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by mjburgess 1857 days ago
> Yet cars are much more intelligent today than they were in the 1970s

Therein lies the problem. Your definition of intelligence presumes that it is a simple quantitative scale, measuring I guess, something like "system complexity".

The relevant sense here, in which no progress has been made, is qualitative -- ie., it is a distinct property. And this property has not been acquired.

What is the property? It is dynamical, not formal. It is more like gravity (, pregnancy) than it is like addition.

It is the ability many animals have of adaption in the shifting and challenging environments in which they are embedded.

That type of adaption is not formal: it is not adaption in the sense of "updating a weight parameter". Rather, of the cells of their bodies coordinating themselves differently, and thus of their tissues, and thus of their organs, and thus of their whole brain-body system. Both from a top-down command ("I want to run now, and so my cells...") and from a bottom-up ("my cells... so I ...").

What enables animals to be fully embedded in their physical environment, to cope and adapt to its radical shifts, is this capacity. The type of "crossword puzzle" "intelligence" we obsess with is entirely derivative of this more basic --and vastly more powerful -- intelligence.

Cognition is just a semi-formal process, parasitical on the body's intelligence; whose role is simply to notice when it fails and problem-solve it.

We have, at best, merely the architecture of this formal reasoning. But there is still nothing for it to reason about. And in this sense, computer science has made no progress -- and indeed, cannot. It is not a formal problem.

3 comments

And yet computers continue to perform tasks that were talked about for years as something uniquely human / intelligence driven. This is a nice philosophical debate, but in practice I think it falls flat.
I dont see any single case of that. Rather in every case the goal posts were moved.

Can a computer play chess? No.

They search through many permutation of board states and in a very dumb way merely select the decision path that leads to a winning one.

That was never the challenge. The challenge was having them play chess; ie., no tricks, no shortcuts. Really evaluate the present board state, and actually choose a move.

And likewise everything else. A rock beats a child at finding the path to the bottom of a hill.

A rock "outperforms" the child. The challenge was never, literally, getting to the bottom of the hill: that's dumb. The challenge was matching the child's ability to do that anywhere via exploration, curiosity, planning, coordination, and everything else.

If you reduce intelligence to merely completing a highly specific task then there is always a shortcut, which uses no intelligence, to solving that task. The ability to build tools which use these shortcuts was never in doubt: we have done that for millenia.

> They search through many permutation of board states and in a very dumb way merely select the decision path that leads to a winning one.

> That was never the challenge. The challenge was having them play chess; ie., no tricks, no shortcuts. Really evaluate the present board state, and actually choose a move.

Uh-huh. And how exactly do you play chess? Do you not, perhaps, think about future states resultant from your next move?

Also, Alpha Zero, with its ability to do a tree search entirely removed, achieves an ELO score of greater than 3,000 in chess, which isn't even the intended design of the algorithm.

A rock will frequently fail to get the to bottom of a hill due to local minimums vs. global minimums. A child will too sometimes.

> Uh-huh. And how exactly do you play chess? Do you not, perhaps, think about future states resultant from your next move?

Not quite. You'd need to look into how people play chess. It has vastly more to do with present positioning and making high-quality evaluations of present board configuration.

> rock will frequently fail to get the to bottom of a hill due to local minimums

Indeed. And what is a system which merely falls into a dataset?

A NN is just a system for remembering a dataset and interpolating a line between its points.

If you replace a tree search with a database of billions of examples, are you actually solving the problem you were asked to solve?

Only if you thought the goal was literally to win the game; or to find the route to the bottom of the hill. That was never the challenge -- we all know there are shotcuts to merely winning.

Intelligence is in how you win, not that you have.

> Not quite. You'd need to look into how people play chess. It has vastly more to do with present positioning and making high-quality evaluations of present board configuration.

That is what Alpha Zero does when you remove tree search

> A NN is just a system for remembering a dataset and interpolating a line between its points.

Interpolating a line between points == making inferences on new situations based on past experience.

> If you replace a tree search with a database of billions of examples, are you actually solving the problem you were asked to solve?

