Furthermore, there has been insane progress over the last few years, which presumably would not have happened if everyone had despaired on reading Marcus' 'hitting a wall' article and dropped everything to work on GOFAI.
But let's widen the lens a little bit:
`In 2015, shortly after Hinton joined Google, The Guardian reported that the company was on the verge of “developing algorithms with the capacity for logic, natural conversation and even flirtation.” In November 2020, Hinton told MIT Technology Review that “deep learning is going to be able to do everything.” I seriously doubt it.`
Well, we've certainly got natural conversation and flirtation, along with some kind of logic - especially if you're OK with accepting python programs as a form of response. This is well beyond what was considered possible at the time. We're certainly not at 'everything' but *shrug*. Maybe in ten years.
`nowhere near the ordinary day-to-day intelligence of Rosey the Robot, a science-fiction housekeeper that could not only interpret a wide variety of human requests but safely act on them in real time.`
It exists, it just isn't anywhere near economical for household tasks... https://www.wired.com/story/google-robot-learned-to-take-ord... LLM's look poised to upend robotics.
Marcus then goes extensively into why everyone should be looking at symbol-manipulation systems. And that's fine... But would be much more convincing if he could actually produce something that works. At some point, one asks, if your idea is so good, why haven't you actually solved any problems?