9 ms·

>> In the past, there were some ambitious projects aiming at this goal, though they all failed. So some people like to repeat. Yet, outside of the hand-picked

>> In the past, there were some ambitious projects aiming at this goal, though they all failed. So some people like to repeat. Yet, outside of the hand-picked examples in the article (the 5th generation computer project? Blast from the past!) there are a whole bunch of classic AI domains where real progress has been achieved in the last few decades. Here's a few: * Game-playing and adversarial search: from Deep Blue to AlphaGo and muZero, minimax-like search has continued to dominate. * Automated planning and schdeduling: e.g. used by NASA in automated navigation systems on its spaceships and Mars rovers (e.g. Perserverance) [1] * Automated theorem proving: probably the clearest, most comprehensible success of classical AI. Proof assitants are most popular today. * Boolean satisfiability solving (SAT): SAT solvers based on the Conflict Driver Clause Learning algorithm can now solve many instances of traditionally hard SAT problems [2]. * Program verification and model checking: model checking is a staple in the semiconductor industry [3] and in software engineering fields like security. Of course, none of all that is considered Artificial Intelligence anymore: because they work very well [4]. _____________ [1] https://www.nasa.gov/centers/ames/research/technology-onepagers/automated_planning_scheduling.html https://www.nasa.gov/centers/ames/research/technology-onepag... [2] https://en.wikipedia.org/wiki/Conflict-driven_clause_learning https://en.wikipedia.org/wiki/Conflict-driven_clause_learnin... [3] https://m-cacm.acm.org/magazines/2021/7/253448-program-verification/fulltext https://m-cacm.acm.org/magazines/2021/7/253448-program-verif... [4] https://en.wikipedia.org/wiki/AI_effect https://en.wikipedia.org/wiki/AI_effect

