Compression

Google published TurboQuant on March 24th. Within 48 hours the paper had 575 points on Hacker News, Micron’s stock dropped $900 million, and TechCrunch compared it to Pied Piper’s algorithm from Silicon Valley. One month later, the hype fog has cleared enough to answer the only questions that matter: Does it work? Can I use it today? And the one nobody wants to ask: Is it actually new? What TurboQuant promises (30-second recap) If you already read my previous article on the math, skip this section. ...

Multiplication is hard. Addition is easy. Any elementary school kid knows this. What they don’t know is that logarithms exist precisely to exploit this asymmetry: you convert multiplication into addition, operate in the simple world, then undo the transformation. The result is correct. The effort, a fraction. This pattern — transform the problem to a space where solving it is trivial, solve it, then transform back — is one of the most powerful in all of engineering. FFT does this with signals. Logarithms do it with products. And now Google just published a paper that does it with language model compression. ...