The ongoing shortage of memory chips looks likely to continue throughout the year as demand from the AI sector surges. According to Nikkei Asia, leading manufacturers are expected to be able to meet ...

Is your iPhone feeling sluggish or running out of storage space? Clearing cached files is a practical way to optimize your device’s performance and free up valuable storage. The video below from ...

TL;DR: Google developed three AI compression algorithms-TurboQuant, PolarQuant, and Quantized Johnson-Lindenstrauss-that reduce large language models' KV cache memory by at least six times without ...

Google's (GOOG)(GOOGL) TurboQuant, a compression algorithm that optimally addresses the challenge of memory overhead in vector quantization, will likely lead to the usage of more intensive AI ...

This voice experience is generated by AI. Learn more. This voice experience is generated by AI. Learn more. On March 24, 2026 Amir Zandieh and Vahab Mirrokni from Google Research published an article ...

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 ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Micron (MU) reported Q1 FY2026 revenue of $13.64B, up 57% year-over-year with non-GAAP EPS of $4.78, but capital expenditures surged 68% to $5.39B in a bet on sustained AI-driven memory demand.

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 scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. Specifically, the Key-Value (KV) cache size ...