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# Google’s New AI May Have Solved The Memory Crisis

**[Two Minute Papers](https://daily.dev/sources/twoninutepapers)** · 8 min read · 2 upvotes · 0 comments

## Summary

Google introduced TurboQuant, a method to compress the KV cache (short-term memory) of large language models using a combination of quantization, random rotation, and the Johnson–Lindenstrauss transform. Independent researchers reproduced the results, finding 30-40% memory reduction and ~40% faster prompt processing with minimal quality loss. The media-hyped '6x less memory' claim applies only to specific corner cases, but real-world gains for long-context tasks (large PDFs, codebases) are still significant. Some researchers raised concerns about overlap with prior work, though the paper was accepted for publication.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=7YVrb3-ABYE>

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Tags: [#data-science](https://daily.dev/tags/data-science), [#google](https://daily.dev/tags/google), [#llm](https://daily.dev/tags/llm)

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