tool / uses
Zo
“I think there’s been one thing, I use another thing called zo, which is kinda like a cloud computer plus agent.”
Public evidence record
Partner · Decibel
Books, apps, and tools
tool / uses
“I think there’s been one thing, I use another thing called zo, which is kinda like a cloud computer plus agent.”
tool / likes
“First of all, you have very good support for mocking in unit tests, which is something that a lot of other frameworks don't do. So, you know, my favorite Ruby library is VCR because it just, you know, it just lets me store the HTTP requests and replay them.”
other / likes
“Yeah, I'm a big fan of Simulative AI. We had a summer of Simulative AI. Another term we're trying to coin.”
Claim ledger
13 transcript-backed records
01 / prediction
“The price of like writing code is going to zero, blah, blah, blah. But it actually seems like the value of having some sort of platform substrate is like increasing because as you build these new things, you can kind of plug them together.”
02 / prediction
“Like they need to monetize in a much shorter timeframe [00:17:00] because the costs are so high.”
03 / prediction
“Everybody needs to run code, right? And I think now all the products and the everybody's graduating to like, okay, it's not enough to just do chat.”
04 / prediction
“Actually, Singapore is the first country to build the cyber range for cyber attack training. And I think you'll see more of that.”
05 / prediction
“The v100 is about 130 teraflops of kind of like compute the gb200 at fp4 is like 20, 000 teraflops so the hardware alone today got much more powerful and I would love to maybe hear from you how at the time you were thinking about optimizing for the hardware today versus how much of an insight you had into the hardware that was coming especially working at NVIDIA and maybe people have the same discussion today it's like you know Should we optimize for the hardware of today or like for the hardware of tomorrow, because we need the results today, you know, as a business, but sometimes maybe we waste some time.”
06 / prediction
“I think before you published it, nobody thought this was like a short term thing that we're just going to have.”
07 / prediction
“I think now for the first time, there's a clear path to how do we make a 7b model good without having to go through GPT-4 or going to Cloud 3. And we'll kind of talk about this later, but I think we're seeing maybe the, not the death, but settling the picks and shovels, it's kind of going away.”
08 / prediction
“I think there's a lot of chatter obviously about synthetic data and like there was the Rephrase the Web paper that came out maybe a few months ago about using, you know, Mastral to make training data better.”
09 / prediction
“And Jensen, at his keynote, he did talk about synthetic data a little bit. So I think that's something that we'll definitely hear more and more of in the enterprise, which never bodes well, because then all the, all the people with the data are like, Oh, the enterprises want to pay now?”
10 / prediction
“Surface is a little smaller for image generation. So if you go back maybe six, nine months, most people will tell you, why would you build a coding assistant when like Copilot and GitHub are just going to win everything because they have the data and they have all the stuff.”
11 / prediction
“I think after all of this, you can quickly do the math and see that training needs to be distributed to actually work because we just don't have hardware that can easily run this.”
12 / prediction
“But good luck with the rest of your fundraise. But it's like, never mention a fundraise, but because in the prompt, it, as part of the prompt is like, if it's a pitch and it's not in the space, a pre-draft, an email, it thinks it has to do it a lot more than it should.”
13 / prediction
“think when it comes to communities, the machine learning technical community, I think in the last six to nine months has exploded.”