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If Google’s AI researchers had a sense of humor, they would have called The cost of TurboQuanta new, highly successful AI memory compression algorithm announced on Tuesday, “Pied Piper” – or, at at least that’s it what and internet he thinks.
This joke is about the fictional story of the Pied Piper that was the TV series “Silicon Valley” for HBO that ran from 2014 to 2019.
The show followed the founders as they navigate the technology landscape, facing challenges such as competition from big companies, fundraising, technology and products, and (too much for us to enjoy) to impress the judges on the fictional story of TechCrunch hack.
Pied Piper’s leading technology for TV programming was a compression method that reduced file size and lossless compression. A new Google search The cost of TurboQuant it also involves high compression without loss of quality, but it is used in the middle bottle of the AI ​​machine. Therefore, the comparison.
Google research explained the art as a new way to reduce AI memory without affecting performance. The combination method, which uses vector quantization to eliminate cache bottlenecks in AI processing, would allow AI to store more information while taking up less space and maintaining accuracy, according to the researchers.
They plan to present their findings to ICLR 2026 price meeting next month, along with two methods that make this pressure possible: the quantization method PolarQuant is a training and optimization method called QJL.
Understanding the math involved here is something researchers and computer scientists can do, but the results are of interest to the entire tech industry.
If implemented successfully in the real world, TurboQuant could make AI cheaper to run by reducing its “memory” time — called the KV cache — “by at least 6x.”
Others, like Cloudflare CEO Matthew Prince, are even call this About Google Time for DeepSeek – evidence to good profit led by the Chinese AI model, which was trained to a little bit the price of its competitors for the worst chips, while remaining competitive in its results.
However, it is important to note that TurboQuant is not yet widely deployed; It’s still a lab success at this point.
This makes comparisons with something like DeepSeek, or the fictional Pied Piper, very difficult. In TV, Pied Piper’s technology will revolutionize the law of computers. TurboQuant, meanwhile, can bring value with systems that require less memory during analysis. But it can’t solve the shortage of RAM driven by AI, because it only focuses on memory, not training – which requires more RAM.
