Her next lawsuit needs to be CashApp and their grotesque negligence on that front.

But again my point applies - the chances they get enough people using it that it becomes a meaningfully worse security target than lots of other existing things seems … super low.

It’s a big world, people make many choices I can’t understand (nix? Haskell? Php? ). Even if this product nailed it - the number of people who can use it is minuscule - yes even as we add Claude-enabled PMs to the software dev ranks.

Alt view with the old saying - “put all your eggs in one basket … and watch that basket!”

They can monitor extreme outliers. It’s not an issue for them.

Meaning - every new technology has both been perceived as a threa and often forced change in society. Agree maybe “it feels different” this time, but don’t you think everybody before us just said the same thing?

Also not clear if this is an actual called action.

I'm looking for a place to direct people to see the math behind it, seemed like it had potential.

Take aways:

* it’s not in prod yet. I suspect those many round trips are going to get expensive on median aka typical redistributed deployments. Curious to see how it goes once in the wild.

* they say it isn’t likely suitable for eg databases.

* they talk about formal verification, which is good and feels appropriate.

Looking forward to seeing more!

Sure, except that once you have a community at critical mass around a reasonably good tool, that trumps most other things. Momentum builds. People write tutorials, explainers, better documentation, etc. it hits escape velocity.

Feels like Lean, with Terrance Tao as a strong proponent / cheerleader, is in that space.

Everyone who argues “but language X is better” … may not be wrong, but they are not making the argument that matters. Is it better than the thing everyone else knows and can use and has more people hours going into it to improve it?

Feels like a “worse is better” situation; or maybe “good and popular is good enough”.

https://github.com/tonbistudio/turboquant-pytorch

“”” For the full technical explanation with equations, proofs, and PyTorch pseudocode, see the companion post: TurboQuant: Near-Optimal Vector Quantization Without Looking at Your Data.“