A compression algorithm like TurboQuant turns the data in the AI's working memory into a smaller, more efficient form.

You take a photo on your iPhone and email it to yourself. You try to open it on your Windows laptop, but the computer says it cannot display the file. You see a file extension you do not recognize: ...

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Memory prices are falling, and stock prices of memory companies took a hit, following news from Google Research of a breakthrough that will greatly reduce the amount of memory needed for AI processing ...

Micron Technology (MU) shares fell to $339 Monday as fears over Alphabet’s (GOOGL) TurboQuant AI memory-compression algorithm raised concerns about long-term demand for high-bandwidth memory across ...

Lam Research (LRCX) delivered a 321% total return over three years by dominating AI chip production through etch and deposition tools for high-bandwidth memory and advanced logic, with advanced ...

The compression algorithm works by shrinking the data stored by large language models, with Google’s research finding that it can reduce memory usage by at least six times “with zero accuracy loss.” ...

Running a 70-billion-parameter large language model for 512 concurrent users can consume 512 GB of cache memory alone, nearly four times the memory needed for the model weights themselves. Google on ...

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 ...

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 ...

AI has a growing memory problem. Google thinks it's found the answer, and it doesn't require more or better hardware. Originally detailed in an April 2025 paper, TurboQuant is an advanced compression ...