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I agree with you. Our current results are impressive enough for me to believe we're not that far from AGI (of the kind that would satisfy the author here). This

I agree with you. Our current results are impressive enough for me to believe we're not that far from AGI (of the kind that would satisfy the author here). This article is already largely outdated because of advances in Reinforcement Learning and other Deep Learning applications that show very strong primordial features of what he claims as epitomes of human capability. For example, trained RL agents will recognize objects without being able to label them, having internal representations for position, object "type", functionality and relevance. You just have to train the agent with a problem that requires this kind of comprehension for efficient performance (kind of comprehension which isn't needed in simple image labeling). AlphaGo and even labeling are indeed milestones in superhuman performance, and I believe Terence Tao's view that AI is a moving target is relevant here. --- 1) Regarding the Fermi paradox, I haven't read too much technical or scientific work on it (it's highly speculative anyway), but I find Isaac Arthur's videos lay the basic ideas pretty well: https://www.youtube.com/watch?v=oIva_60l3ww&t=1016s https://www.youtube.com/watch?v=oIva_60l3ww&t=1016s It becomes pretty convincing that technological intelligent life is an incredible coincidence. There might not be any huge "filters", as they are called (stages which reduce the probability of observing TIL), such as a superintelligence extinction event, but an enormous sequence of minor filters, ranging from low probability of a planet with adequate conditions, to low probability of actual technological development, to low probability of occurrence in our light cone (we can only see fairly young distant galaxies), and limitations to the visibility and spreading velocity of such civilizations. There is a wide range of parameters such that this does not contradict the generalized Mediocrity principle, such that there is probably more than one TIL in the universe, but they're few and far from each other in space and time. 2) I don't follow. This objection is only valid for discovering new laws of physics -- technological development can happen even with fixed knowledge of basic physical laws. At this stage it's not clear that even continued refinement of physical models. For example, the discovery of quarks certainly helped understanding nature, but it hasn't led to any direct technological applications due to quark confinement, and the fact that the particles are just too small. Neutrinos are another conceptually important discovery that doesn't really have applications due to low interactivity with matter.

philipkglass 9y ago
This objection is only valid for discovering new laws of physics -- technological development can happen even with fixed knowledge of basic physical laws. No, experimentation is also important for translating fundamental scientific knowledge into working technologies. Consider the problem of building a fusion reactor that generates net electricity. You don't need new laws of physics, but you can't make progress with simulations alone. You have to experiment to find out if devices behave in reality the way they do in your model.
- darkmighty 9y ago
  Well as simulations improve that tends to be less of a problem. Engineering by now is highly reliant on simulations, building actual prototypes is only done as a last validating step as you mentioned (specially for something as expensive and complicated as a fusion reactor). So validation devices are a O(1) step in the innovation chain, I don't see a scaling issue here. You can also simply make arbitrarily many experimentation/testing devices. I think a greater issue is the general misconception of intelligence as something of a magical attribute, and even more so "superintelligence", and even more so "recursive-self-improving superintelligence" (RSIS for short?). There are not only various limits to hardware, some of which discussed in the article (size of atoms, capacity of communication between parts), but also there are limits to software. For example, while it seems that an RSIS could really solve any problem it wanted, Turing's almost century-old Halting Problem solution already proved that no such computer exists. There's no algorithm that takes an arbitrary conjecture, e.g. the Riemann hypothesis, and outputs either {yes,no,malformed_problem}. In fact the general expectation of what AGIs can do (think creatively, solve arbitrary problems, replace mathematicians, replace programmers) are things that we ourselves can't really do. We solve problems using a small set of heuristics and lots of trial and error, with no success guarantee. Another fact is that there are many asymptotically optimal algorithms that are already know, and the trivial fact that almost all tasks performed by this super-intelligence (many of which are ordinary tasks we already do, analogous to maybe sorting, database queries, and search engines) will just improve constants on near-optimal algorithms. A god-like creature those AIs will be not.
  - 9y ago

philipkglass 9y ago

This objection is only valid for discovering new laws of physics -- technological development can happen even with fixed knowledge of basic physical laws. No, experimentation is also important for translating fundamental scientific knowledge into working technologies. Consider the problem of building a fusion reactor that generates net electricity. You don't need new laws of physics, but you can't make progress with simulations alone. You have to experiment to find out if devices behave in reality the way they do in your model.

darkmighty 9y ago
Well as simulations improve that tends to be less of a problem. Engineering by now is highly reliant on simulations, building actual prototypes is only done as a last validating step as you mentioned (specially for something as expensive and complicated as a fusion reactor). So validation devices are a O(1) step in the innovation chain, I don't see a scaling issue here. You can also simply make arbitrarily many experimentation/testing devices. I think a greater issue is the general misconception of intelligence as something of a magical attribute, and even more so "superintelligence", and even more so "recursive-self-improving superintelligence" (RSIS for short?). There are not only various limits to hardware, some of which discussed in the article (size of atoms, capacity of communication between parts), but also there are limits to software. For example, while it seems that an RSIS could really solve any problem it wanted, Turing's almost century-old Halting Problem solution already proved that no such computer exists. There's no algorithm that takes an arbitrary conjecture, e.g. the Riemann hypothesis, and outputs either {yes,no,malformed_problem}. In fact the general expectation of what AGIs can do (think creatively, solve arbitrary problems, replace mathematicians, replace programmers) are things that we ourselves can't really do. We solve problems using a small set of heuristics and lots of trial and error, with no success guarantee. Another fact is that there are many asymptotically optimal algorithms that are already know, and the trivial fact that almost all tasks performed by this super-intelligence (many of which are ordinary tasks we already do, analogous to maybe sorting, database queries, and search engines) will just improve constants on near-optimal algorithms. A god-like creature those AIs will be not.
- 9y ago