| Here's a question to ChatGPT I just made up: >> A magical frog was counting unicorns. He saw 5 purple unicorns, 2 green unicorns, and 7 pink unicorns. However, he made a mistake and didn't see 2 unicorns: one purple and one green. Also, since he was a magical frog, he didn't see unicorns that were the same color as himself. How many unicorns did he count? It correctly answers 11 for me. To me this has demonstrated: * "Understanding": It understood that "didn't see" implies he didn't count. * "Knowledge": It knew enough about the world to know that frogs are often green. * "Reasoning": It was able to correctly reason about how many should be subtracted from the final result. * "Math: It successfully did some basic additions and subtractions arriving at the correct answer. Crucially, I made this up right here on the spot, and used a dice for some of the numbers. This question does not exist anywhere in the training corpus! I think this demonstrates an impressive level of intelligence, for what up until about a year ago I thought a computer would ever be capable of in my lifetime. Now in absolute terms of course current gen ChatGPT is clearly far less good at reasoning and understanding than most people (well, specifically it seems to me that it's knowledge and reasoning are super-humanly broad, but child-level deep). Can future improvements to this architecture improve the depth up to "AGI", whatever that means? I have no idea. It doesn't automatically seem impossible, but maybe what we see now is already near the limit? I guess only time will tell. |