’ findings point to significant opportunities for GSI Technology as customers increasingly require performance-per-watt gains across various industries, including Edge AI for ...
ATLANTA--(BUSINESS WIRE)--d-Matrix today officially launched Corsair™, an entirely new computing paradigm designed from the ground-up for the next era of AI inference in modern datacenters. Corsair ...
Startup launches “Corsair” AI platform with Digital In-Memory Computing, using on-chip SRAM memory that can produce 30,000 tokens/second at 2 ms/token latency for Llama3 70B in a single rack. Using ...
South Korean chip startup Xcena is betting that AI's real bottleneck is not compute, but memory.
A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...
In popular media, “AI” usually means large language models running in expensive, power-hungry data centers. For many applications, though, smaller models running on local hardware are a much better ...
Artificial intelligence computing startup D-Matrix Corp. said today it has developed a new implementation of 3D dynamic random-access memory technology that promises to accelerate inference workloads ...
CHANDLER, Ariz.--(BUSINESS WIRE)--Everspin Technologies, Inc. (NASDAQ: MRAM), the world’s leading developer and manufacturer of Magnetoresistive Random Access Memory (MRAM) persistent memory solutions ...
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