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EURISKO Lives

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Re: EURISKO Lives

#71

Post by at_a_remove »

rvba wrote: post #41
api wrote: post #26

Earlier quoted context omitted.

> a much younger Eliezer Yudkowsky cautioning that Doug Lenat should have perceived a non-zero chance of hard takeoff at the moment of its birth Why is Yudkowsky taken seriously? This stuff is comparable to the "LHC micro black holes will destroy Earth" hysteria. There are actual concerns around AI like deep fakes, a deluge of un-filterable spam, mass manipulation via industrial scale propaganda, mass unemployment cr…

> "LHC micro black holes will destroy Earth" hysteria. I will be heavily downvoted for this, but here is how I remember it: 1) LHC was used to study blackholes and prove things like Hawking radiation 2) LHC was supposed to be safe due to Hawking radiation (that was only an unproven theory at the time) So the unpopular question: what if Hawking radiation didnt actually exist? Wouldnt there be a risk of us dying? A sma…

You remember ... wrongly. It's just another particle accelerator, its intention was not to produce micro black holes for study.

You shouldn't use "theory" when it comes to science unless you know what that means. Gravity is a "theory." "Theory" means that it has a working model, comes with a ton of observational evidence in line with predictions, and it has yet to be replaced by anything better. Outside of math, nothing is ever proven. Any leading scientific theory is, at best, "yet to be disproven." And it stays in the lead until something better comes along: more accurate, extending over a greater domain, etc.

Hawking radiation has yet to be observed.

And if you're worried about micro black holes, well, even an iron atom has a non-zero chance of tunneling to a micro black hole state. No collider needed.

Cyc isn't secretive, it's proprietary, the way the Microsoft codebase is, the Adobe codebase is, and so on.

Re: EURISKO Lives

#72

Post by lisper »

avmich wrote: post #70
lisper wrote: post #63

Earlier quoted context omitted.

Sorry about that, I'm dealing with a troll on another thread so I'm on a bit of a hair trigger. I think we have a fundamental disconnect somewhere, so let's try to diagnose it. Where do you start to disagree in the following series of claims: 1. People can have kinematic skills, like throwing and catching balls, without having math or physics skills, like solving kinematic equations. 2. In order to have kinematic ski…

It's great to read conversation of towering HN experts in the field. Lisper, as I understand this part - > In order to have kinematic skills, something in your brain must be doing something that can be equated by some mapping to solving kinematic equations you're talking about an equivalent of YeGoblynQueenne's > that humans ... do not find solutions to kinematic equations, but instead use simple heuristics that expl…

Let's go back to the original formulation so we don't lose the plot here:

Me: As an analogy, consider a professional tennis or baseball player.

YeGoblynQueenne: humans e.g. playing baseball do not find solutions to kinematic equations, but instead use simple heuristics that exploit our senses and body configuration, like placing their hands in front of their eyes so that they line up with the ball etc.

At the risk of stating the obvious, being a professional tennis or baseball player involves a lot more than "simple heuristics ... like placing their hands in front of their eyes so that they line up with the ball." That simple heuristic might work for one specific skill -- catching a ball that happens to be heading in your direction. But it won't help much for moving a bat or a raquet in such a way that it will hit a ball moving past you at close to 100mph in such a way that the ball ends up traveling on some desired trajectory.

But even just moving your hand in front of your eyes is nowhere near as trivial as YeGoblynQueenne implies. To do that you have to control seven degrees of freedom: two at your shoulder, two at your elbow, and two at your wrist. Solving those kinematic equations even to find a static solution is elementary but non-trivial, a skill that is solidly at the undergraduate level.

Now consider running to catch a ball. That involves controlling about 20 or 30 degrees of freedom (two arms, two legs, neck, waist, two eyes...) in real time in a situation that involves not just kinematics but also dynamics. Solving that analytically was an unsolved research problem for a long time (maybe still is, I haven't been keeping up with recent developments). A child can learn to do it. But they do have to learn to do it. It's not a skill humans are born with.