mdp2021 3y ago
> considered Artificial Intelligence anymore That is just the confusion between AI and AGI - which may seem to be peaking for some reason (in the past few days it seemed like a zombie apocalypse). The so-called "AI effect" is said by some to originate from some "Ah but this is not intelligent" - but there where we wanted to solve a problem of replacing intelligent action, not of implementing it. Be contented with the rough discriminator "I would have had to pay an intelligent professional otherwise". To speak about «powerful AI, with broad capabilities at the human level and beyond» Ben Goertzel adopted and popularized 'AGI': https://goertzel.org/who-coined-the-term-agi/ https://goertzel.org/who-coined-the-term-agi/ Edit, update: this confusion is like having robotics and some people rising a "Ah but this is not Artificial General Ability".
- welshwelsh 3y ago
  What counts as "human level"? I would contend that a 5-year-old has general intelligence, and therefore an AI system with the language and reasoning abilities of a 5-year-old has artificial general intelligence. But the discriminator of having to "pay an intelligent professional otherwise" sets the bar very high. That implies AGI must be an expert in every subject, surpassing the average human. I'd prefer we use a different term for that, like "artificial superintelligence."
  - pedrosorio 3y ago
    > But the discriminator of having to "pay an intelligent professional otherwise" sets the bar very high. That implies AGI I believe they were using that discriminator to classify AI, not AGI.
    - mdp2021 3y ago
      > pay an intelligent professional otherwise [...] discriminator to classify AI Exactly. "Ah but your system to organize the warehouse is not intelligent!" "No it isn't, but it does it intelligently - and without it you would have to pay an intelligent professional to get it done optimally". AI: "automation of intelligence". (Not "implementation of intelligence itself" - that is AGI.)
  - worrycue 3y ago
    > What counts as "human level"? IMHO if it can do every single human job at a level of competency that's consider acceptable if a human did it, I would consider that "human level" - frankly, it's implied that when people say "human level", they mean the average human. Seriously though, arguing over semantics is just a waste of time. It's what it can do and the consequences of what it can that really matter. > That implies AGI must be an expert in every subject, surpassing the average human. Doesn't have to be the same AI "instance". We can have multiple copies of the AI with different specializations. That would still count - I mean it's how we humans do it.
- cubefox 3y ago
307th 3y ago
I think the sentence in the article is fair. They're right that projects aimed at AGI failed; everything you mention are used for narrow AIs that tackle particular tasks. Also, regarding search in gameplaying, I would argue the opposite: the trend is that breaking into bigger and more difficult domains has required abandoning search. Tree search is limited to small games like board games or Atari. In more open-ended games we see model-free (i.e. no search) approaches; e.g. AlphaStar and OpenAI Five, the AIs for Starcraft 2 and Dota 2, were both model free. So was VPT (https://openai.com/research/vpt https://openai.com/research/vpt) by OpenAI, which tackled Minecraft. Even in board games, DeepNash (https://www.deepmind.com/blog/mastering-stratego-the-classic-game-of-imperfect-information https://www.deepmind.com/blog/mastering-stratego-the-classic...), a 2022 project by DeepMind similar in scale to MuZero/AlphaGo, had to abandon tree search because of the size of the game and the challenges of applying tree search to hidden information domains.
- deleted 3y ago
  [deleted]
- YeGoblynQueenne 3y ago
  The sentence I quoted is from the part of the article discussing classical AI, not AGI. >> Tree search is limited to small games like board games or Atari. To be clear, those are board games like chess and go (and shoggi).
goatlover 3y ago
If Data from Star Trek (or Eva from Ex Machina) walked out of a lab, we’d have no problem accepting that AGI had been accomplished. Or if the scenario in the movie Her played out with the Samantha OS, we’d be forced to admit not only to AGI, but the evolution of ASI as well. However, there are no such examples in the real world, and after months of overhyping ChatGPT, we still don’t have anything like Data. So it’s not shifting the definition, it’s recognizing that accomplishing a single intelligent task isn’t general intelligence.
- famouswaffles 3y ago
  >If Data from Star Trek (or Eva from Ex Machina) walked out of a lab, we’d have no problem accepting that AGI had been accomplished Lol no. What testable definition of general intelligence does GPT-4 fail that a good chunk of humans also wouldn't ? If you can answer this then you have a point, otherwise I really beg to differ.
  - VirusNewbie 3y ago
    Tell them something important to remember, ask a week later.
    - jsiva 3y ago
      Needs a few more constraints, otherwise someone could just maintain a session for a week and this task would be trivial
      - VirusNewbie 3y ago
        Sure, point is, we could easily design A test that 5th graders could pass that GPT4 as it is today would fail.
        famouswaffles 3y ago
        I said design an intelligence test that a good chunck of humans wouldn't also fail. I'm sorry to tell you this but there are many humans that would fail your test. Even otherwise healthy humans could fail your test nevermind Anterograde Amnesia, Dementia etc patients
cubefox 3y ago
There seems to be only one broad paradigm which achieved basically all the AI big impact we see today: Deep learning. That is, machine learning with multi-layer neural networks with backpropagation and ReLU activation functions. Everything else seems to be mostly irrelevant or very small scale.
- feoren 3y ago
  > ReLU activation functions ReLU is not nearly at the same level of importance as backpropagation and the high-level theory of neural networks. Plenty of other activation functions can be, and are, used. ReLU is a fine default for most layers but isn't even always what you want (e.g. at the output), nor is it clear that ReLU is even the best choice for all hidden layers and all uses.
- mdp2021 3y ago
  > seems to be mostly irrelevant From a perspective that could be too local in time. But: > ReLU activation functions Why did you pick ReLU, of all? The sigmoid makes sense because of the aesthetic (with reference to the derivative), but ReLU in that perspective is an information cutoff. And in the perspective of the goal, I am not aware of a theory that defends it as "the activation function that makes sense" (beyond effectiveness). Are you saying that working applications overwhelmingly use ReLU? If so, which ones?
- YeGoblynQueenne 3y ago
  All the classical AI tasks I list abover are dominated by the classic approaches I listed and neural nets are completely useless in them.
  - sdenton4 3y ago
    The 'game playing' you lead with is clearly dominated by deep learning in this decade.
    - deleted 3y ago
      [deleted]

mdp2021 3y ago

> considered Artificial Intelligence anymore That is just the confusion between AI and AGI - which may seem to be peaking for some reason (in the past few days it seemed like a zombie apocalypse). The so-called "AI effect" is said by some to originate from some "Ah but this is not intelligent" - but there where we wanted to solve a problem of replacing intelligent action, not of implementing it. Be contented with the rough discriminator "I would have had to pay an intelligent professional otherwise". To speak about «powerful AI, with broad capabilities at the human level and beyond» Ben Goertzel adopted and popularized 'AGI': https://goertzel.org/who-coined-the-term-agi/ https://goertzel.org/who-coined-the-term-agi/ Edit, update: this confusion is like having robotics and some people rising a "Ah but this is not Artificial General Ability".

