The internet was a hype cycle, which ended with the dot com bubble burst. But some of the companies that came out of the bubble came out strong. AI has had multiple hype cycles, like every washing machine with "fuzzy logic" in the 90s, they usually end, but they do usually leave us with more than we had. This AI hype cycle is ending now, and we have seen a lot of progress on image detection, video editing, etc. but the highest targets haven't been reached.
It's kind of the explore-exploit dichotomy. You have some new technology (internet), in the first few years you have exploration and all the low hanging fruit are implemented, then everybody just starts iterating on similar ideas, which lead to less and less gain. The Uber/AirBnb/Amazon for X pitches. If you hear those you're in the late phase of the hype cycle. Because Y for X just means it's not a really new idea and plenty of people have thought of those.
Similarly you have some new technology like fuzzy logic, then some people thought of some good applications. But because the hype train was running it was put everywhere where it didn't make sense.
Or deep learning which was the first to have useful image processing. Now most research is tuning some parameters, adding compute, and hoping for better results.
But in the end we'll be left with some technological advances, and maybe in ten or twenty years somebody has a new idea which beats deep learning in learning efficiency.
It's kind of the explore-exploit dichotomy. You have some new technology (internet), in the first few years you have exploration and all the low hanging fruit are implemented, then everybody just starts iterating on similar ideas, which lead to less and less gain. The Uber/AirBnb/Amazon for X pitches. If you hear those you're in the late phase of the hype cycle. Because Y for X just means it's not a really new idea and plenty of people have thought of those.
Similarly you have some new technology like fuzzy logic, then some people thought of some good applications. But because the hype train was running it was put everywhere where it didn't make sense.
Or deep learning which was the first to have useful image processing. Now most research is tuning some parameters, adding compute, and hoping for better results.
But in the end we'll be left with some technological advances, and maybe in ten or twenty years somebody has a new idea which beats deep learning in learning efficiency.