It seems pretty obvious to me that the process of learning how to catch a ball while running is very different than the process of learning how to do math. And yet, there must be a mapping between them because the movements required for catching a ball are the solutions to kinematic equations.

Re: EURISKO Lives

#73

Post by avmich »

lisper wrote: post #72
avmich wrote: post #70

Earlier quoted context omitted.

It's great to read conversation of towering HN experts in the field. Lisper, as I understand this part - > In order to have kinematic skills, something in your brain must be doing something that can be equated by some mapping to solving kinematic equations you're talking about an equivalent of YeGoblynQueenne's > that humans ... do not find solutions to kinematic equations, but instead use simple heuristics that expl…

Let's go back to the original formulation so we don't lose the plot here: Me: As an analogy, consider a professional tennis or baseball player. YeGoblynQueenne: humans e.g. playing baseball do not find solutions to kinematic equations, but instead use simple heuristics that exploit our senses and body configuration, like placing their hands in front of their eyes so that they line up with the ball etc. At the risk of…

I suspect there's a terminological difference.

> being a professional tennis or baseball player involves a lot more than "simple heuristics ...

Mmm, a combination of simple heuristics, all of which are of course learned, but still simple heuristics, could in itself be a simple heuristic. Yet it could allow performing pretty complex-looking actions, including those you described. Simple heuristic here could be a linear or low degree polynomial approximation of a good solution to kinematic equation - not precise, but enough to get to the goal, while learnable and explainable. But still without actual full-blown abstract, mathematically correct complete solution.

Re: EURISKO Lives

#75

Post by TeMPOraL »

talldayo wrote: post #43
adw wrote: post #38

Earlier quoted context omitted.

People have advanced that argument a lot, and it's often worked for a short while; then the statistical models get better. Chess was a game for humans. It was very briefly a game for humans and machines (Kasparov had a go at getting "Advanced Chess" off the ground as a competitive sport), but soon enough having a human in the team made the program worse. But at least the evaluation functions were designed by humans,…

I find myself not wanting to agree with you, but deep down I think you're right. AI greatly reminds me of the Library of Babel thought experiment. If we can imagine a library with every book that can possibly be written in any language, would it contain all human knowledge lost in a sea of noise? Is there merit or value in creating a system that sifts through such a library to attune hidden truths, or are we dooming…

> If we can imagine a library with every book that can possibly be written in any language, would it contain all human knowledge lost in a sea of noise? Is there merit or value in creating a system that sifts through such a library to attune hidden truths, or are we dooming ourselves to finding meaning in nothingness?

The work that system would be required to find those "hidden truths" is equivalent to re-deriving those truths from scratch.

Similar argument: an image is just a number; if you take e.g. a 800x600 24bpp picture, that's a number 1 440 000 bytes long; you could hypothetically start from 0 and generate every 1 440 000-byte number, thus generating every possible 800x600 24bit image. In that set, you'd find every historical event, photographed at every moment from every angle, and even photos of every fragment of every book from the Library of Babel. But good luck finding anything particular in there.

Similar argument 2: any movie or song is contained somewhere within digital expansion of the number Pi. But again, it's worthless unless you know how to find such works, which basically requires you to have them in the first place.

Re: EURISKO Lives

#76

Post by TeMPOraL »

YeGoblynQueenne wrote: post #53
lisper wrote: post #52

Earlier quoted context omitted.

> then the statistical models get better Maybe. The statistical models are definitely better at natural language processing now, but they still fail on analytical tasks. Of course, human brains are statistical models, so there's an existence proof that a sufficiently large statistical model is, well, sufficient. But that doesn't mean that you couldn't do better with an intelligently designed co-processor. Even humans…

If human brains are statistical models, why are human brains so bad at statistics? Edt: btw, same for probabilistic inference, same for logical inference, and same for any other thing anyone's tried as the one true path to AI since the 1950's. Humans have consistently proven bad at everything computers are good at, and that tells us nothing about why humans are good at anything (if, indeed, we are). Let's not assume…

> If human brains are statistical models, why are human brains so bad at statistics?

