Poolside：弥合模型与人类智能的鸿沟
Poolside 的核心使命是弥合当前AI模型与人类智能之间的差距。公司致力于从零开始构建自己的模型，其基础理念源于两年前的洞察：单纯的“下一个token预测”虽然是一项重大的技术突破，但必须与强化学习（Reinforcement Learning）相结合，才能实现真正的飞跃。过去两年半的时间里，Poolside 一直专注于此，目前已迭代至第二代模型，即Malibu agent。
Original English
How many people here know what poolside is and does? Anyone? Anyone? Yeah. So, let's talk about that real quickly. Poolside exists to close the gap between models and human intelligence. That's literally it. That's what we're here to go do. We're building our own models from scratch to do this. We're based on the idea 2 and a half years ago that we thought next token prediction was an amazing technological breakthrough, but it need to be paired with reinforcement learning really to make that leap. So that's what we've been doing for the past 2 and a half years. So we're on our second generation of models now, Malibu agent.高风险环境下的AI代码实践
在实际应用层面，Poolside 展示了其AI助手在处理高风险代码环境中的能力。演讲者通过一个演示，展示了如何使用其 Malibu agent 在 Visual Studio Code 中，将政府用于运行关键基础设施的 ADA 编程语言代码库，转换为 Rust 语言。这并非使用第三方模型（如 OpenAI 或 Anthropic），而是完全基于 Poolside 自主训练的模型和专有技术。这种能力在政府和国防等高后果代码环境中尤为关键，因为在这些领域，AI代理需要严格的权限控制和高度的可靠性，不能随意执行操作。演示中，AI成功生成了大量代码，并自动编写了测试脚本，验证了转换的有效性，包括数据库操作和代码库的添加与构建。
Original English
So as I said, you were supposed to see him today, but there's I don't know. Our airline system kind of works sometimes, maybe. So he's stuck in California, but uh we thought we'd just walk you kind of through some um some demos here today. So what you're looking at here is a very modern programming language that the government uses to run all the world's critical infrastructure called ADA. Anyone familiar with ADA? Yes. Yes. Okay. So everyone I saw put their hands up for ADA either has no hair or gray hair like me. So that should tell you what's going on here. So ISO, why don't we uh why don't we figure out what's going on with this codebase here? Well, let's start asking what the codebase is about. That's great. And what you're seeing here is obviously our assistant in in Visual Studio Code backed by poolside agent, a model we train from scratch using our proprietary techniques. Um, and you can see what's going on here. Kind of the stuff you expect from an agent. Uh and obviously the form factors of all of these things are going to change a couple of times over the next couple of years, but you know people seem to like VS Code. Uh so we're going to you know show you this demo here today. So you can see from this it kind of went through told you what this codebase is all about but um you know these things run in our satellites and uh I don't know anything about ADA but I do know a lot about a couple of other programming languages. So uh ISO what do we want to do here? Why don't we uh see what this thing might look like in Rust? Let's do it. Let's ask it convert this database to rest. So obviously you're going to see what's going on here. Again, if you guys have used other tools, you're not going to expect too much of the difference for what's happening here. Except that again, we're backed by our own model. We're not using Open AI. We're not using Anthropic. This is poolside. And poolside is a bottom and top stack that is right now if no one's touched it and I know no one in this room has touched this unless you work for a three-letter agency, a defense contractor, or you've sent missiles somewhere that we're not going to talk about in this session. Um because that's where we're working. We're working in high consequence code environments for the last year inside the the government and the the defense sector. Um as you can see from this demo. Um so what you see here is is kind of going through doing the conversions. What you see in the middle pane is something that we built to kind of show you as the streams come through all the different changes that are happening. Um, one of the tricky parts about working on inside the defense sector and things like that is you can't have an agent that's just going to run around and do stuff. I mean like I can't walk into half of these buildings. You can't give an agent access to these data source and just say, "Hey, go nuts." You need to have the right permissions. You got to actually really ratchet these things down to do things inside those environments that you know they feel comfortable with. So, uh, where are we on this now? What is is it trying to fix itself yet? Yes, it's it wrote about 1152 lines of code. Uh, and it just popped up a command start and tested, excuse me. Uh, so we see here all the files on the left hand side that it created. Uh this is essentially our live diff view that's available. Uh and as we see it's currently starting to actually test it out. So this is the part where we just sit here and watch this for 3 minutes and I see nothing. No. What you see the good thing is that this is a very fast inference. Yes. So 1100 lines of code. Did it task completed? Do we know if this works yet? Well, let's have a look. So it actually wrote some bash commands to test it. And when we check out the output of those, this actually looks pretty good. We ask can we verify that to run it? Let's go verify it. So of course our agent came back and gave a summary of what it did. But let's just ask how to run this. Okay. So, I'm going to go open up now. So, it says this