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https://en.wikipedia.org/wiki/Moravec%27s_paradox https://en.wikipedia.org/wiki/Moravec%27s_paradox Moravec's paradox is the observation in artificial intellig

by graphe 3y ago

https://en.wikipedia.org/wiki/Moravec%27s_paradox https://en.wikipedia.org/wiki/Moravec%27s_paradox Moravec's paradox is the observation in artificial intelligence and robotics that, contrary to traditional assumptions, reasoning requires very little computation, but sensorimotor and perception skills require enormous computational resources. The principle was articulated by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s. Moravec wrote in 1988, "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".

anon291 3y ago
> Moravec wrote in 1988, "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". The resolution to the paradox is so simple I must be missing something. The amount of data in datasets for 'mobility' is basically zero. You would have to manually construct such a dataset. Whereas, humans have for thousands of years been trained to symbolically encode their reasoning processes in a way that has been incredibly accessible to computers (prose). If I understand correctly, the scaling laws for mobility are the same for language and reasoning. We need more data.
- graphe 3y ago
  The training data for chess is very easy in comparison to walking. If you had the same amounts of data for both and the ability to get it, understand it and use it you wouldn't have a problem. Basically it's hard to make a machine use and understand how to use it's physical form and in 1988 it was even harder. For chess it was easy. It's easy to get, understand and use chess data.

by graphe 3y ago

anon291 3y ago

> Moravec wrote in 1988, "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". The resolution to the paradox is so simple I must be missing something. The amount of data in datasets for 'mobility' is basically zero. You would have to manually construct such a dataset. Whereas, humans have for thousands of years been trained to symbolically encode their reasoning processes in a way that has been incredibly accessible to computers (prose). If I understand correctly, the scaling laws for mobility are the same for language and reasoning. We need more data.

graphe 3y ago
The training data for chess is very easy in comparison to walking. If you had the same amounts of data for both and the ability to get it, understand it and use it you wouldn't have a problem. Basically it's hard to make a machine use and understand how to use it's physical form and in 1988 it was even harder. For chess it was easy. It's easy to get, understand and use chess data.