4 ms·

Please take this as nothing more than my subjective opinion: I believe that humans don't have GI but HI - we have a "world-view" that is very idiosyncratic to b

by dkural 7y ago

Please take this as nothing more than my subjective opinion: I believe that humans don't have GI but HI - we have a "world-view" that is very idiosyncratic to being human, which is essentially heuristics all the way down - in other words, I don't believe there is a magical novel concept that explains HI, but that it is a collection of party tricks that evolved over time, i.e. hacky engineered system.

solipsism 7y ago
I don't see why that's not GI. That HI enables us to do incredible things, far beyond what we evolved to do (we evolved to hunt and fuck and exist in small groups, not to do quantum mechanics).
- Fricken 7y ago
  It begs the question, though: is the development of AGI contingent on some magical breakthrough, or is it a matter of endless tinkering and cobbling until we've got something that works?
  - fasturdotcom 7y ago
    magical breakthrough ... https://research.fb.com/publications/canonical-surface-mapping-via-geometric-cycle-consistency/ https://research.fb.com/publications/canonical-surface-mappi...
  - tachyonbeam 7y ago
    It's probably both. There's going to need to be a series of breakthroughs, but there's also going to be a lot of engineering required. I believe that AGI won't happen suddenly. It will require putting a lot of pieces together. We'll get systems that have an incrementally better and better model of their environment. Personally, I find it kind of offensive how scientifically-minded people believe they have the monopoly on generating ideas and making the world progress. That's clearly not true. Deep learning research wouldn't be where it is without GPUs, and compilers like TensorFlow and PyTorch. Engineers are huge drivers of change, they make things happen. Deep learning research already involves a lot of trial and error. Tinkering and cobbling as you put it. People can't really tell, just writing things on a whiteboard, whether it's going to work or not. There might be some mathematical intuition, but a lot of it is throwing things at the wall and seeing what sticks, empirical testing. Some very high percentage of the research being done is basically thrown away. Furthermore, I would personally say, as someone who works in deep learning, that we're collectively getting a little myopic. We finally got neural networks to do cool things. People are very excited, but they're forgetting neural nets are not the only kind of machine learning technique around. It actually works really poorly for some things. We're just largely disregarding every other approach because we have this one cool new toy. So, I don't know, maybe the next huge breakthrough will come from someone who's a deep learning outsider, and who's not completely locked into this paradigm and unwilling to look at anything else.
codingslave 7y ago
Yeah I believe in this too. It's not exactly politically correct to say so for a number of reasons, but if you listen carefully to some public intellectuals, behind the scenes they believe the same. For instance, noam chomsky will talk about how the ability for humans to speak language is hard coded. That if we really were some piece of clay to be molded, noone would be able to run their own life.
- mantap 7y ago
  IMO he's wrong about at least the importance of it, you can point to many tasks that are clearly not hard coded because they are recent inventions yet are difficult for a general AI (with zero task specific architecture) to perform, e.g. driving, playing jazz piano, playing any video game, doing advanced mathematics. Either language is much harder than all of these things (I think that's wrong) or all of these things require language capacity (in which case it's just another form of 'language = thought').
Daniel_sk 7y ago
I believe this too, I think everyone in the field should probably first study the biology, workings and evolutionary mechanisms behind it. I think you first have to understand why actually such level of "GI" exists in humans, what's the actual purpose upon which it evolved. In a perfect world without constraints we would never exist (or life at all), because there would be no constraints that shaped us. Our mind and the way we think is built around the world we live in. Without all the sensor (and other chemical / inside the body) inputs the brain would not work - it would stop to work after the body and inputs are detached (even if you kept supplying all the nutrients). I don't think you can just "store" or encapsulate GI on digital storage because you would have to emulate all the complex environment inputs which it needs to function in a comparable way to humans... We are the "product" of the environment we live in.

by dkural 7y ago

solipsism 7y ago

I don't see why that's not GI. That HI enables us to do incredible things, far beyond what we evolved to do (we evolved to hunt and fuck and exist in small groups, not to do quantum mechanics).

Fricken 7y ago
It begs the question, though: is the development of AGI contingent on some magical breakthrough, or is it a matter of endless tinkering and cobbling until we've got something that works?
- fasturdotcom 7y ago
  magical breakthrough ... https://research.fb.com/publications/canonical-surface-mapping-via-geometric-cycle-consistency/ https://research.fb.com/publications/canonical-surface-mappi...
- tachyonbeam 7y ago
  It's probably both. There's going to need to be a series of breakthroughs, but there's also going to be a lot of engineering required. I believe that AGI won't happen suddenly. It will require putting a lot of pieces together. We'll get systems that have an incrementally better and better model of their environment. Personally, I find it kind of offensive how scientifically-minded people believe they have the monopoly on generating ideas and making the world progress. That's clearly not true. Deep learning research wouldn't be where it is without GPUs, and compilers like TensorFlow and PyTorch. Engineers are huge drivers of change, they make things happen. Deep learning research already involves a lot of trial and error. Tinkering and cobbling as you put it. People can't really tell, just writing things on a whiteboard, whether it's going to work or not. There might be some mathematical intuition, but a lot of it is throwing things at the wall and seeing what sticks, empirical testing. Some very high percentage of the research being done is basically thrown away. Furthermore, I would personally say, as someone who works in deep learning, that we're collectively getting a little myopic. We finally got neural networks to do cool things. People are very excited, but they're forgetting neural nets are not the only kind of machine learning technique around. It actually works really poorly for some things. We're just largely disregarding every other approach because we have this one cool new toy. So, I don't know, maybe the next huge breakthrough will come from someone who's a deep learning outsider, and who's not completely locked into this paradigm and unwilling to look at anything else.

codingslave 7y ago

Yeah I believe in this too. It's not exactly politically correct to say so for a number of reasons, but if you listen carefully to some public intellectuals, behind the scenes they believe the same. For instance, noam chomsky will talk about how the ability for humans to speak language is hard coded. That if we really were some piece of clay to be molded, noone would be able to run their own life.

mantap 7y ago
IMO he's wrong about at least the importance of it, you can point to many tasks that are clearly not hard coded because they are recent inventions yet are difficult for a general AI (with zero task specific architecture) to perform, e.g. driving, playing jazz piano, playing any video game, doing advanced mathematics. Either language is much harder than all of these things (I think that's wrong) or all of these things require language capacity (in which case it's just another form of 'language = thought').

Daniel_sk 7y ago

I believe this too, I think everyone in the field should probably first study the biology, workings and evolutionary mechanisms behind it. I think you first have to understand why actually such level of "GI" exists in humans, what's the actual purpose upon which it evolved. In a perfect world without constraints we would never exist (or life at all), because there would be no constraints that shaped us. Our mind and the way we think is built around the world we live in. Without all the sensor (and other chemical / inside the body) inputs the brain would not work - it would stop to work after the body and inputs are detached (even if you kept supplying all the nutrients). I don't think you can just "store" or encapsulate GI on digital storage because you would have to emulate all the complex environment inputs which it needs to function in a comparable way to humans... We are the "product" of the environment we live in.