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One problem with ai (or general ai) is ai lives in a box, it experiences what we tell it to experience, unlike a child who learns organically with what it's exp

One problem with ai (or general ai) is ai lives in a box, it experiences what we tell it to experience, unlike a child who learns organically with what it's exposed to randomly while trying to survive and thrive. 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.

choxi 8y ago
> it all can't be deep learning unfortunately, because that's not how we learn 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.
- chii 8y ago
  > we start with some priors (random weights) 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.
  - garmaine 8y ago
    There is no way that the genome encodes synaptic layouts to such a detail as to specify an algorithmic prior. At best it specifies, loosely, the generic architecture of how many neurons, how many layers, how tightly folded, and where the inputs (senses) connect. We develop the same algorithms because we all start with the same priors in largely the same gestational and early infant environments.
    - username90 8y ago
      Right, watch this genius horse learn to walk and navigate a 3d environments just hours after birth: https://www.youtube.com/watch?v=RXKdYThau7c https://www.youtube.com/watch?v=RXKdYThau7c 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.
      - garmaine 8y ago
        Is this sarcasm? You do know that babies (human or animal) exercise their muscles and gain body awareness during gestation, right?
- gremlinsinc 8y ago
  Part of it could be hardware related, we may need special chips just geared for this, with special coded sensors. 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.
russdill 8y ago
Seen a few people claim from time to time that real world experience is the "special sauce" of general AI. I've never seen anything to substantiate this claim. We all live in a box, we all experience our world through simple electrical signals. Other than being unsubstantiated, the real world only runs at 1x, simulated world can run at any rate your computing platform supports.
- garmaine 8y ago
  Much of our reasoning develops from metaphorical comparisons with our embodied experiences. E.g. it is certainly true that we gain spatial awareness from embodiment, and it is worth noting how much of our language of reasoning uses spatial metaphors. Can we expect a non-embodied AI whose only view of the world is text we feed it to develop a similar understanding? That’s the steelmanned argument at least.
- gremlinsinc 8y ago
  One feature also is hardware capabilities (storage + processing), the human body/mind is extremely capable. It can store an unknown amount of data, it boggles my 'mind' at the amount that can be stored in such a small area compared to today's hdd's and sdd's, then how fast we can bring up those memories - yet we don't always have those memories in quick access points, sometimes we have to think real hard to remember something. We also don't remember EVERY single detail about something, only key characteristics, where I think a lot of AI tries to learn/store/remember everything about something. 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.
pessimizer 8y ago
Have you ever done any reading about "embodied cognition"? https://blogs.scientificamerican.com/guest-blog/a-brief-guide-to-embodied-cognition-why-you-are-not-your-brain/ 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.
- gremlinsinc 8y ago
  I think finding a way to quite literally build a 'brain' that mimics all aspects of the human brain including: Size, shape/areas/etc that is essentially a mechanically cloned brain like a mechanical heart or lung (Similar to the organs in Bicentennial man), may be the only way to get true AGI. 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.

choxi 8y ago

> it all can't be deep learning unfortunately, because that's not how we learn 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.

chii 8y ago
> we start with some priors (random weights) 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.
- garmaine 8y ago
  There is no way that the genome encodes synaptic layouts to such a detail as to specify an algorithmic prior. At best it specifies, loosely, the generic architecture of how many neurons, how many layers, how tightly folded, and where the inputs (senses) connect. We develop the same algorithms because we all start with the same priors in largely the same gestational and early infant environments.
  - username90 8y ago
    Right, watch this genius horse learn to walk and navigate a 3d environments just hours after birth: https://www.youtube.com/watch?v=RXKdYThau7c https://www.youtube.com/watch?v=RXKdYThau7c 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.
    - garmaine 8y ago
      Is this sarcasm? You do know that babies (human or animal) exercise their muscles and gain body awareness during gestation, right?
gremlinsinc 8y ago
Part of it could be hardware related, we may need special chips just geared for this, with special coded sensors. 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.

russdill 8y ago

Seen a few people claim from time to time that real world experience is the "special sauce" of general AI. I've never seen anything to substantiate this claim. We all live in a box, we all experience our world through simple electrical signals. Other than being unsubstantiated, the real world only runs at 1x, simulated world can run at any rate your computing platform supports.

garmaine 8y ago
Much of our reasoning develops from metaphorical comparisons with our embodied experiences. E.g. it is certainly true that we gain spatial awareness from embodiment, and it is worth noting how much of our language of reasoning uses spatial metaphors. Can we expect a non-embodied AI whose only view of the world is text we feed it to develop a similar understanding? That’s the steelmanned argument at least.
gremlinsinc 8y ago
One feature also is hardware capabilities (storage + processing), the human body/mind is extremely capable. It can store an unknown amount of data, it boggles my 'mind' at the amount that can be stored in such a small area compared to today's hdd's and sdd's, then how fast we can bring up those memories - yet we don't always have those memories in quick access points, sometimes we have to think real hard to remember something. We also don't remember EVERY single detail about something, only key characteristics, where I think a lot of AI tries to learn/store/remember everything about something. 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.

pessimizer 8y ago

Have you ever done any reading about "embodied cognition"? https://blogs.scientificamerican.com/guest-blog/a-brief-guide-to-embodied-cognition-why-you-are-not-your-brain/ 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.

gremlinsinc 8y ago
I think finding a way to quite literally build a 'brain' that mimics all aspects of the human brain including: Size, shape/areas/etc that is essentially a mechanically cloned brain like a mechanical heart or lung (Similar to the organs in Bicentennial man), may be the only way to get true AGI. 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.