It seems like wero [0] is making some progress on this front without relying digital euro or on crypto.

0: https://en.wikipedia.org/wiki/Wero_(payment)

It's most probably ZenStack given the description: https://zenstack.dev/

yes sorry, typo, i meant ZenStack!

The analogy between projects/companies and governments is missing big components though.

- "Benevolent Dictators" of companies or projects have to obey the law - They can't forbid competition or alternatives - Every participant can leave at any time - If they burn the organization to the ground, the worst case scenario is the organization get replaced and people move on

I think it shows that we're using the word "dictator" way too casually in that case.

Do you have a chat example you can share where you found it to work great? I feel that the performance varies a lot between domains.

You mentioned a model released this week. Is it Lumina new model by any chance?

Imagen 3 002

Also commits. I imagine that there is a lot of information to gather from the history of repos in addition to the "static view" of a codebase.

However, it doesn't seem trivial to do deduplication in that case without removing relevant/necessary context.

I'm totally with you on the evolution of motor tech because of drone and also personal mobility (scooters and hoverboard motors are a steal for what they can handle).

While high torque motors got way cheaper, especially with MIT Cheetah "clones" getting easily available, they're still at least 200-500 a pop (depending on the torque needed for each articulation) from what I could find.

I might not know where to search for the real gems though. Where do you search for cheap powerful servomotors?

I can't find any information that show a difference as large as 2x. Do you have a specific comparison point in mind?

From Nvidia and AMD, I read sparse fp8 at 7 PFLOPs for B100 [0] vs 5.22 PFLOPs for mi325x [1]

Nvidia doesn't give the dense fp8 so that's the easiest comparison I could get.

[0] https://resources.nvidia.com/en-us-blackwell-architecture [1] https://www.amd.com/en/products/accelerators/instinct/mi300/...

But Meta is the main company behind Pytorch development. If they make it work and upstream it, this will cascade to all Pytorch users.

We don't have to imagine far, it's slowly happening. Pytorch for ROCm is getting better and better!

Then they will have to fix the split between data-center and consumer GPU for sure. From what I understand, this is on the roadmap with the convergence of both GPU lines on the UDNA architecture.

When you already know what you building, but not when you're doing exploratory data analysis for example.

There is a good reason why the ML community took Python as the favorite language overall.