行业73°

Gary Marcus对AI局限性的观点获支持

Gary Marcus was indeed right.

精选理由

Chamath直言AI在长周期和复杂问题上仍不实用,预言AI将经历幻灭期,需要新架构解决。

AI 摘要

Rohan Paul引用Chamath在斯坦福AI俱乐部的观点,指出长周期任务仍不成熟。Chamath强调复杂问题处理能力不足,可能导致AI经历炒作周期后的幻灭期。他认为需要符号空间引导嵌入空间来解决AI在复杂环境中的工作问题。

原文 · Gary Marcus

Gary Marcus was indeed right.

Gary Marcus was indeed right. Rohan Paul @rohanpaul_ai "Long-horizon tasks are still a joke. They do not work, and I do not care what anybody says. Do not show me a stupid evaluation. Do not tell me about some dumb script you ran for 48 hours. Long-horizon tasks are not handled well. They simply do not work." - Chamath at Stanford AI Club "2nd, complex problems also do not work. They are neither addressed nor handled well. Why is this important? If AI develops like any other technology, we are going to experience an initial rise—the hype cycle. Then, we will see a natural contraction because, somehow and somewhere, something is going to fail. We are all going to see this, and then we will enter what is called the “trough of disillusionment.” I think the business and MBA folks will confirm whether that is true. Afterward, you typically see the slow and gradual adoption of the real, final solution. This happened with the internet, and it has happened in many other cases. The problem is that we are spending hundreds of billions, potentially trillions, of dollars trying to figure out how to cross this chasm. So, what do we do? If we do not figure this out, people will reach the trough of disillusionment and say that AI was a joke. I think we need to be able to bring AI into highly complicated environments and make it work. What is my solution? At a very basic level, you need a symbolic space that guides the embedded space." ---- From "techniahqrobot" YouTube channel, (full video link in comment) Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 4 🔄 3 ❤️ 11 👀 2697 📊 4 ⚡