welshwelsh 3y ago
What counts as "human level"? I would contend that a 5-year-old has general intelligence, and therefore an AI system with the language and reasoning abilities of a 5-year-old has artificial general intelligence. But the discriminator of having to "pay an intelligent professional otherwise" sets the bar very high. That implies AGI must be an expert in every subject, surpassing the average human. I'd prefer we use a different term for that, like "artificial superintelligence."
- pedrosorio 3y ago
  > But the discriminator of having to "pay an intelligent professional otherwise" sets the bar very high. That implies AGI I believe they were using that discriminator to classify AI, not AGI.
  - mdp2021 3y ago
    > pay an intelligent professional otherwise [...] discriminator to classify AI Exactly. "Ah but your system to organize the warehouse is not intelligent!" "No it isn't, but it does it intelligently - and without it you would have to pay an intelligent professional to get it done optimally". AI: "automation of intelligence". (Not "implementation of intelligence itself" - that is AGI.)
- worrycue 3y ago
  > What counts as "human level"? IMHO if it can do every single human job at a level of competency that's consider acceptable if a human did it, I would consider that "human level" - frankly, it's implied that when people say "human level", they mean the average human. Seriously though, arguing over semantics is just a waste of time. It's what it can do and the consequences of what it can that really matter. > That implies AGI must be an expert in every subject, surpassing the average human. Doesn't have to be the same AI "instance". We can have multiple copies of the AI with different specializations. That would still count - I mean it's how we humans do it.
cubefox 3y ago

307th 3y ago

I think the sentence in the article is fair. They're right that projects aimed at AGI failed; everything you mention are used for narrow AIs that tackle particular tasks. Also, regarding search in gameplaying, I would argue the opposite: the trend is that breaking into bigger and more difficult domains has required abandoning search. Tree search is limited to small games like board games or Atari. In more open-ended games we see model-free (i.e. no search) approaches; e.g. AlphaStar and OpenAI Five, the AIs for Starcraft 2 and Dota 2, were both model free. So was VPT (https://openai.com/research/vpt https://openai.com/research/vpt) by OpenAI, which tackled Minecraft. Even in board games, DeepNash (https://www.deepmind.com/blog/mastering-stratego-the-classic-game-of-imperfect-information https://www.deepmind.com/blog/mastering-stratego-the-classic...), a 2022 project by DeepMind similar in scale to MuZero/AlphaGo, had to abandon tree search because of the size of the game and the challenges of applying tree search to hidden information domains.

deleted 3y ago
[deleted]
YeGoblynQueenne 3y ago
The sentence I quoted is from the part of the article discussing classical AI, not AGI. >> Tree search is limited to small games like board games or Atari. To be clear, those are board games like chess and go (and shoggi).

goatlover 3y ago

If Data from Star Trek (or Eva from Ex Machina) walked out of a lab, we’d have no problem accepting that AGI had been accomplished. Or if the scenario in the movie Her played out with the Samantha OS, we’d be forced to admit not only to AGI, but the evolution of ASI as well. However, there are no such examples in the real world, and after months of overhyping ChatGPT, we still don’t have anything like Data. So it’s not shifting the definition, it’s recognizing that accomplishing a single intelligent task isn’t general intelligence.

famouswaffles 3y ago
>If Data from Star Trek (or Eva from Ex Machina) walked out of a lab, we’d have no problem accepting that AGI had been accomplished Lol no. What testable definition of general intelligence does GPT-4 fail that a good chunk of humans also wouldn't ? If you can answer this then you have a point, otherwise I really beg to differ.
- VirusNewbie 3y ago
  Tell them something important to remember, ask a week later.
  - jsiva 3y ago
    Needs a few more constraints, otherwise someone could just maintain a session for a week and this task would be trivial
    - VirusNewbie 3y ago
      Sure, point is, we could easily design A test that 5th graders could pass that GPT4 as it is today would fail.
      - famouswaffles 3y ago
        I said design an intelligence test that a good chunck of humans wouldn't also fail. I'm sorry to tell you this but there are many humans that would fail your test. Even otherwise healthy humans could fail your test nevermind Anterograde Amnesia, Dementia etc patients

cubefox 3y ago

There seems to be only one broad paradigm which achieved basically all the AI big impact we see today: Deep learning. That is, machine learning with multi-layer neural networks with backpropagation and ReLU activation functions. Everything else seems to be mostly irrelevant or very small scale.

feoren 3y ago
> ReLU activation functions ReLU is not nearly at the same level of importance as backpropagation and the high-level theory of neural networks. Plenty of other activation functions can be, and are, used. ReLU is a fine default for most layers but isn't even always what you want (e.g. at the output), nor is it clear that ReLU is even the best choice for all hidden layers and all uses.
mdp2021 3y ago
> seems to be mostly irrelevant From a perspective that could be too local in time. But: > ReLU activation functions Why did you pick ReLU, of all? The sigmoid makes sense because of the aesthetic (with reference to the derivative), but ReLU in that perspective is an information cutoff. And in the perspective of the goal, I am not aware of a theory that defends it as "the activation function that makes sense" (beyond effectiveness). Are you saying that working applications overwhelmingly use ReLU? If so, which ones?
YeGoblynQueenne 3y ago
All the classical AI tasks I list abover are dominated by the classic approaches I listed and neural nets are completely useless in them.
- sdenton4 3y ago
  The 'game playing' you lead with is clearly dominated by deep learning in this decade.
  - deleted 3y ago
    [deleted]