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 ...

What if the future of artificial intelligence wasn’t about building bigger, more complex models, but instead about making them smaller, faster, and more accessible? The buzz around so-called “1-bit ...

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 ...

Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...

One-bit large language models (LLMs) have emerged as a promising approach to making generative AI more accessible and affordable. By representing model weights with a very limited number of bits, ...

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 ...