The eminent professor of complexity Melanie Mitchell rightly points out that present-day AI systems have many limitations: they can’t transfer knowledge from one domain to another, provide quality explanations of their decision-making process, and so on.

For real intelligence you also need reasoning, language, and analogy, none of which is nearly so well handled by current technology.

As we successfully apply simpler, narrow versions of intelligence that benefit from faster computers and lots of data, we are not making incremental progress, but rather picking low-hanging fruit. The jump to general “common sense” is completely different, and there’s no known path from the one to the other.

I don't see it that way: Progress has indeed been fast lately. In a few years I will not be writing a snarky remark about GPT-N not being used for much because by then it will be obvious that there are at least a handful of legitimately useful applications for LLMs in broad use. At the same time, in a few years I do expect some people tha