The NN still performs well on positions it hasn't see before. It's not a database. The fact that the NN learned from billions of examples is irrelevant. Age limits aside, a human could have billions of examples of experience as well.

> A NN is just a system for remembering a dataset and interpolating a line between its points.

So are human brains. That is the very nature of how decisions are made.

> Only if you thought the goal was literally to win the game; or to find the route to the bottom of the hill. That was never the challenge

So then why did you bring it up as an example other than to move goal posts yet again? I can build a bot to explore new areas too. Probably better than humans can. Any novel perspective that a human brings, is, by definition, learned elsewhere, just like a bot.

> Intelligence is in how you win, not that you have.

Sure, and being a dumbass is in how you convince yourself you're superior when you lose every game. There are many open challenges in AI. Making systems better at learning quickly and generalizing context is a very hard problem. But at the same time, intellectual tasks are being not only automated, but vastly improved by AI in many areas. Moving goalposts on what was clearly thought labor in the past is just handwaving philosophy to blind yourself from something real and actively happening. The DOTA bots don't adapt to unfamiliar strategies by their opponents, and yet, they're still good at DOTA.

Humans do not interpolate between billions of examples. A human cannot be shown billions of examples in a lifetime.
Let’s say that you have the ability to know the state of every neuron, and the interconnect map between them, at all times. You watch a chess player make a move, determine what is going on, and define the process the brain follows as an algorithm. Now that you have an algorithm, you have a very powerful piece of silicon execute the algorithm. Does that piece of silicon have intelligence? You would probably say no, since simply executing a pre-defined algorithm is a shortcut. Intelligence means the ability to develop the algorithm intrinsically in your head.

So fine, we take a step back. Instead of tracing all the neurons as they determine a chess move, we trace all the neurons as they start, from a baby, and learn to see and to understand spatial temporal behavior and as they understand other independent entities that can think like they do and as they learn chess and how to make a move. Then we encode all of that into algorithms and run it on silicon. Is that intelligence? To me, it sounds like it is just a shortcut - we figured out what a brain does, reduced it to algorithms, and ran those algorithms on a computer.

What if we go back further and replay evolution. Is that a shortcut?

To be fair, you did claim that the ability to adapt and make tools is what distinguishes real intelligence. But I wonder if ten years from now, you will saying that a tool making computer is just a shortcut.

I think intelligence is more generally how an agent optimizes to be successful, objectively and subjectively, across a wide variety of different situations.
> Can a computer play chess? No. > They search through many permutation of board states and in a very dumb way merely select the decision path that leads to a winning one.

This is a perfect example of moving the goal posts. The objective was never to simulate a human playing chess.

The moving of the goal posts is being done by those who claim that chess algorithm are in any sense intelligent.

The same holds for artificial intelligence broadly. It is as far from intelligence as a can opener.

At what point would you be willing to concede that an algorithm is actually intelligent? What would be required for that?
The definition of algorithm and intelligence are mutually exclusive. Maybe you are asking a different question?

"When will we discover an algorithm for intelligence?"

If a lookup table can predict human decisions with high accuracy given access to its senses and feelings, then either a human is just another can opener or intelligence isn't real.
The objective was to build an intelligent machine. Games were chosen as they, in humans, require intelligence.

They thought that AI would come out of building systems that can replace humans: sure, but only insofar as you preserve the use of intelligence.

If you replace with a shortcut, you havent built an intelligent machine.

The objective was to make a machine that could beat anybody at chess. Nobody on the Alpha Zero team believes Alpha Zero is an example of general AI. Teaching a system to understand a complex system is a necessary subcomponent of general intelligence.
> Teaching a system to understand a complex system is a necessary subcomponent of general intelligence.

This is my point. Weak AI is not a component of general AI. A chess game futhers the project zero amount.

General intelligence is a way of being embedded in an environment; is the mechanism of furnishing narrow intelligence with content.

It is not a formal challenge, it's at best an engineering one. And a bioengineering one, in my view.

Are you suggesting that there is a binary property "intelligent or not"? In which case, what would progress even look like?
Indeed, a bit like, "made of metal, or not".

