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I would not call it the “AI winter”. If you look at what people have called AI over time, the definition and the approaches have evolved (sometimes drastically)

I would not call it the “AI winter”. If you look at what people have called AI over time, the definition and the approaches have evolved (sometimes drastically) over time. Instead of being stuck on the fact that deep learning and the current methods seem to have hit a limit I think I am actually excited about the fact that this opens the door for experimenting other approaches that may or may not build on top of what we call AI today.

felippee 8y ago
Yeah, the problem is deep learning sucked a bunch of money - essentially took a loan against the future in the form of VC investments. And if that loan does not get payed, for the next few years you may not afford to explore all that other stuff.
- mirceal 8y ago
  Technically, VCs are not loaning you money. They’re more likely betting on you. It’s true that maybe they’ll be more reluctant to place big bets, but as with everything in life the VC optimism is cyclical.
  - felippee 8y ago
    Sure it is not technically a loan. But it carries the same sentiment change when it blows up. People get extremely cautious, to the point of skipping some really good ideas. And not just those VC's that made the bets but everyone else too. Fear spreads just as effectively as hype.
slowmovintarget 8y ago
Perhaps it'd be more correct to call it a "Strong AI Winter". We're no closer to "aware" machines. We've simply gotten very good at automating tasks that were once difficult to automate.
- mirceal 8y ago
  A friend that’s more optimistic about Strong AI once said that the ML that goes on today will probably serve the purpose of driving the peripheral sense organs of a future AI. Although it stretches a bit what’s possible today I could see that. I would call this a win if this ends up happening although I still belive we’re hundreds of years away from Strong AI.
  - randcraw 8y ago
    I'm inclined to agree with your friend. This ability of DL to convert streams of raw noisy data into labeled objects seems like exactly what's needed to solve an intelligent agent's perceptual grounding problem, where an agent that's new to the world must bootstrap its perception systems, converting raw sensory input into meaningful objects with physical dynamics. Only then can the agent reason about objects and better understand them by physical interaction and exploration. This is one of the areas where symbolic AI failed hardest, but DL does best. With some engineering, it's easy to imagine how active learning could use DL to ground robot senses - much like an infant human explores the world for the first year of life, adding new labels and understanding their dynamics as it goes. I suspect the potential for DL's many uses will continue to grow and surprise us for at least another decade. If we've learned anything from the past decade of DL, it's that probabilistic AI is surprisingly capable.
- checker659 8y ago
  There never was a Strong AI Summer to begin with.

felippee 8y ago

Yeah, the problem is deep learning sucked a bunch of money - essentially took a loan against the future in the form of VC investments. And if that loan does not get payed, for the next few years you may not afford to explore all that other stuff.

mirceal 8y ago
Technically, VCs are not loaning you money. They’re more likely betting on you. It’s true that maybe they’ll be more reluctant to place big bets, but as with everything in life the VC optimism is cyclical.
- felippee 8y ago
  Sure it is not technically a loan. But it carries the same sentiment change when it blows up. People get extremely cautious, to the point of skipping some really good ideas. And not just those VC's that made the bets but everyone else too. Fear spreads just as effectively as hype.

slowmovintarget 8y ago

Perhaps it'd be more correct to call it a "Strong AI Winter". We're no closer to "aware" machines. We've simply gotten very good at automating tasks that were once difficult to automate.

mirceal 8y ago
A friend that’s more optimistic about Strong AI once said that the ML that goes on today will probably serve the purpose of driving the peripheral sense organs of a future AI. Although it stretches a bit what’s possible today I could see that. I would call this a win if this ends up happening although I still belive we’re hundreds of years away from Strong AI.
- randcraw 8y ago
  I'm inclined to agree with your friend. This ability of DL to convert streams of raw noisy data into labeled objects seems like exactly what's needed to solve an intelligent agent's perceptual grounding problem, where an agent that's new to the world must bootstrap its perception systems, converting raw sensory input into meaningful objects with physical dynamics. Only then can the agent reason about objects and better understand them by physical interaction and exploration. This is one of the areas where symbolic AI failed hardest, but DL does best. With some engineering, it's easy to imagine how active learning could use DL to ground robot senses - much like an infant human explores the world for the first year of life, adding new labels and understanding their dynamics as it goes. I suspect the potential for DL's many uses will continue to grow and surprise us for at least another decade. If we've learned anything from the past decade of DL, it's that probabilistic AI is surprisingly capable.
checker659 8y ago
There never was a Strong AI Summer to begin with.