Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in large language models to 3.5 bits per channel, cutting memory consumption ...

Macworld explains how Apple uses “binned” chips—processors with disabled cores due to manufacturing defects—to create more ...

Macworld Over the past several weeks, you’ve probably heard the term “binned” when referring to the chips inside the iPhone ...

The big picture: Google has developed three AI compression algorithms – TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss – designed to significantly reduce the memory footprint of large ...

Older models, like the Google Pixel 10 and Samsung Galaxy S25 Plus, are now more appealing than ever. Here's why.

As Large Language Models (LLMs) expand their context windows to process massive documents and intricate conversations, they encounter a brutal hardware reality known as the "Key-Value (KV) cache ...

I enabled Personal Intelligence, connected my Google apps, and now Gemini guesses what I want without me saying it.

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

"The global artificial intelligence (AI) industry is turning its attention to ICLR (International Conference on Learning ...

Oracle tackles database infrastructure with its Globally Distributed AI Database, aiming to ensure zero data loss for mission ...