Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are effectively massive vector spaces in which the probabilities of tokens occurring in a specific order is ...

Google's TurboQuant combines PolarQuant with Quantized Johnson-Lindenstrauss correction to shrink memory use, raising ...

The launch of Google's TurboQuant has fueled a nasty sell-off in artificial intelligence (AI) memory and storage stocks.

Shares of Micron Technology(NASDAQ: MU) were taken out to the woodshed in March, tumbling as much as 18.1%, according to data ...

On March 25, 2026, Google Research published a paper on a new compression algorithm called TurboQuant. Within hours, memory ...

Even as models keep getting larger, some companies are moving models in the opposite direction — with some impressive results. Caltech-originated AI ...

Google Quantum just cut the qubit requirement to break Bitcoin encryption by 20x, and 6.7 million crypto addresses are in risk.

Bernstein upgraded Western Digital to Outperform from Market Perform, hiking its price target to $340 from $170, arguing that a sharp pullback driven by fears over Google’s new TurboQuant compression ...

A new compression technique from Google Research threatens to shrink the memory footprint of large AI models so dramatically ...

A small error-correction signal keeps compressed vectors accurate, enabling broader, more precise AI retrieval.

Google has released a new compression algorithm this week that it says can shrink the memory an AI model needs during inference by at least six times—.