Speakers in the public record
Claim mix
belief 8evaluation 7uncertainty 3prediction 1preference 1recommendation 1commitment 1
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
The useful parts, with receipts.
22 published records
“Uh, so it actually, in terms of the overall time to deploy, it’s total time savings if you spend more time on a longer model, like thinking for an hour, because then, then you, you don’t have to spend all that time during testing and rolling, you know, rolling back the deployment.”
- Publisher
- Latent Space
“Uh, so like I, I think, you know, our conversation like today has like really, uh, oh, I guess opened my eyes to a lot.”
- Publisher
- Latent Space
“Cool. Um, I think that that was all the questions I had. I said I, I have one sort of a bonus thing if you, if you wanna indulge in, uh, some Bing history.”
- Publisher
- Latent Space
“I think Andre really deserves a lot of credit for popularizing this approach. This is, uh, this is incredibly, I think, powerful and cool and You know, the, uh, even him, him just mentioning it led to a lot of gains in a lot of places in the industry, so we should be thankful.”
- Publisher
- Latent Space
“I think, I think on UCP, you know, like UCP is very important for us and, and it just we are-- UCP, we have a structured, uh, discussions, and you can read about them, and we have, uh, blog posts, and we have a big release this week, in fact, like with our catalog.”
- Publisher
- Latent Space
“I, I don’t know, I don’t know, uh, you know, it’s, uh, people va-variously refer you as like CEO or, or, uh, I don’t know what that, that, that said previous role at Microsoft was.”
- Publisher
- Latent Space
“I think that’s why we wanted to even, uh, cover them today is because this is something that if you go back even, you know, five years ago, would’ve been unthinkable.”
- Publisher
- Latent Space
“I think obviously, you know, there’s a lot of, uh, ML infra at, at Shopify that people can, uh, dive into.”
- Publisher
- Latent Space
“Do you guys use stack diffs? I don’t know if, uh, that’s a, like, a merge queue stack diff type of thing.”
- Publisher
- Latent Space
“I think I can, I can screen share, and then we can kind of go through some of the shocking stats that maybe, maybe put some numbers to what exactly is going on.”
- Publisher
- Latent Space
“I don’t know if, uh, you know, for our statisticians among us, I couldn’t believe, but we-- recently we’re looking at it, and we had to bring back, uh, CRPs, you know, Chinese restaurant process.”
- Publisher
- Latent Space
“I’m familiar with these people for the LLM, you know, autoregressive stack. But the other interesting category of these optimizers is also the diffusion people, whereas like Fel and, you know, uh, Pruna recently has come up a lot as well, which I think is like really underappreciated, uh, at least by myself, because I, I thought, oh, all the workload would be LLMs, but actually there’s a lot of diffusion as well.”
- Publisher
- Latent Space
“Uh, one of the reasons I reached out was because you started promoting more sort of internal tooling, uh, primarily Tangle, but also a lot of people have seen and adopted Tobi’s QMD, uh, and obviously, I think, uh, Shopify has always been sort of leading in terms of, uh, engineering.”
- Publisher
- Latent Space
“I, I think everybody right now is just trying to keep their head above the water ‘cause, ‘cause there, there’s so many PRs and then everybody’s CICD pipelines start creaking, the, the times are increasing, the number of bugs slipping by increasing, and you have to, have to clap on down.”
- Publisher
- Latent Space
“Lines of codes are exploding for everybody right now, or partially because AI is really mover balls, but partially just because AI can write a lot more code, you know, doesn’t get tired.”
- Publisher
- Latent Space
“Like I think for example, right, like in the audio kind, kind of use cases, the SSMs ef-effectively have unbounded context length because they, they just have to operate on like the most, the sliding window of the most recent stuff.”
- Publisher
- Latent Space
“You want to, to be able to get the image like of what humans will see because you wanna, uh, detect effects like, “Hey, if I make my images larger, will I have more sales or l- uh, fewer sales?” And like usually people’s intuition here, by the way, is that I increase my images, I will have more because they look nicer.”
- Publisher
- Latent Space
“At peer review tool, uh, time, you want to run the largest models. That means, I don’t know, Codex or, or, uh, Cloud Code is not gonna cut it.”
- Publisher
- Latent Space
“Like in general, it’s basically on par with transformers, and if you do hybrids with transformers, it’s, it’s even better. That’s why we at Shopify, when we tried multiple and we constantly try multiple models, multiple companies, we found that for small, particularly with low latency applications, when you have low latency and/or if you need longer context lengths, liquid was the best.”
- Publisher
- Latent Space
“” We then morphed it into, and very recently just released it, when you have just your site, your theme, we run over it and we say, “Hey, here’s what predicted values of, of, uh, uh, conversions are, and here’s how we think you should modify it to increase your conversions.”
- Publisher
- Latent Space
“Then the other thing that you mentioned, which also raised my eyebrows, was content-based caching, which you mentioned is, is, um, you know, is ve-very much, uh, um, a sort of efficiency measure about, uh, you know, just like recalculation only on, on sort of content addressing Which I think makes sense.”
- Publisher
- Latent Space
“We run it at, uh, thirty milliseconds, a, a tiny model, like three hundred million parameters in, but we run it in thirty milliseconds, uh, end to end for search when you, when you type a query, and then we produce all the possible things what you, what you can mean by that query and some, you know, uh, not only synonyms, but, but, uh, a que-kind of full query understanding the, the whole tree of what you might need and including your personal personalization because you might have done like previous queries and lowering it all down into the search server so that the requirements on latency obviously they are very, uh, very strict.”
- Publisher
- Latent Space