01:42:07 · Thibault Sottiaux, Bernt Øivind Børnich
[01:42:07] S4: So one thing that you see as well with Soul is its uncanny ability at understanding human intent. And you know, you need shorter prompts, you don't need to explain yourself in that much detail and sort of like, you know, just gets it and then goes and like does like a very complex thing. You know, you saw the prompt for like post training, the Luna model, which is like super crisp, and then it does that, but it actually worked for many days. Yeah. And this is also like with us launching Chat50 Work, it's about making it accessible for everyone and you know, you don't need to have like a PhD to use this model. It's just like, should just behave like just like another super super smart human and you know, just kinda like get you in the moment, and that's what we're striving for. Of course, if you know, you really push it to the limit, you're always going to find new setups and this is like also a very exciting space. Know, we continue to develop like also codecs in the open source and we're seeing like, you know, all of novel ways to set up these agents and models so that, you know, you can get results in like cybersecurity and like, you know, all these other more nuanced and complex things. But for everyone, you know, you should just feel like, you know, a ton of power out of the box. [01:43:16] S5: Mhmm.
01:43:16 · Bernt Øivind Børnich, Jordi Hays, Thibault Sottiaux
[01:43:16] S5: Mhmm. [01:43:16] S0: Talk about what was important at the product layer. Fundamentally, what I think people want out of products is to just be able to talk to their computer like a really smart coworker and be able to get things done. But then you're dealing with, you know, so many users over here, millions of users over here trying to combine it and condense it into something that's simple and obviously simple things end up being exceptionally complex to actually create. [01:43:43] S4: Yeah. So if if you look at it, it's deceptively simple. You can open it on your phone. It's ChatGrifty work, you just toggle it and then there you go, you connect it to the things that you already have, your email, calendar, you know, your docs, and then suddenly you're like, okay, wait, I can ask it to process all of this information that I had over there that I had to manually like do all these things myself and it can just do all of that. And it's just like on the go and it's like on your phone in the Chateapute app you already have installed. I mean, that's the beauty of keeping it very simple. At the end of the day, we want it to be just a normal conversation between you and the agent. This is also why we decided to, you know, ship it, like, just in touch with you.
01:43:43 · Thibault Sottiaux, John Coogan
[01:43:43] S4: Yeah. So if if you look at it, it's deceptively simple. You can open it on your phone. It's ChatGrifty work, you just toggle it and then there you go, you connect it to the things that you already have, your email, calendar, you know, your docs, and then suddenly you're like, okay, wait, I can ask it to process all of this information that I had over there that I had to manually like do all these things myself and it can just do all of that. And it's just like on the go and it's like on your phone in the Chateapute app you already have installed. I mean, that's the beauty of keeping it very simple. At the end of the day, we want it to be just a normal conversation between you and the agent. This is also why we decided to, you know, ship it, like, just in touch with you. [01:44:23] S1: Mhmm. Talk about progress in computer use. What is actually driving progress there? Is this just something that sort of comes for free with scale and and model advances, or is there deliberate data collection that's happening and some sort of flywheel that's unlocking new capabilities in computer use?
01:44:23 · John Coogan, Thibault Sottiaux
[01:44:23] S1: Mhmm. Talk about progress in computer use. What is actually driving progress there? Is this just something that sort of comes for free with scale and and model advances, or is there deliberate data collection that's happening and some sort of flywheel that's unlocking new capabilities in computer use? [01:44:44] S4: Yeah. We've done a lot of efforts bespoke effort on Windows, Mac, and like mobile computer use, also like phone use as well. And so there's an entire team working on this. It doesn't just come for free, but what does come for free is like every time we push the efficiency frontier and the model gets like, you know, more efficient like at thinking and acting and it costs less tokens and it gets compressed in time, it also gets better at computer use because it reduces the latency and reduces the cost. And so the two compounds, we have a lot of gains that we're getting from also visual understanding and every time it improves, model just gets more precise so it doesn't have to correct itself. And it was like maybe it misclosed the button and they're just like, oh, it's just like, wait, I have to redo that. So every time it's like more accurate and more token efficient, computer just definitely benefits from it. And when you compare it to 5.5, it's like, you know, it's just really like three times faster. Know, we're not at all hitting a wall here in, like, how fast we can do computers.
01:45:39 · John Coogan, Thibault Sottiaux
[01:45:39] S1: Yeah. Can you talk about how the role of member of technical staff is evolving? Because you're you're you're talking about Soul Ultra going off and working for days at a time. And at a certain point, your job sort of evolves to if you have a launch tomorrow, don't kick off a task that takes four days. Even if the model's capable of it and will deliver something great in four days, you need it tomorrow. And so you have to size your workloads appropriately. How is the how how are you thinking about sizing work and and actually delegating the right the right chunk of work at this stage? [01:46:19] S4: Yeah. I find your question very interesting because, it actually highlights, like, a shift in our thinking over you know, since we had five sixes, you don't really instruct necessarily, you know, for a task that's gonna take four days. It's like, you know, you tell it all the information that you have. So, know, you're like, Hey, I have a launch tomorrow. Yeah. Right? And then it's like, keep track of the time and like understand that, you know, the PR needs to land, like, you know, I'm in that or like by 2AM, it will just like reason over it. Yep. You're not the one that needs to manage like, you know, all of that extraneous like complexity. Yeah. And so that's it. What you're seeing as well, like, you know, your relationship with the agent like changes over time as it gets more intelligent and you're just like, oh yeah, can just talk to you like, you know, another like, you know, super smart human.
01:46:19 · Thibault Sottiaux, Jordi Hays
[01:46:19] S4: Yeah. I find your question very interesting because, it actually highlights, like, a shift in our thinking over you know, since we had five sixes, you don't really instruct necessarily, you know, for a task that's gonna take four days. It's like, you know, you tell it all the information that you have. So, know, you're like, Hey, I have a launch tomorrow. Yeah. Right? And then it's like, keep track of the time and like understand that, you know, the PR needs to land, like, you know, I'm in that or like by 2AM, it will just like reason over it. Yep. You're not the one that needs to manage like, you know, all of that extraneous like complexity. Yeah. And so that's it. What you're seeing as well, like, you know, your relationship with the agent like changes over time as it gets more intelligent and you're just like, oh yeah, can just talk to you like, you know, another like, you know, super smart human. [01:46:58] S0: Yeah. Yeah. Talk about the efficiency of the model, what work went into that, why why it matters, you know, what kind of conversations you're having with, you know, big customers, all that stuff.