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
35 published records
01 / belief
“Like hugging face. I think every. Library, like all these people at Hugging and Face, were working super hard this weekend to make day zero support for Llama2.”
02 / uncertainty
“Near, especially after three organizational restructures of researchers hopping, playing hopscotch from one org to another, and being in between, in between jobs. I don't know.”
03 / belief
“One of the things that I've really been excited about, and I think Qualcomm made an announcement with Meta and they said they're going to be looking at optimizing it for Snapdragon hardware, accelerating it.”
04 / observation
“Indeed, we are the first immorals. It's the way to achieve immortality. Yeah. You know, immortality take it.”
05 / belief
“I think we have something like 350,000 people all around the world who are sort of helping with this stuff.”
06 / belief
“Generally we're trying to operate in the scale a little bit smaller than what Meta is doing cuz we obviously don't have that kind of resources at a startup. So I do a lot of technical research and also try to actually engage and communicate that with the community and specifically, Llama, I think I was most interested on kind of the research side.”
07 / belief
“I think may like, it seems like now that both surge and scale are claiming some part in it, which I find hilarious.”
08 / belief
“You know, I I think we should all be incredibly, you know, appreciative that Meta is doing this and it, and it's not, you know, maybe quite perfect, you know, for some of the reasons that folks are are talking about.”
09 / belief
“I think you guys use the magic word, which is open source, and everybody has a, has a different, different definition.”
10 / belief
“The full data sets of of Lama as long as we are able to eval for everything that we want to know about. I think we actually have to live with AI becoming more and more of a black box.”
11 / belief
“AI apparently had early access to this and now released a a, I think open source, like full open source toolkit to fine tune mosaic and which is now Databricks also chime in, but it's now super simple to fine tune LAMA on their you know, infrastructure.”
12 / belief
“We've seen this with a two, two line change that you can, you can make Lama forget about the context it was trained on, and there was back and forth about how effective this is and whether or not it suffers from the same dip, you know, in the middle of the context. But this rope scaling trick then was verified by folks from, I think Microsoft, independently from that guy Kaiko, Ken Devrel, and I, I see some folks in the audience here who are participating in this.”
13 / belief
“I think that the Chinese universities have, have made some interesting progress there.”
14 / belief
“I don't care about the doom scenarios. I care about building stuff with, with what we've got.”
15 / belief
“I think to a lot of the AI engineers audience that we have, they're not as deep into the details of the papers.”
16 / belief
“I, I wish, I wish we could close enterprise customer security requirements on the vibes, but at least in my experience at at scale people do, you know, there there's some compliance function somewhere in the organization that has to sort of check the boxes that you're not, you know, gonna get screwed on later.”
17 / belief
“I, yeah, we do, we do, we do a lot of code sort of data acquisition right now, so I think that's definitely in the wheelhouse.”
18 / commitment
“Again, if somebody wants to be really useful, publish a nice detailed step-by-step instructions, they're getting that working and I will benefit from it and so will load of it.”
19 / belief
“All right. I think unless you dunno if you have any predictions. I, I, I think I'm kind of out.”
20 / belief
“I agree with everything you say, but at the same time, right now, I've got a whole bunch of models that I'm choosing to be to, to, that I'm trying to choose between, and I don't have the information I need to make the decision.”
21 / belief
“Usage restrictions, I think, I think for evaluating models, there are very few restrictions for use of these data sets.”
22 / belief
“I think he's got a few interesting things to say about how scale is thinking about these things.”
23 / belief
“I, I think the commercial use of this is gonna be off the charts very soon, like at hugging face.”
24 / uncertainty
“We didn't I don't know, since, since nobody here worked at Meta I would rather not go, not go down that path.”
25 / belief
“We'll clean up the audio of this thing and post it tomorrow on the in space, but otherwise, I think we should follow what Russell and, and Nathan and the others have been saying, which is go play with Llama2.”
26 / recommendation
“Could somebody please figure out how to do that with hugging face transformers, then publish the world's most straightforward how to do this document because I have not managed it yet.”
27 / recommendation
“We like did a, like a nice experimentation of that hugging face and it's, it's out there, it's ready for someone to invest more time in it and do it.”
28 / prediction
“I like, that's what everyone in my circles is saying is the trend and given machine learning in the last few years, I think trends tend to be stickier than most people expect them to be.”
29 / preference
“I think for, for languages, and I've tried and my go-to like vibe check with these models is to, with the, especially the open source one is the ability to translate, the ability to understand the languages.”
30 / commitment
“Because I think one of the big moments with Uber pajama was like, okay, we can take the LAMA one data mixture, use all the open source data sets and just run GPUs at them.”
31 / evaluation
“I think technical terms are like deduplication, so you don't wanna pass the model, the same text, even if it came from different websites and there's tons more that goes into this.”
32 / recommendation
“You know, you can already run it on your local computer with two bit precision, which is kind of crazy if you stop and think about that for a second, that with two bits you can actually run a super advanced language model on your own computer. So I, I think I, I just think this is a huge, huge deal for startups and I think if you're a startup founder working in ai, you know, you, you really should be taking a look at, at open source models now and seeing how they, how they can be used to, to kind of deepen your moat and, and, you know, build a really great AI product.”
33 / evaluation
“Because open AI will not randomly deprecate your models on you, you know, every three months. And I do think that for people who want a certain level of stability and are okay with trading off not being state of the art in three months I think that is a perfectly reasonable tradeoff.”
34 / evaluation
“Now the big thing is we have commercial licensing, but the amount of people, I don't know if you guys noticed, but like the amount of people who signed, quote unquote in support of releasing these models, Paul Graham and Mark Andreesen, and like a bunch of other folks, like in addition to the model, they also released kind of a counterweight to the moratorium papers and all the AI safety stuff.”
35 / evaluation
“I don't, I'm really frustrated by this because the, the language says you cannot train a competing large language model.”