Yup, we've had several AI winters. Now we have an AI Spring of Hype. Then we will have a Summer of Hope. Then a Fall of Failure. Then another, long AI Winter.
This type of unbridled pessimism baffles me. If you think what had happened over the past, say, 24 months is "AI Winter", I can't imagine what your bar for AI Summer is.
The progress in AI didn't stop during the past AI winters, it just slowed as funding dried up when people realized the AI at the time couldn't possibly live up to the hype.
In fact AI was essentially paused for years during the AI Winter.
That's completely false. AI winter wasn't about AI research being "essentially paused" but about AI startups becoming essentially non-fundable. It was backlash to the intense hype that surrounded the category.
The AI summer/winter cycle feels to me like something similar to a search algorithm, we have a phase of exploration, which seem to have slower, if any, progress and no one is very sure what's the next big thing so they perhaps start trying many things (the winter "skepticism") and eventually someone finds some breakthrough and gets everyone to an exploitation phase in which everyone knows where to invest and comparatively small effort is required to create progress (the summer "hype"). And eventually all low-hanging fruits are over and the search seems to converge to a local maximum and again larger exploration is required.
So maybe the winter is just as important as the summer. Each winter lead to a summer with different focus points (specialist systems and logic followed by neural networks, bayesian models and SVMs and finally deep learning). And after each cycle we have more and more tools, each more useful than the last. And also maybe the key to avoid this strict cycle would be to encourage more exploration during the exploitation phase, giving full support to both incremental ideals that improve on the state of the art and (potentially) revolutionary ideas that give poor immediate results but create new venues to investigate.
Of course that's a simplification and there are many aspects to it, including data availability, hardware and tooling that can easily prevent brilliant ideas that were had too soon.
Agree these detractors seem to be missing the big picture. An AI winter will never happen again because AI is so incredibly useful in so many areas now.
And yes it still fails in some, we aren’t at GAI yet, but we also likely aren’t far off
The AI winter was caused to a large extent by the hardware of the day not being powerful enough to do much that was useful. That seems less likely to be a problem this time around.
Aí winters happened because of the hype and that people ultimately realize AGI (not even talking about the Singularity) is not as easily achievable as hyped. So interest dies.
Yeah but the AI winter was mostly a period of low funding for AI due to disappointment at the research in the 70s and 80 not producing useful products. No one then was expecting human level intelligence but they were hoping to get some return on investment.
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