https://blogs.scientificamerican.com/guest-blog/a-brief-guid...
It seems there's nothing logical about human cognition, it just ends up resembling logic because movement through space either works or it doesn't, and humans have the ability to assign physical analogies to abstractions and to respond to those metaphors with the same heuristics and physical reflexes that it was born with; heuristics and reflexes designed over a few billion years to allow your ancestors to survive and reproduce.
The problem with training things on artificial datasets is that they are not rich (resolution is too low) or surprising (generated by simple algorithms.) An AI that worked as well as the human brain would just end up reading them back to you. The real world is, information-wise, incompressible. It has such fine distinctions that its impossible to examine them beyond a certain level without the act of observation changing them.
I always thought there was some potential in using robotic bodies with good sensors that fed into some processing theory of mind in order to grow an AI.
Simply put we need to work more on mirroring nature and biological brains to get computer brains that function like human brains. Even neuroscience still debates on what consciousness even is.
If you could humor me, why can't it all be deep learning? It seems like a robust model for how we learn: we start with some priors (random weights), experience something that either confirms or negates those priors (sampling), and then adjust our priors based on that experience.
Of course there are a wide variety of architectures and the human brain is more sophisticated than one conv net. Our brains have on the order of 100 billion neurons and I believe the largest neural networks are on the order of 10's of millions. I would argue that a combination of better architectures and scale could simulate human intelligence.
i dont think we start with random priors. We start with a set of priors that are geared for certain things - facial recognition, language etc. The environment then fine tunes them.
No, we don't "learn" how to balance, how to identify objects and navigate 3d environments. All of that is highly codified in our DNA from hundreds of millions of years of evolution. Human babies, similar to kangaroos, are just born too early for those systems to have developed.
Also, not everything we do is in our brain -- there's also muscle memory, and even tissue inside the gut stores some memories and 'knowledge'. Technically every cell in our body has some purpose/goal and can contribute to our entire being/feeling/mood/etc.
There's a lot we don't know about conscience that makes developing an artificial one, very tough. That's why it's not estimated to happen till after 2050. I don't doubt it will happen, I don't doubt deep learning as is will be crucial to the discovery, I just think there's possibilities that undiscovered and better/alternate techniques might be discovered that could potentially trump dl as we now know it.
There's a lot of things we do not know to get us to general ai, and to get there we may need to jump outside some 'boxes' that ai researches have put themselves into.
Other than being unsubstantiated, the real world only runs at 1x, simulated world can run at any rate your computing platform supports.
That’s the steelmanned argument at least.
The storing of that can take up precious resources, to create service droids that can do everything using AGI we need the computer that runs it to be essentially the size of a real human brain. Which we need to find ways to map AI tech more closely to biology.
There's also the fact that we are born with instincts built up over millenia, passed down. We also absorb random tidbits of data with no actual purpose. We watch the news and our toddler gets excited at the commercials, I don't know what he's learning from it, but getting him to turn his attention away from it is nigh impossible.
You can see the processing going on, it's amazing to watch him learn. I just think we need to think outside the current ai 'boxes' with dl/ml and consider their may be whole swath's of things we're missing, whole pieces of the puzzle before we get to AGI or the Singularity.
Perhaps the answer is to figure out all the things that make people tick via deep learning and other techniques, build one huge open api/db for vision/audio/movement in 3d planes/ethics/morality/understanding/discernment/language and then a more general ai could simply send out calls to api's of data already trained on specific foundations and create a 'whole' brain from multiple 'sub' brains (pre-learned open knowledge).
Unless we literally learn to clone the human brain technologically, in it's entirety.
I think another issue is not all working in AI are neuroscientists, and it may take understanding every mapped out facet of the human brain to come close to re-creating that in humans, it all can't be deep learning unfortunately, because that's not how we learn and we're the best guess solution to 'intelligence' as the only intelligent race (we know of) in the universe.