The reason why large language models are called ‘large’ is not because of how smart they are, but as a factor of their sheer size in bytes. At billions of parameters at four bytes each, they pose a ...
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 ...
Huawei, a major Chinese technology company, has announced Sinkhorn-Normalized Quantization (SINQ), a quantization technique that enables large-scale language models (LLMs) to run on consumer-grade ...
“Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the ...
Microsoft’s latest Phi4 LLM has 14 billion parameters that require about 11 GB of storage. Can you run it on a Raspberry Pi? Get serious. However, the Phi4-mini ...
TOKYO, Sept. 7, 2025 /PRNewswire/ -- Fujitsu announced the development of a new reconstruction technology for generative AI. The new technology, positioned as a core component of the Fujitsu Kozuchi ...
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 ...