Moravec's Paradox

A Moravec's Paradox is a paradox that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills require enormous computational resources.

• See: Artificial Intelligence, Robotics, Reasoning, Sensory Processing#Sensorimotor System, Hans Moravec, Rodney Brooks, Marvin Minsky, Steven Pinker.

---

---

References

2024-11-08

• https://x.com/karpathy/status/1855659091877937385
  • Moravec's paradox in LLM evals
  • I was reacting to this new benchmark of frontier math where LLMs only solve 2%. It was introduced because LLMs are increasingly crushing existing math benchmarks. The interesting issue is that even though by many accounts (/evals), LLMs are inching well into top expert territory (e.g., in math and coding, etc.), you wouldn't hire them over a person for the most menial jobs. They can solve complex closed problems if you serve them the problem description neatly on a platter in the prompt, but they struggle to coherently string together long, autonomous problem-solving sequences in a way that a human would find very easy.
  • This is Moravec's paradox in disguise, who observed 30+ years ago that what is easy/hard for humans can be non-intuitively very different to what is easy/hard for computers. E.g., humans are very impressed by computers playing chess, but chess is easy for computers as it is a closed, deterministic system with a discrete action space, full observability, etc. Vice versa, humans can tie a shoe or fold a shirt and don't think much of it at all, but this is an extremely complex sensorimotor task that challenges the state of the art in both hardware and software. It's like that Rubik's Cube release from OpenAI a while back where most people fixated on the solving itself (which is trivial) instead of the actually incredibly difficult task of just turning one face of the cube with a robot hand.
  • So I really like this FrontierMath benchmark and we should make more. But I also think it's an interesting challenge how we can create evals for all the "easy" stuff that is secretly hard. Very long context windows, coherence, autonomy, common sense, multimodal I/O that works, ... How do we build good menial job evals? The kinds of things you'd expect from any entry-level intern on your team.

2014

• (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/Moravec's_paradox Retrieved:2014-1-19.
  • Moravec's paradox is the discovery by artificial intelligence and robotics researchers that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills require enormous computational resources. The principle was articulated by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s. As Moravec writes, "it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility."Template:Sfn

    Linguist and cognitive scientist Steven Pinker considers this the most significant discovery uncovered by AI researchers. In his book The Language Instinct, he writes: }}

     Marvin Minsky emphasizes that the most difficult human skills to reverse engineer are those that are unconscious. “In general, we're least aware of what our minds do best," he writes, and adds "we're more aware of simple processes that don't work well than of complex ones that work flawlessly."Template:Sfn

1988

• (Moravec, 1988) ⇒ Hans Moravec. (1988). “Mind Children." Harvard University Press. ISBN:9780674576186
  • QUOTE: … unfortunately for humanlike robots, computers are at their worst trying to do the things most natural to humans, such as seeing, hearing, manipulating objects, learning languages, and commonsense reasoning. This dichotomy - machines doing well things human find hard, while doing poorly what is easy for us - is a giant clue to the problem of how to construct an intelligent machine ...

---