And I think it looks more or less like, "organic-in-relevant-way or not".

"Relevant" here means a type of organic-physiological adaptability which is able to operate on incredibly short time scales: ie., you're able to physically adapt your body as your environment changes at the second, minute, hour, day, ... decade, timescales.

Typing is a type of organic adaption which takes years to complete. As are essentially all of our skills.

With digital machines and robots we're maybe able to emulate our cognitive processes as they consider our body-environment relationship. But we have not emulated, at all, our ability to have this type of body-environment relationship.

A dog is not.made of metal but I have yet to see a dog that drives better than a waymo self-driving car.
A dog's environment isn't roads. And no car has been design for a dog to drive.

Were such a car to exist, it is clear the dog would win in very very many environments (almost all). As would a mouse, let alone a dog.

That it may be possible to rig a human environment to be replete with so many symbols (road signs, etc.) that an incredibly dumb automated system can follow them is hardly here-nor-there.

Personally, I dont even think that will be possible. Self-driving cars may work on highways and motorways; I don't see there being any in cities. Not for centuries.

(Absent pretty big engineering projects to make cities so overly sign'd that a non-intelligent automated system could navigate them. Consider, eg., existing automated trains & train networks.)

> Were such a car to exist, it is clear the dog would win in very very many environments (almost all). As would a mouse, let alone a dog.

This seems incredibly unlikely. AI vastly outperforms 99.99% of humans on various video games, and 100% on many others. I'll bet on a well trained ml model over a dog every time.

> That it may be possible to rig a human environment to be replete with so many symbols (road signs, etc.) that an incredibly dumb automated system can follow them is hardly here-nor-there.

We already have above average human performance with just normal road signs, and could also simply use digital information.

> Self-driving cars may work on highways and motorways; I don't see there being any in cities. Not for centuries.

Goalpost shifting

IMHO the biggest problem is the moral problem; even once the tech achieves better reliability in general (as compared to human drivers, who are quite crappy but we're all used to them), the cases when it will fail will be so spectacular and cause so much outrage because we're ill equipped to deal with situations where there is nobody to blame: we always try to find somebody to hold responsible. When there is none, we make them up (deities and whatnot).

When natural disaster strike, people feel plenty of emotions, including anger. Often that anger though cannot be directed to anybody in particular. ("God isn't easily sued

When machines misbehave, being by definition human made, it's harder to accept it "as just the way the world works".

"centuries"

Centuries is a long, long time in science and technology. It is 2021. If we take "centuries" to mean two centuries, railways with steam engines were not yet a thing in 1821. Cars without horses much less so.

None of us can predict the state of computer science in 2221.

A waymo self-driving car is not made of flesh and bones but I have yet to see a waymo self-driving car that performs better than a dog at: rescuing humans, detecting cancers and disease, shepherding and playing with other animals, protecting family from threats...
> rescuing humans

Vague and undefined, mostly a hardware problem, not an intelligence problem

> detecting cancers and disease

AI is a strong tool for detecting many cancers, and in some areas of research, just using the same olfactory data as dogs: https://journals.plos.org/plosone/article?id=10.1371/journal...

> shepherding

Again, not so much an intelligence problem, but a hardware problem. Nonetheless

https://www.theguardian.com/world/2021/apr/09/stress-test-au...

> protecting family from threats

In terms of ability to recognize and classify a threat, AI is clearly superior here. Dogs have terrible false positive rates.

my point was just a crude attempt to dispel the myth that flesh has anything to do with efficiency at some task. What matters is design, and the immense research powers that nature has through eons of natural selection does an impressive job and doing things for which it has been "trained for" (hence your example).
FYI. Humans are made of metal. Iron, Calcium, and Sodium are all essential metals.
You have a valid point here. But it might be that for practical reasons the progress in that direction won't be needed. Like, brute forcing it might be enough to reach a level higher than we can grasp. And if we can't grasp it, it's all Greek to us anyway...
The problem with brute forcing is it requires data from the future.

Physics can be solved with statistics, but only from God's POV.

The future, absent information about it, is too open to solve by merely constraining models by past example cases.