is how I can run the ADA version and this is how I can run the Rust version. Let's run the Rust version. Perfect. Let's have a look at We might be hitting an actual an actual demo bug. Let's have a look. Let's see what happens. I know. No, no. Just warnings. Just warnings. Do we have an unwrap in there that we need to take care of? I heard that those things are dangerous. So, right now there's a ripple. Uh, let's hit help. See what we're able to do. So, it looks like we have a set of commands. I'm going to be lazy. I'm going to copy paste these queries. So, create table users. Okay. So far so good. Let's insert a record. Okay. Well, let's find out if it actually did its job. Select start from users. Okay, we've got a record here. That's nice. Now, now I want to actually uh you see if I use the up arrow, it doesn't actually allow me to cycle through commands. Let's ask it to add a feature. Uh allows me to use the up arrow to cycle through. I think it will understand my center. The one thing we know about ISO is he actually does know how to read and write but he can't type. So all those errors that you're seeing in there. Uh yeah. So it looks like the agent's identified a package that we can use. Let's just quickly look here. Compare this to the Virgin one. And it looks like it's adding a library called rusty line and changing the files accordingly. It's currently built it and it looks like the build output is successful. There's some warnings. We'll ask it to clean those up later on. And it's now starting to test it. Okay, apparently it works. It's going to It wrote itself a little bash script to test the history. It's wrote itself a little final demo script. So let's let it Okay. So, and it gave us the summary. Well, now how do I rerun this? I do kind of know that, though. So, let's just should know that. That was 30 seconds ago. Let's build it. And let's run it again. Okay, let's do a help. And oh yeah, that's the up arrow. It works. Very nice.超越编码：AI的多模态能力与交互界面
Poolside 的模型能力远不止于代码生成。它们在各类知识工作领域均表现出色，并且具备情感智能，能够进行富有创造性的任务，例如为孩子写睡前故事。演讲者提到，当前展示的 Visual Studio Code 集成界面只是 Poolside 平台的一个入口。对于已采用 Poolside 技术的组织，还存在其他交互方式，包括 Web 界面以及可下载到本地机器的独立代理。尽管公司不主推其娱乐性功能，但这些能力展示了模型在理解和生成多样化内容方面的潜力。
Original English
Now, our models aren't just capable coding agents. They're capable in lots of areas of knowledge work. They're also emotionally intelligent. They're fun. They're great to write bedtime stories with for the kids. So, I'm going to ask you to write me a poem about all these changes, but that's just more for fun. So, as Isa was saying, this is just an interface into our platform. There's other interfaces into it if you're inside one of those organizations that has adopted poolside. So this is the coding interface into it but we also have other ways in which you you can interact with it web as well as an agent that you can download on your machine but um yeah we don't really tout the poem writing or the songwriting though I did send this to my wife to see and I have been sending her love letters written by poolside so I kind of hope that she did not enter this session to know exactly how I've been doing that for the past 6 months but uh yeah so this is kind of poolside this is what we've been up to算力驱动的未来：下一代模型与平台扩展
Poolside 正在为下一代模型的发布做准备，其核心驱动力之一是计算能力（Compute）的显著提升。随着超过 40,000 个 GB300 的上线，公司能够训练出更强大的模型。预计在明年年初，下一代模型将公开发布，并通过自有 API 提供服务，同时也会集成到 Amazon Bedrock 等平台。这将使全球的开发者能够利用 Poolside 的模型来构建各种工程助手，如代码编辑器插件（cursors, windsurfs, cognitions, replets）或其他类型的应用程序。Poolside 采取垂直整合的策略，从德克萨斯州的自建数据中心到模型训练，旨在全面掌控并推动 AI 技术的进步。
Original English
Um, so as I said, Malibu agent is as a second generation. We've got a ton more compute coming online and that's when we're training our next generation. That is be going to be the one that comes out publicly to everybody very early next year. We're going to have it behind our own API. It'll be on Amazon behind the bedrock API. Anybody in the world who's building out any sort of on a one side the engineering assistants like the cursors, windsurfs, cognitions, replets of the world, you can use ours. or if you use building out on any other side of the fence, the Harveys, the writers, the whatever applications of the world, there's going to be a fifth model out there that's going to be at that level that you can you can consume. But we're dead set on doing this and bringing this out to everybody in the world and kind of advancing that state-of-the-art and we're just going to keep pushing that out. So, that's kind of who we are. Um, and uh you can find out very little more at our website since we don't put much out there. So, I would say that it's been a pretty incredible journey for the last 2 and 1/2 years of starting entirely from scratch and now building to a place where we see our models have grown up to become increasingly more intelligent. And the kind of missing ingredient that we had was compute. And now that it's unlocked for us and and with a large number of over 40,000 GB300s coming online, we see how we can start scaling up some of those models uh to get even further uh in in their level of capabilities and software development and other types of long horizon knowledge work. We're really focused on the fundamentals, building intelligence, and being able to scale up and serve it. And it's why we go full vertical. It's why we go from our multi gigawatt campus in West Texas where we're building out data centers building out models. And the interface that you saw today is just our version of an expression.合作共赢：携手伙伴构建AI生态
