Public evidence record
Published podcast speaker
Claim ledger
10 transcript-backed records
01 / evaluation
“I don't trust benchmarks, especially when the numbers are close. I'm like, okay, this is useless now because it is completely gamified, right?”
02 / commitment
“I think we're still approximating what we have available. It's a super interesting topic, but It really depends on like how you define it, and we will have to have a discussion on the definition and then how you measure it.”
03 / commitment
“Just physics sounded so cool from their perspective, reading their books that I was like, okay, I'm going to try this, but sadly I will not be able to replicate some of them.”
04 / belief
“I think with gaming, I believe there is a new even way of interaction that's coming up with this AI experiences.”
05 / evaluation
“The character would look at you and be like, why are you looking at me with that face? And that changes the whole flow, because right now, if you just talk to talk, it's not the same as if it sees you, it sees your reaction, and then it begins a conversation and it changes and you make a state based on that and all of that.”
06 / evaluation
“Like we, we've seen papers like textbooks is all you need, right? And that is because the textbooks are starting informationally dense and it's years of a human carefully crafting like word after word after word of what they are saying.”
07 / evaluation
“They use samples. And obviously this is not necessarily apples to apples comparison because you need to check at the fine print as to how they are running this.”
08 / evaluation
“But there were product requirements, right? And this is where inference becomes very interesting because it's not about making it the fastest, it's about meeting the human perceived latency.”
09 / prediction
“The way that people were doing it was by putting tags, like literally QR codes, onto the item such that they had some ground truth and then they would label it. But that's impossible, like this is the case where synthetic data really becomes important because there is no way you're going to get the pose of the item in every single position.”
10 / prediction
“As we discover what are the use cases that are truly valuable, we are going to figure out what is the data that was actually valuable through this training process, I think, and we are going to be able to.”