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I'm an investor, the founder of new alchemy, co-founder Lamina1, former CEO of coinlab.com, Chairman of the Bitcoin Foundation, Ethereum security researcher, holder of patent 9298806, general nerd. Currently working at Capital6, my private equity fund.

I’ve lost more than $1bn twice - failure is the best teacher! He says to himself..

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The exabox is interesting. I wonder who the customer is; after watching the Vera Rubin launch, I cannot imagine deciding I wanted to compete with NVIDIA for hyperscale business right now. Maybe it’s aiming at a value-conscious buyer? Maybe it’s a sensible buy for a (relatively) cash-strapped ML startup; actually I just checked prices, and it looks like Vera Rubin costs half for a similar amount of GPU RAM. I’m certain that the interconnect will not be as good as NV’s.

I have no idea who would buy this. Maybe if you think Vera Rubin is three years out? But NV ships, man, they are shipping.

This looks super super useful.. I'm making an agent to agent chat tool (that I think is actually ready for testing, so please check it out) -- https://chat.corpo.llc/ or https://github.com/corpo/qntm -- and the difficulty of getting claude to check and respond to messages is real.

Basically the Claude CLI is the operating system is the product vibe I get right now.

qntm Messenger

I've been wondering this since they started it, mostly as a concern they stay afloat. Since Daniel does the work of ten, it seems like their value:cost ratio is world-class at the very least.

With the studio release, it seems to like they could be on the path to just bootstrapping a unicorn or a 10x corn or whatever that's called, which is super interesting. Anyway, his refusal to go into details reassures me, sounds like things are fine, and they're shipping. Vai com dios

There's some texture here. Elon's enriched pretty much everybody who's ever worked for and invested with him. He makes money for people throughout his orgs. Many ex-employees have said to me: "incredible opportunity, made great money, worked insanely hard, once is plenty".

Salvatore - this is cool. I am a fan of using Steve Yegge's beads for this - it generally cuts the markdown file cruft significantly.

Did you run any benchmarking? I'm curious if python's stack is faster or slower than a pure C vibe coded inference tool.

in the NIST Curve arena, I think DJB's main concern is engineering implementation - from an online slide deck he published:

We’re writing a document “Security dangers of the NIST curves”
Focus on the prime-field NIST curves
DLP news relevant to these curves? No
DLP on these curves seems really hard
So what’s the problem?
Answer: If you implement the NIST curves, chances are you’re doing it wrong
Your code produces incorrect results for some rare curve points
Your code leaks secret data when the input isn’t a curve point
Your code leaks secret data through branch timing
Your code leaks secret data through cache timing
Even more trouble in smart cards: power, EM, etc.
Theoretically possible to do it right, but very hard
Can anyone show us software for the NIST curves done right?

As to whether or not the NSA is a strategic adversary to some people using ECC curves, I think that's right in the mandate of the org, no? If a current standard is super hard to implement, and theoretically strong at the same time, that has to make someone happy on a red team. At least, it would make me happy, if I were on such a red team.