It turns out the rapid growth of AI has a massive downside: namely, spiraling power consumption, strained infrastructure and runaway environmental damage. It’s clear the status quo won’t cut it ...
A new technical paper titled “Pushing the Envelope of LLM Inference on AI-PC and Intel GPUs” was published by researcher at ...
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
Today LeapMind announced Efficiera, an ultra-low power AI inference accelerator IP for companies that design ASIC and FPGA circuits, and other related products. Efficiera will enable customers to ...
All over the AI field, teams are unlocking new functionality by changing the ways that the models work. Some of this has to do with input compression and changing the memory requirements for LLMs, or ...
Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...
Today LeapMind announced Efficiera, an ultra-low power AI inference accelerator IP for companies that design ASIC and FPGA circuits, and other related products. Efficiera will enable customers to ...
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