Answered raw tape
D 5 · C 4 · P 3 · Cm 3 3.90
Q Why don't you talk about the, the bottom, like, why don't we have reliable agency? What are the, the main bottlenecks as you see them?
A Yeah, I think a big part of it is the things that we train on were often really good at, and then sometimes with the things outside of that, it can be a bit, um, sometimes it's good at those things, sometimes it's not good at those things. Um, so I think, yeah, creating more data across, like, a broader range of things that we want it to be good at. Um, I think also what's interesting with, with agents is we have this, like, uh, when, when something is doing something on your behalf and it has access to your You know, your private data and the things that you use. Um, it's kind of more scary the different things it could do to achieve its final goal. Um, you know, in theory, if you asked it to, to buy you something that, like, make sure that I like it, it could go and buy five things just to make sure that you liked one of them. Right. Which you might not necessarily want. So, I think that there's definitely, like, having oversight during training is also, like, an interesting area. I think there's just, like, new things that We have to, like, develop to, you know, push these agents even further. Um, so yeah, I think that that's part of it. And then also, like, as every time we get to have a smarter, like, base model or something like this, it improves every model that's built on top of that. So I think that will also help, especially with, like, multimodal capabilities, as Tin…
AI assessment note: “a big part of it is the things that we train on were often really good at”
Answered raw tape
D 5 · C 4 · P 3 · Cm 3 3.90
Q Why don't you talk about the, the bottom, like, why don't we have reliable agency? What are the, the main bottlenecks as you see them?
A Yeah, I think a big part of it is the things that we train on were often really good at, and then sometimes with the things outside of that, it can be a bit, um, sometimes it's good at those things, sometimes it's not good at those things. Um, so I think, yeah, creating more data across, like, a broader range of things that we want it to be good at. Um, I think also what's interesting with, with agents is we have this, like, uh, when, when something is doing something on your behalf and it has access to your You know, your private data and the things that you use. Um, it's kind of more scary the different things it could do to achieve its final goal. Um, you know, in theory, if you asked it to, to buy you something that, like, make sure that I like it, it could go and buy five things just to make sure that you liked one of them. Right. Which you might not necessarily want. So, I think that there's definitely, like, having oversight during training is also, like, an interesting area. I think there's just, like, new things that We have to, like, develop to, you know, push these agents even further. Um, so yeah, I think that that's part of it. And then also, like, as every time we get to have a smarter, like, base model or something like this, it improves every model that's built on top of that. So I think that will also help, especially with, like, multimodal capabilities, as Tin…
AI assessment note: “creating more data across, like, a broader range of things that we want”