Poolside 积极寻求与业界伙伴的合作。公司认识到，目前许多公司在现有模型基础上进行二次强化学习和微调，通常是基于顶级的开源模型。Poolside 希望能与这些公司建立伙伴关系，让他们能够在其模型基础上进行开发，无论是在早期阶段还是当前版本。他们相信，通过更紧密的合作，能够共同推动 AI 技术的发展。Poolside 认为，世界过去由智能驱动，未来也将继续如此，因此与他们合作将是构建未来智能的关键一步。
Original English
As as our models are are getting more capable, we'd love to also see who wants to build with them. Right now, the the vast majority of of you know, companies that are doing additional reinforcement learning and fine-tuning on top of models are are doing it on what I would consider right now the you know, best-in-class open source models, the the Quens and Fumies and Miniaxes of the world. And uh we'd like to start figuring out how we can you know partner with you with our our models anywhere from any checkpoint early on to where we are today for you to be building closer together with us on top of things. Uh we haven't really figured out the approach to it yet. Uh but I think since we have this audience it's uh it's not a bad place to put it out there and so definitely reach out to us. Uh we think the world till date was built by intelligence. The world in the future has been built on top of intelligence and so be a great way to partner.创业初心与AGI的“青春期”
Poolside 的创立源于 Jason Warner 和 Eiso Kant 之间一段颇具戏剧性的渊源。Jason Warner 在 2017 年加入 GitHub 时，曾尝试收购 Eiso Kant 的公司，当时 Eiso Kant 已经实现了基于 LSTM 的代码补全功能，甚至早于 Transformer 架构的成熟。尽管收购未成，两人因对神经网络潜力的共同探讨而结下深厚友谊。随着 2022 年 ChatGPT 等模型的出现，他们看到了 AI 领域的“终局”，并决定再次联手，创立了 Poolside。他们坚信，将强化学习与大型语言模型（LLMs）相结合是构建更强大智能的关键，尽管这一观点在公司早期曾被视为“逆势而行”。如今，他们认为 AI 正进入 AGI（通用人工智能）的“青春期”，这是一个充满挑战但也极具潜力的阶段，无数公司和应用正在涌现，致力于将原始智能转化为有价值的经济成果。Poolside 希望能在此过程中扮演一个“渺小而谦逊”的角色，并持续推动 AI 能力的边界。
Original English
Sort of. I mean, I think of him that way. Here, here's a fun story. Here's how I met ISO. I like to tell this story because um ISO is a fun fun dude. I met ISO because started with a failed acquisition at GitHub. So back when I joined GitHub in 2017 as a CTO, I wanted to take GitHub from a kind of collaborative collaborative code host with open source bent and turn it into an endto-end software development platform infused by intelligence. And so you know the the products that we launched from 27 on or 17 on GitHub actions, packages, alerts, notifications, eventually code spaces, um and then co-pilot was the last thing that the office of the CTO did before I left with Nat Friedman, Uga De Moore, and a couple of other folks inside there. But ISO in 2017 when I joined uh he had working code completion before the transform architecture had landed fully. He had on LSTMs and so I quickly tried to acquire his company and he just he just said no. So he just said no to me. Uh but we had that was a long drawn out process talking about what we thought neural networks were going to mean for the world. And so during that process, which was a lengthy one, we became really good friends and we'd stayed in close contact over the years. And then 22 rolled around, obviously Chat GPT comes out, Anthropics out, and we kind of saw the endgame at play and we said, "Do we jump back in or not?" And of course, yes, we jump back in. But I like to tell that story about how he just kept saying no to me and I just kept asking him questions and eventually he said, "Yes, we should found a company." Cuz by the way, when I asked him if we should do this, he said, "Oh, god damn no." That were his exact words. He's like, "No, we should just learn how to paint and sail." But here we are. So, yeah, it's it's been a great journey together. Jason, I I think the reason we ended up doing this is because of our our opinionated view on what it was going to take to build more capable intelligence. And in the first 18 months of this company, you know, obsessing and focusing on reinforcement learning combined with LLMs felt like one of the most contrarian opinions in the world, but I think today it's absolutely not. And it's super exciting to see the the progress that's continuing to make like we're in the coming years we're going to see the world that started in completions and went to chat and is now at a gentic increasingly approach more autonomous and we're all of it is stemming effectively from the combination of bringing highly capable models that are constantly evolving together with real world problems and and I think what we're starting to see now is we're entering these kind of awkward teenage years ahead of AGI where everybody in this room is building out incredible companies and applications is bridging this gap of what it really takes to make intelligence that in its raw form actually be valuable and we uh we want to be a small humble part of that. We've got a lot of work still ahead of us. Uh the team is growing. Uh but hopefully what you've seen today uh is what our our customers and enterprises have been having access to and seeing for a while is that we're you know hard at work at uh at really pushing those capabilities. We also want to make sure we make them available to build together with others.📌 文中提及的人物和组织
公司/组织: Poolside
产品/模型: Malibu agent