[TaylorAlexander]

A 15 year old can reason about how to move their body through a complex obstacle course. They could reason about the nonverbal social cues in a complex interpersonal situation between multiple people, estimate the mood of each person even if there are very few words being exchanged, and determine how different possible actions would affect the situation. They could learn with brief instruction how to control their muscles to climb up a rope. They could learn how to learn so that they become better at a task of their choosing. They can receive new information that permanently changes their understanding of the world. They can learn new tasks for which no massive data set of training data exists. They can perform hierarchical reasoning, like “if I want to fly from San Francisco to New York I first need to buy a plane ticket, then pack my bags, tell my family where I will be going, make sure my phone is charged, walk to the train station, etc etc.”

Also if you ask them a question they can provide you one answer with very little thinking, and then if that’s not good enough they can devote more time to thinking about the answer before they answer again. They can devote arbitrary levels of thinking to any problem depending on what is needed. They can continuously take in new data and continually update their world view throughout their entire existence based on this new information.

There’s actually a huge list of things current autoregressive approaches to AI cannot do, but they can be hard to describe and people don’t like to talk about them so many people actually don’t understand how limited the current systems are.

Here’s a great video where Yann Lecun talks about the limits of autoregressive approaches to AI with many examples:

https://youtu.be/1lHFUR-yD6I

[lostmsu]

Also: https://sl.bing.net/ep8K7FWVAHY

The quality of your argument is very low. You didn't even bother to check yourself.

[TaylorAlexander]

That’s fair. In the interview LeCun uses the example of flying from San Francisco to New York and he asserts that these systems are not good at hierarchical reasoning. I’m no expert in this field so I take him at his word but maybe it warrants further explanation.

He also says that such a system wouldn’t be familiar with how to actually move through the world because we don’t have good datasets for how to do so. The rest of what I said still stands. These systems aren’t good at things for which we don’t have massive datasets, and they’re not able to devote different amounts of thinking time to different problems.

[lostmsu]

What any of what you said has to do with abstract reasoning?

[TaylorAlexander]

What isn’t abstract about looking at an obstacle course and then imagining how you will move your body? Or looking at someone’s face and imagining how they feel. Isn’t that abstract?