AI NewsGoogle unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

Google unveils TurboQuant, a new AI memory compression algorithm — and yes, the internet is calling it ‘Pied Piper’

5:24 AM IST · March 26, 2026

If Google’s AI researchers had a sense of humor, they would have calledTurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, atleastthat’swhattheinternetthinks. The joke is a reference to the fictional startup Pied Piper that was the focus of HBO’s “Silicon Valley” TV series that ran from 2014 to 2019. The show followed the startup’s founders as they navigated the tech ecosystem, facing challenges like competition from larger companies, fundraising, technology and product issues, and even (much to our delight)wowing the judges at a fictional version ofTechCrunch Disrupt. Pied Piper’s breakthrough technology on the TV show was a compression algorithm that greatly reduced file sizes with near-lossless compression. Google Research’s newTurboQuantis also about extreme compression without quality loss, but applied to a core bottleneck in AI systems. Hence, the comparisons. So Google TurboQuant is basically Pied Piper and just hit a Weismann Score of 5.2https://t.co/WievkwijjDpic.twitter.com/4rirvu2YyV Google Researchdescribed the technologyas a novel way to shrink AI’s working memory without impacting performance. The compression method, which uses a form of vector quantization to clear cache bottlenecks in AI processing, would essentially allow AI to remember more information while taking up less space and maintaining accuracy, according to the researchers. They plan to present their findings at theICLR 2026conference next month, along with the two methods that are making this compression possible: the quantization methodPolarQuantand a training and optimization method calledQJL. TurboQuant is the new Pied Piper 🤣pic.twitter.com/iMAYJs02zt So basically TurboQuant is Pied Piperhttps://t.co/Zx9Oq84tSLpic.twitter.com/JPZjz8M3Wp Understanding the math involved here is something researchers and computer scientists may be able to do, but the results are exciting the wider tech industry as a whole. If successfully implemented in the real world, TurboQuant could make AI cheaper to run by reducing its runtime “working memory” — known as the KV cache — by “at least 6x.” Some, like Cloudflare CEO Matthew Prince, areeven calling thisGoogle’sDeepSeek moment— a reference to theefficiency gainsdriven by the Chinese AI model, which was trained at a fraction of the cost of its rivals on worse chips, while remaining competitive on its results. This is Google’s DeepSeek. So much more room to optimize AI inference for speed, memory usage, power consumption, and multi-tenant utilization. Lots of teams at@Cloudflarefocused on these areas.#staytunedhttps://t.co/hHoY4sLT2I Well, we all know who stole the Pied Piper codebase nowhttps://t.co/Inv0nlMYnP Still, it’s worth noting that TurboQuant hasn’t yet been deployed broadly; it’s still a lab breakthrough at this time. That makes comparisons with something like DeepSeek, or even the fictional Pied Piper, more difficult. On TV, Pied Piper’s technology was going to radically change the rules of computing. TurboQuant, meanwhile, could lead to efficiency gains and systems that require less memory during inference. But it wouldn’t necessarily solve the wider RAM shortages driven by AI, given that it only targets inference memory, not training — the latter of which continues to require massive amounts of RAM. Pied Piper would have been a better namehttps://t.co/qNZmtANFhs