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Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

nytimes.com

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Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#41

Post by newsbinator »

skohan wrote: post #40
kcorbitt wrote: post #38

Earlier quoted context omitted.

> Each one of those synapse is a complex, constantly adapting chemical computer which is sensitive to the interaction of dozens of neurotransmitters. Granted. On the other hand, electric signals can propagate across a chip several orders of magnitude faster than the chemical-electrical signals neurons use to communicate. So while our current path won't lead us to an artificial brain that works exactly like the human…

> "we're not building machines that work exactly like the brain does" is a poor counterargument. It's not that artificial intelligence has to work exactly like human intelligence; my point is that the system that produces human intelligence is many orders of magnitude more complex than what passes for AI these days. I think there's an idea out there that because deep learning allows computers to solve some problems t…

It may not be necessary for a system to be as complex as the human brain to reach the raw intelligence levels of the human brain.

You don't need to make a vehicle as complex as a cheetah for it to move as quickly as cheetah. You just strap a rocket to a box and you're there.

Granted a rough solution like that is not as good or as agile as a live cheetah in a lot of ways, but it depends on what you're optimizing for.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#42

Post by FrozenVoid »

gaius wrote: post #16
FrozenVoid wrote: post #4

Lets rename "Deep learning" to "Statistical Compression". Its essentially distilled data from a dataset, limited by size of the neural network. There isn't anything "deep" there, the goal of NN is always towards overfitting the data.

Lets rename "Deep learning" to "Statistical Compression" The previous name for what is now called “machine learning” was predictive statistics. But a better name for deep learning is “machine intuition” since it seems to work pretty well but can’t be readily explained

> can’t be readily explained

It works "pretty well" in well-defined complete-information domains like Go.

The training in that case is actually about improving the next dataset from which higher-quality patterns are extracted.

1.We have a NN that doesn't know how to play and makes random moves.

2.Blank slate dataset filled from random games.

3.NN learns to produce better games by weighting wins vs losses, making losing moves less likely and winning moves more likely.

4.NN produces slightly better dataset.

5.Repeat #3 until you have covered a large chunk of go openings and have pretty good estimation for move quality.

6.NN becomes the condensed statistic pattern data extracted from billions of games, able to estimate value of a move more accurately than humans.

Still in some rare cases it "condensed pattern database" will make mistakes due gaps in data or wrong correlation that NN hallucinated from its connections.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#43

Post by gremlinsinc »

choxi wrote: post #28
gremlinsinc wrote: post #24

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/understandin…

> 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 h…

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.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#44

Post by gremlinsinc »

russdill wrote: post #29
gremlinsinc wrote: post #24

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/understandin…

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.

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.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#45

Post by gremlinsinc »

pessimizer wrote: post #30
gremlinsinc wrote: post #24

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/understandin…

Have you ever done any reading about "embodied cognition"? 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 refl…

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.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#46

Post by polkapolka »

sgt101 wrote: post #35
YeGoblynQueenne wrote: post #26

Earlier quoted context omitted.

Well, going by formal language theory, FOL is equivalent to a universal Turing machine, which is probably also the full expressive power of human language. Therefore, everything that can be said in human language should in principle be possible to say in FOL. I don't think this is controversial. Notice again that I don't think this is feasible in practice. At least not with hand-crafted FOL expressions and certainly…

Yeah but humans don't have a single consistent logical model for all reasoning - i believe that all my models can be in fol, but i don't believe that they can be unified in fol

Dennett aims to solve this using heterophenemenology:

https://en.m.wikipedia.org/wiki/Heterophenomenology

In this framework, utterances can be studied without taking their truth value at face value.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#47

Post by gaius »

FrozenVoid wrote: post #42
gaius wrote: post #16

Earlier quoted context omitted.

Lets rename "Deep learning" to "Statistical Compression" The previous name for what is now called “machine learning” was predictive statistics. But a better name for deep learning is “machine intuition” since it seems to work pretty well but can’t be readily explained

> can’t be readily explained It works "pretty well" in well-defined complete-information domains like Go. The training in that case is actually about improving the next dataset from which higher-quality patterns are extracted. 1.We have a NN that doesn't know how to play and makes random moves. 2.Blank slate dataset filled from random games. 3.NN learns to produce better games by weighting wins vs losses, making losi…

works "pretty well" in well-defined complete-information domains like Go

But no one can definitively say “my AI credit scoring system didn’t decline his mortgage because he is black” and that’s the explainability bar that needs to be passed.

Right now the state of it is “gut feel” with an unknown amount of unconscious bias.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#48

Post by altvali »

skohan wrote: post #32

Deep learning has produced a lot of interesting results over the past few years, but we're still miles away from anything that even approximates human intelligence. When I hear someone like Elon Musk say something like "Autonomous vehicles can drive without Lidar because humans can drive without Lidar" it makes me cringe. The human brain is unimaginably complex. Even if we created a neural network on the order of the…

Perhaps Elon meant to reason the following: if humans can drive without Lidar, then it is possible to drive without Lidar, then it is possible to build an autonomous car that doesn't use an expensive piece of equipment such as Lidar.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#49

Post by sgt101 »

polkapolka wrote: post #46
sgt101 wrote: post #35

Earlier quoted context omitted.

Yeah but humans don't have a single consistent logical model for all reasoning - i believe that all my models can be in fol, but i don't believe that they can be unified in fol

Dennett aims to solve this using heterophenemenology: https://en.m.wikipedia.org/wiki/Heterophenomenology In this framework, utterances can be studied without taking their truth value at face value.

Very interesting, I'll have to think a lot about that.

Re: Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So

#50

Post by sitkack »

altvali wrote: post #48
skohan wrote: post #32

Deep learning has produced a lot of interesting results over the past few years, but we're still miles away from anything that even approximates human intelligence. When I hear someone like Elon Musk say something like "Autonomous vehicles can drive without Lidar because humans can drive without Lidar" it makes me cringe. The human brain is unimaginably complex. Even if we created a neural network on the order of the…

Perhaps Elon meant to reason the following: if humans can drive without Lidar, then it is possible to drive without Lidar, then it is possible to build an autonomous car that doesn't use an expensive piece of equipment such as Lidar.

Being possible and being a good idea are different. I have also driven a car w/o brakes. Or a motorcycle w/o a working clutch.
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