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 ...
A new technical paper titled “Pushing the Envelope of LLM Inference on AI-PC and Intel GPUs” was published by researcher at ...
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 ...
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, ...
Large language models (LLMs) are increasingly everywhere. Copilot, ChatGPT, and others are now so ubiquitous that you almost can’t use a website without being exposed to some form of "artificial ...
The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...
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