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Teaching Robots How to Do Everything
2025/6/5
What's Your Problem?
C
Chelsea Finn
J
Jacob Goldstein
Jacob Goldstein: 我认为目前市面上缺乏能够执行如叠衣服等日常任务的机器人。然而，我设想在不久的将来，我们将能够开发出通过人工智能学习执行各种任务的机器人。
Chelsea Finn: 我认为开发能够执行通用任务的机器人面临诸多挑战，尤其是在数据收集方面。尽管如此，我坚信通过遥控操作等方式收集数据，并不断改进模型，我们能够逐步实现机器人的通用技能。我强调，虽然自动驾驶领域的数据收集经验值得借鉴，但机器人领域仍需克服其独有的数据稀缺性问题。我同时也提到，通过在不同环境和场景下训练机器人，可以提高其泛化能力，使其能够在新的环境中执行任务。此外，我强调提高机器人的可靠性和速度是当前的主要目标，并认为人机协作是未来发展的重要方向。
Deep Dive
Despite AI's advancements, robots struggle with simple physical tasks. This is because motor skills are incredibly complex, and there's a lack of readily available training data compared to the abundance of data for language models and computer vision.
- AI excels in many areas but lags in physical tasks like folding clothes.
- Motor skills, seemingly simple to humans, are extremely complex for AI.
- Lack of training data hinders robot learning compared to language models and computer vision.
Shownotes Transcript