Latent Space / episode intelligence
Speakers in the public record
Claim mix
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
19 published records
01 / belief
“I want to make sure that can't happen structurally. So that's why I realized that it's really important that I do this.”
02 / recommendation
“I'm going to build a box for Kama and then I'm going to show off the box I built for Kama and be like, okay, like, do you want to build?”
03 / belief
“You know, I think you wrote like, feels like ChatGPT wrote the movie and that's my worry a little bit.”
04 / belief
“I think the best chatbot models are going to be the ones where you had a thousand training runs instead of one.”
05 / uncertainty
“There's been a whole round trip with positional embeddings. I don't know if you've seen this discussion.”
06 / belief
“Like, we'll just, I think, think of it as maybe more of, like, a stipend than a salary.”
07 / belief
“I think you, right now the math was that for the price of the most expensive thing we build, which is the International Space Station, we could build one Tampa of.”
08 / belief
“Coming back to what I think is actually gonna happen is, yeah, people are gonna train smaller models for longer and fine-tune them and find all these tricks.”
09 / belief
“You've name checked Elon a few times. I think about both of you as systems thinkers.”
10 / evaluation
“That's, I mean, that's one of them where, like, I really, I put a lot of effort into CI for TinyGrad. I think CI is super important.”
11 / recommendation
“I think we need to keep our audience along with us by pausing every now and then to explain key terms.”
12 / prediction
“I think the right answer is something that looks more like queues that feed into ALUs, and then you can prefetch the loads from the memory, put in a bunch of queues, and then the queue is just like, and feeds into another queue over here.”
13 / prediction
“We have better support for ONNX than Core ML does. And we're going to have, I think we're going to pass ONNX Runtime soon, too.”
14 / prediction
“They're excited about reduced instruction set processors. So TinyGrad is, we are going to make a RISC offset for all ML models.”
15 / evaluation
“0. No PCIe extender I've tested, and I've bought 20 of them, works at PCIe 4.0. So you're going to need PCIe re-drivers.”
16 / evaluation
“No one does, of course, because it's so difficult, right? Like, actually, NVIDIA used to, I think CUDA 9 was the last one that had it.”
17 / evaluation
“It's all eventually going to be fused into one massive. So to say computer vision is solved, well, it doesn't make any sense because what's the output of a computer vision model?”
18 / commitment
“Okay, you've shown that it's worth my time, and I will put my time in because, like, let's make this better.”
19 / evaluation
“Because even the lines to express the, well, you can't use the where operator in PyTorch.”