SemiAnalysis Weekly
00:36:21 · Jordan Nanos, Andrew Megalaa
[00:36:21] S0: Makes sense. Just to... If you could expand on that a little bit more, because I think I know the backdrop. You're specifically talking about the reason for focusing on these domains specifically, rather than... Like, the choice to do that, rather than just taking a cross section of all knowledge work in the economy and saying we're gonna have tasks for every single thing that people do across the economy. Right? Yeah, I think the thing that the listeners are probably thinking about right now is just the concept of AI driven job loss. If people are using Frontier Intelligence and they're gaining these productivity improvements, or they're making more money, or they're winning more things, maybe you can talk about how does running through a benchmark like this inform your point of view on whether AI is going to yeah, cause job loss in the next year or two years, even five year time horizon? [00:37:22] S2: I actually think
00:37:25 · Max Kan
[00:37:25] S1: they're like orthogonal in some sense because we don't... We especially choose not to cover a lot of sort of the white collar knowledge work domains that people are probably most afraid of drop loss occurring, like, I don't know, customer service or something like that. In terms of whether or not we will have, like, massive job loss from AI, it's really hard to say. I think a lot of the doomers have probably been very pleasantly surprised by sort of how AI plus human, like, coworking has evolved over the past year where it's like every... Any any software engineer that sort of, like, has their eyes on the ball will probably tell you that Opus, when given sort of like a well specified problem, is just like a better software engineer than me, period. But at the same time, like, good software engineers are more valuable today than they've ever been. Now is it possible we're sort of in this, like, Goldilocks zone where the humans can... Like, a lot of humans can still provide kind of that, like, taste and supervision and judgment that makes it so that, like, them plus the model is, like, way, way more effective than just the model. But then, like, maybe two years from now, you actually only need, like, one dude at each company who's, like, supervising all the software engineering and, like, basically, everyone else got fired. Maybe. I don't know. I think it's possible that's the world we end up in. But it's also possible it's not. I think we just have to... You really gotta pay close attention to the model capabilities to see. I would
00:39:05 · Andrew Megalaa, Max Kan, Jordan Nanos
[00:39:05] S2: say it's definitely raised the bar for the kind of person you're looking for to like work like on stock. Like when you're when you're looking at like software engineering, for example, [00:39:17] S1: like I feel bad for the interns. [00:39:19] S2: Yes. Essentially. Like, you have to be really good to like provide value higher than just pure like Opus at this point as a software engineer. [00:39:26] S1: Yeah. Because I think a lot of people viewed interns as like, oh, I'm gonna... These are the people who I give my well specified, well defined problems I don't wanna do and they're gonna go do them for me. But obviously, now you just tell Claude to do that. And then sort of all the additional overhead of managing an intern oftentimes becomes sort of just like unbearable in those cases. [00:39:47] S2: I know one of the big quant trading firms had a post around this. It was like... Yeah. Really? Yeah. They they said their interns, like, finish their projects in the first few weeks this year compared to previous years. [00:39:59] S1: Hey, least interns, how do you say Ireland? That's good. Yeah. And [00:40:03] S0: I think the typical response from people is that you need to get more ambitious. It makes sense. I mean, going back to cybersecurity, where I've been doing some work recently. We saw this recently just with the increase in CVEs. I posted this on October 1. It's been a month. I don't have an update. There's a lot more than just this at this point.
00:40:03 · Jordan Nanos, Max Kan, Andrew Megalaa
[00:40:03] S0: I think the typical response from people is that you need to get more ambitious. It makes sense. I mean, going back to cybersecurity, where I've been doing some work recently. We saw this recently just with the increase in CVEs. I posted this on October 1. It's been a month. I don't have an update. There's a lot more than just this at this point. [00:40:26] S1: Yeah. Dude, is is the whole Internet just like broken now? Dude, what's what's gonna happen? What are you gonna do, Jordan? [00:40:33] S0: Well, I think it's a... The... Yeah. I can [00:40:36] S2: I mean? [00:40:36] S0: Do that in a lot more detail. Let's save that for another time, but let's use it as a way to make the point that there's, I think there's a lot more demand for cyber security experience right now, even when using the models. [00:40:51] S2: Yeah, for sure. [00:40:52] S0: And I think that's one of the first domains as a product of software engineering that's getting knocked down. But if you're pushing the frontiers of material science, for example, you're probably not automating away the jobs of the material sciences. You're probably starting to discover a whole bunch of new materials that need to go through the whole discovery phase and a [00:41:12] S1: lot Well, no, think it is very possible that you have automated the job of your PhD candidate assistant if you're a cracked material scientist. [00:41:20] S2: I think this is actually exactly what we've heard from [00:41:23] S1: our partners.
00:41:23 · Max Kan, Jordan Nanos, Andrew Megalaa
[00:41:23] S1: our partners. [00:41:24] S0: Yeah. If they have no ambition to go beyond what they were doing today or last year Yeah. Then, yeah, there's nothing useful for them to do. But if they have ambition to accomplish more with the tools that are at [00:41:37] S1: the disposal. Yeah. If the the person who would have been forced to just be, you know, kind of some PhD candidate grunt worker two years ago can now kind of leverage their infinite PhD grunt workers on tap to elevate themselves and, you know, just do way more interesting material science, that's great. We'll just have to see sort of... I I mean, I think I'm generally very optimistic kind of human agency and people being able to kind of, take their life in their own hands and, like, you know, do whatever makes them happy. And so I am just kind of bullish People kind of using these tools to be, just up leveling themselves essentially. We'll have to see what actually happened. [00:42:19] S2: It's interesting. I actually completely disagree with that. [00:42:22] S1: Andrew Andrew's a hater. [00:42:23] S2: No. Think I most people... Well, I mean, when you look at it, like most people in America, they just want to go in, put their hours in and go home. They like don't care that much about their careers and like... And like maybe maybe actually like this is what forces them to care. Cause otherwise, you won't be able to provide value, but we'll see. Yeah. Interesting.
00:42:23 · Andrew Megalaa, Jordan Nanos, Max Kan
[00:42:23] S2: No. Think I most people... Well, I mean, when you look at it, like most people in America, they just want to go in, put their hours in and go home. They like don't care that much about their careers and like... And like maybe maybe actually like this is what forces them to care. Cause otherwise, you won't be able to provide value, but we'll see. Yeah. Interesting. [00:42:43] S0: Okay. Let me go back and get some quick reactions to results that we kind of glossed over. So, you love Opus 5.5. Were you super happy to see it come out on top on a lot of these leaderboard charts or justifying me? What... Where'd you get that insight? [00:43:03] S2: I mean, obviously, like, you know, I'm I'm glad that my subjective experience was validated. Though, you know, some domains that I am not particularly involved in, like, it was very clear that Astra was just, like, ridiculous... Ridiculously strong on. Some of these, like, material science, but also, you know, like some of the engineering stuff is very clear that like Astra was like a step ahead there. And maybe that's just because we don't have Table 5.5 yet, but, you know, we'll see. But it's good to see that like different labs have different strengths because, know, there's spike here in different things so you can leverage whatever is best for what you're actually doing. [00:43:44] S0: Yeah. Makes sense. How about Gemini 4 Carbon? Quick take there. We saw Sundar quote tweeted everything there. You guys are excited about that. Like [00:43:55] S1: Yeah. That was sick. Shout out Sundar. I mean,