[zep15]

Reasoning means things like this: suppose you are holding a ball and want to make it drop. A rule of inference tells you that if you release it, it will drop. You can then reason out that you should release it.

Sure, the rule of inference may have ultimately been derived from experience, by a process which in some sense involved statistical correlation. But you have to distinguish that ultimate basis for the inference rule from _the process of logical inference itself_. It's the latter that is generally called reasoning.

Reasoning in the above sense is essential to intelligence, even at the toddler level, and the DeepMind work doesn't address reasoning. I think that may be the point the parent was getting at.

[wutbrodo]

Right, inference is essential to any attempt to build an intelligence and DeepMind in particular doesn't do inference (AFAIK). I just wanted to clarify what the parent commenter was saying; I work in the field, and in conversations around AI, I very often hear "reasoning" used as an ill-defined, unattainable (for machines) _je ne sais quoi_ that's used to prognosticate about the potential for AI in general. Being specific about what one means by "reasoning" (in this context, inference) is useful for removing those kinds of useless, unmoored-from-logic[1] perspectives from a conversation.

[1] To be clear, I'm not dismissing a viewpoint that I think is wrong as "unmoored from logic", I'm specifically talking about the very common situation where people confidently assert this with no attempt (and no ability) to back it up in any way other than confidence that intelligence is simply natural and non-biological entities can never get arbitrarily close.