Inside the robotics laboratory of the Toyota Research Institute (TRI) in Cambridge, Massachusetts, a group of robots are busy cooking. There is nothing special about that; robotic chefs have been around for a while. But these robots are more proficient than most, flipping pancakes, slicing vegetables and making pizzas with ease. The difference is that instead of being laboriously programmed to carry out their tasks, the Cambridge robots have been taught only a basic set of skills. Using the wonders of artificial intelligence (AI), they quickly improved upon those skills to become far more dexterous.
在位于马萨诸塞州剑桥市的丰田研究所（TRI）机器人实验室里，一群机器人正忙碌地进行烹饪。这本身并没有什么特别之处；机器人厨师已经存在一段时间了。但这些机器人比大多数更加娴熟，它们轻松地翻煎饼、切蔬菜和制作比萨。与众不同的是，这些剑桥的机器人并不是通过繁琐的编程来执行任务的，而是仅被教授了一套基本技能。借助人工智能（AI）的神奇力量，它们迅速提升了这些技能，变得更加灵巧。
Despite their extraordinary culinary capabilities, these robots are not destined for a career in catering. “If you give a robot the confidence to work in a kitchen, it will also have the confidence to work in a factory or a person’s home,” says Gill Pratt, Toyota’s chief scientist. Cooking involves lots of complex tasks, such as picking up and placing items, pouring liquids and mixing ingredients. All this makes a kitchen an ideal training ground for experimenting with a new method of using generative AI to train robots known as “diffusion policy”.
尽管这些机器人拥有非凡的烹饪能力，但它们并不会从事餐饮行业。丰田首席科学家吉尔·普拉特（Gill Pratt）表示：“如果你让一个机器人具备在厨房工作的信心，它也会有在工厂或个人家庭中工作的信心。” 烹饪涉及许多复杂的任务，比如拾取和放置物品、倾倒液体和混合食材。所有这一切使得厨房成为实验一种新的使用生成式AI训练机器人的方法——即“扩散策略”（diffusion policy）——的理想场地。

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