If CPUs are made of silicon, why are they so bad at simulating semiconductors? Or why CPUs are so bad at emulating CPUs?

If JavaScript runs on a CPU, why is it so bad at doing bitwise stuff?

Etc.

What the runtime is made of is entirely separate of what's running on it. Same is with human brain (substrate) and human consciousness (software), or humans (substrate) and bureaucracy (runtime) and corporations (software).

Re: EURISKO Lives

#77

Post by datascienced »

YeGoblynQueenne wrote: post #53
lisper wrote: post #52

Earlier quoted context omitted.

> then the statistical models get better Maybe. The statistical models are definitely better at natural language processing now, but they still fail on analytical tasks. Of course, human brains are statistical models, so there's an existence proof that a sufficiently large statistical model is, well, sufficient. But that doesn't mean that you couldn't do better with an intelligently designed co-processor. Even humans…

If human brains are statistical models, why are human brains so bad at statistics? Edt: btw, same for probabilistic inference, same for logical inference, and same for any other thing anyone's tried as the one true path to AI since the 1950's. Humans have consistently proven bad at everything computers are good at, and that tells us nothing about why humans are good at anything (if, indeed, we are). Let's not assume…

Your question implies it is obvious that a system of statistical models would (or should) be good at statistics. And that the opposite is a paradox. I would ask why you think that is obvious?

Being good at statistics is more of a knowledge graph of understanding concepts than a statistical model, I think.

Just like understanding a car engine.

Re: EURISKO Lives

#80

Post by YeGoblynQueenne »

lisper wrote: post #63
YeGoblynQueenne wrote: post #61

Earlier quoted context omitted.

... because they don't need to use maths or physics? And yes, I'm serious. Can you please be less confrontational?

Sorry about that, I'm dealing with a troll on another thread so I'm on a bit of a hair trigger. I think we have a fundamental disconnect somewhere, so let's try to diagnose it. Where do you start to disagree in the following series of claims: 1. People can have kinematic skills, like throwing and catching balls, without having math or physics skills, like solving kinematic equations. 2. In order to have kinematic ski…

>> Sorry about that, I'm dealing with a troll on another thread so I'm on a bit of a hair trigger.

Hey, no worries. Thanks for being a gentleman and I'm sorry you're being harassed. Btw, just to be clear: I'm perfectly fine with robust disagreement, I just don't deal well with personal attacks; which you didn't do, I was just worried that's where this conversation was going.

So, thanks for the very detailed analysis of your argument. That indeed makes it much simpler to find common ground. Here's where I disagree: point number 2!

Here's why. It's obvious to me that it's entirely possible to have two distinct models of the same process that compute almost identical results, so it's entirely possible for humans to be using a completely different process to catch balls etc, than kinematic equations.

And here's why I think this is likely: first, because of the point I made above about computational complexity and second because of the observed wide variability in the uh, let's say kinematic capabilities of different humans. If we were all solving kinematic equations, we would all have the same skills. What's more: humans can be wildly inaccurate in their motions (I know I am; don't leave coffee cups on my desk), while robots for example, are distinctly not. That also points to a different computation.

So, to summarise my argument: what we do needs neither be the same computational process, nor be computing the same results, as kinematic equations.

Btw, I'm a bit confused because I thought you were talking about kinematics in classical mechanics, but now I think you're talking about kinematics in robotics, with muscle actions etc. But I think both apply, except the robotics equations are I think much easier to solve than the classical mechanics ones, which I suspect may veer off into the chaotic.

Edit: I had more here on my _agreement_ to your point number 4, but I'm cutting it down to shorten the comment. You don't have all day :)

In any case, I think we just can't say for sure what our brains do, until we can say for sure.

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