Sundar Pichai: Path To Recursive Self-Improvement, Compute Allocation Dilemma, Future AI Interfaces

章节 1：谷歌如何坚持前沿人工智能研究

📝 本节摘要：

皮查伊强调，谷歌始终致力于保持人工智能前沿地位，并介绍 Argon 的能力、谨慎测试和上线过程，以及发布初期的使用情况。他承认模型仍有改进空间，尤其在编程等方面，并表示团队会持续迭代。

[原文] [Sundar Pichai]: We are at the early stages of the most consequential technology ever. This is not like fiber. It's not dark. We are using it. For AI researchers, it's like the bigger the computer, the better the AI. You give the researchers the biggest possible computer, even if it is to the detriment of today's profits, like the cloud business. So the compute we have today is a function of decisions I made in 2024. Today, obviously, when you sit and look at anything, everyone is short—not just us, other companies—and everyone wishes they had 2x of what they planned for. Where's Google's Muse or its product? Users both in consumer and enterprise will have access to some multi-agent framework, with things working all the time and doing things. And so, you know, it feels like a moment of infinite possibilities. Alphabet CEO Sundar Pichai joins us to

[译文] [Sundar Pichai]: 我们正处于人类历史上影响最深远的技术发展的早期阶段。这不像光纤，它并不遥远，我们正在使用它。对人工智能研究人员来说，计算机越大，人工智能就越好。你会给研究人员尽可能大的计算机，即使这会损害当下的利润，比如云业务的利润。我们今天拥有的算力，取决于我在 2024 年做出的决策。现在显然，无论看什么，大家都觉得算力不够，不只是我们，其他公司也一样；每个人都希望自己准备的算力能翻一倍。谷歌的 Muse 或者它的产品呢？消费者和企业用户都会用上某种多智能体框架，让智能体一直运行、持续办事。所以，这感觉像是一个充满无限可能的时刻。Alphabet 首席执行官桑达尔·皮查伊今天来到节目，和我们聊聊……

[原文] [Alex Kantrowitz]: talk about Google's plan to compete on the frontier of AI, the balance between cutting-edge AI research and the company's cloud business, and what the future of the interface looks like. Sundar is here with us in the studio in Mountain View today. Sundar, great to see you. Welcome to the show.

[译文] [Alex Kantrowitz]: ……谷歌如何在人工智能前沿领域竞争，如何平衡尖端人工智能研究与公司的云业务，以及未来的交互界面会是什么样子。今天桑达尔来到山景城的演播室和我们一起录节目。桑达尔，很高兴见到你，欢迎来到节目。

[原文] [Sundar Pichai]: Thanks, Alex. Great to be here.

[译文] [Sundar Pichai]: 谢谢你，亚历克斯。很高兴来到这里。

[原文] [Alex Kantrowitz]: So Google is back on the frontier with Gemini 4 Argon. In plain speak, that means it is a world-leading model. It's breaking benchmarks. It beats OpenAI's and Anthropic's public models on a variety of benchmarks, including coding, math, science, and knowledge work. Now, the conventional wisdom had been that Google had basically given up on the frontier, that it was going to make these fast models that were good enough and use them in its products, and that it wasn't pursuing frontier AI anymore. But that was wrong.

[译文] [Alex Kantrowitz]: 谷歌凭借 Gemini 4 Argon 重回前沿。简单来说，它是世界领先的模型，打破了多项基准纪录，在编程、数学、科学和知识工作等多项基准测试中超过了 OpenAI 和 Anthropic 的公开模型。过去人们普遍认为，谷歌基本上已经放弃了前沿研究，准备开发够用又快速的模型，把它们用于产品，不再追求人工智能前沿。但事实并非如此。

[原文] [Sundar Pichai]: I mean, very wrong. Look, I think we are so committed to being at the frontier. I think it's in our DNA. We wouldn't do it any other way. We've been thinking about the AI frontier for well over a decade now. The frontier is very dynamic. It's very competitive. It's very exciting. I couldn't be more pleased with how Argon has come together. We took our time with it. We made sure we tested it safely and deployed it carefully.

[译文] [Sundar Pichai]: 可以说，错得很离谱。我们非常坚定地要站在前沿。我觉得这已经融入了我们的基因，我们不会选择别的做法。我们思考人工智能前沿已经十多年了。这个领域变化很快、竞争激烈，也令人兴奋。Argon 最终的成果让我非常满意。我们花了时间打磨，确保经过安全测试后再谨慎部署。

[原文] [Sundar Pichai]: we took a bit longer than our other models given given its capabilities. But I think across the board be it for agentic work, knowledge work, coding, creative tasks, I think Argon is you know one one of the really good frontier models and you know in the first 72 hours since we launched it's you know almost up to 25 trillion tokens used which is about 3x what Gemini 3.0 had in the first 72 hours. So and we are capacity constrained as we are serving it. So excited but there are always areas you know both the frontier is just last it's very dynamic and you have to keep evolving the models and there are areas which we can see we need to improve as well. So we'll be at it at work on all of that as well.

[译文] [Sundar Pichai]: 考虑到它的能力，我们花的时间比开发其他模型稍长一些。但我认为，无论是智能体任务、知识工作、编程还是创意任务，Argon 都是非常优秀的前沿模型之一。上线后的头 72 小时里，它处理的 token 接近 25 万亿，大约是 Gemini 3.0 上线头 72 小时处理量的三倍。现在我们提供服务时受到算力容量限制。我很兴奋，但模型总有需要改进的地方。前沿不断向前发展、变化很快，所以模型也必须持续迭代。我们看得到仍需改进的领域，也会继续努力。

[原文] [Alex Kantrowitz]: Which areas? Okay. on any given model, you know, Argon will be across the board better at everything if you just look even two months back. But the space is so evolving. but even on coding for example, there are there are areas pockets where we we know we need to do better and you know there's clear feedback and so we'll we'll make it better. Let me at least make the argument for why standard models might be good enough for Google. Yeah. I'm going to channel what people say about this. Yeah.

[译文] [Alex Kantrowitz]: 具体是哪些方面？好。就任何一个模型而言，Argon 在各方面都比两个月前更强，但这个领域发展得太快了。比如编程方面，我们知道还有一些局部领域需要做得更好，也收到了明确的反馈，所以会继续改进。让我先替另一种观点说说理由：为什么对谷歌来说，标准模型可能已经够用了。我来转述一下大家对此的看法。