AI & Logical Induction - Computerphile
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- Опубліковано 3 жов 2018
- Continuing to address the challenges of AI safety, Rob Miles discusses a paper from the Machine Intelligence Research Institute (MIRI).
Read the paper for yourself here: bit.ly/LogicalInduction
More from Rob Miles: bit.ly/Rob_Miles_UA-cam
/ computerphile
/ computer_phile
This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at www.bradyharan.com
Definitely check out the paper for this one (link in the description). Even in a video this long there's so much cool stuff in there that we didn't have time for! I might make a more technical follow-up video myself if people want that
Absolutely
That would be great!
Please make a followup video, this is a really interesting subject
I am really looking forward to extra bits on this paper on your channel.
You need to eat more and do some exercise to gain some muscle.
Then people say philosphy is useless...this is pure formal epistemology, and it really shows in the references section of the paper BTW (Carnap, Priest, Hintikka, etc...)
Yes, Kant talks about the edges of computability. Except the philosophers of today can't compete or converse on the mathematical level. Which is to say philosophy isn't useless, but philosophers are... Lolz.
@@DJjakedrake how did you come to be so confident in such a false statement? Burnt out from that Williamson?
@@DJjakedrake we tend to be specialists nowadays. In the past, people could be mathematicians, philosophers and even artists all at the same time.
@@IcthiCalm down. It's a "Truthism".
@@whannabiand in the future we will be able to be none of those.
This is what’s been missing from recent computerphile videos. Rob!
He's great, and looks like a real-life Alex Kidd, too.
A young Terence McKenna...
Although I think this is the worst he's ever done, you're still right ;-)
Great video.
One small caveat: the agents must be risk neutral and have a discount factor equal to one, for the conclusions in the video to be right (otherwise, for instance with risk-averse rational agents with a discount factor smaller than one, a 50% bet would be traded at LESS than 0.5, and vice-versa).
Really love all Rob Miles' videos!
wouldnt such agents go bankrupt in the limit, though?
>"spherical chickens in a vacuum"
I always heard this expressed as "spherical cows on a frictionless surface".
I heard it as an anecdote about physics.
A rich man came to biologist, statistician and physicist and asked them to predict the outcome of a horse race. Biologist looked at body structure and physical health of the horses, and named the probable winners. Statistician looked at outcomes of past races and named the probable winners. Then came physicist's turn. He was still busily writing and calculating. The rich man got impatient and asked, what is he doing. The physicist answered, "I am working on a model of spherical horses in a vacuum"... :)
I know it as "spehrical cow in a vacuum"
It turns out that physicists don't like being placed on a frictionless surface in a vacuum.
i love this guy. More of him please. Computerphile used to do videos on real world stuff like cross site scripting (tom scott is dope) and like more feet on the ground real world programming things, not so etherial. This guy is more in the weeds, which i like.
Get this genius a glass of water when you interview him next.
or make him a cup of tea.
@Tomasz
and of course make sure, if at all possible, that it's made by a safe AGI agent. And probably with no vases or children around, just for extra caution
He did, you can see it 14 seconds in
This video explained so much more than the title promised it would.
I just learned a lot. Thank you!
The guy writes on toilet paper sheets and all.. but then he rolls the dice, and out of nowhere, the dice turns green! We can see it's trajectory in slow-mo UNDER THE CUP! Blew my mind! Direct thumbs up!
Computerphile needs infinitely more theory/math videos.
That is what Numberphile channe is for
P.S.A.: There's an abridged version (from 131 pages down to 20) of the paper on logical induction. The link to it is given in the original article (see Description)
This is a topic I've thought about for a long time. I'm excited to learn the theory.
Sounds like you need a device to throw ink at the page, to bypass friction with the delivery device. ink-jet-pen?
was going to suggest laser pointer based pen but then checked up on how did laser printers actually work again.. turns out heat to transfer powder to paper is actually produced by the drum and, if I understood correctly, laser is basically drawing negative image to counteract an electrostatic charge to prevent the powder sticking to non-printed parts of the paper. TIL. probably (I'll likely forget again soon)
FYI here's a full lecture where one of the co-authors of the paper talks about it in more depth: watch?v=UOddW4cXS5Y
It's a great talk, I highly recommend watching it before trying to read the paper, which is quite technical.
"we're not going to get too far into it" (looks at the video length) -rrr-right
The paper is 131 pages
@@RobertMilesAI wow! I will check out the paper. Btw, I'm shaking right now :D I read superintelligence upon your advice and watched all your videos! Thank you, you're awesome!
Probably one of my favorite computerfile videos.
Rob Miles! My favorite presenter.
Amazing channel! Keep up the great work!
Little correction: The price of futures does not actually depend on the expected future price. It is only a function of the current price and interest rates. That is the case because the predicted future price of the good is already reflected in the current price. If you would predict the price to go up in the future, you could also buy the good now and sell it in the future. By "no arbitrage" assumption, the expected value of doing this and selling a futures contract must be the same. As such the price in a futures contract will just be the current price plus interest for the time period.
Doesn't that assume completely durable goods? Buying strawberries could be different than strawberry futures, because that option for arbitrage wouldn't be available.
Edit: not trying to dispute you, just asking a question
@@toast_recon The future contract is durable - that you'd buy the current contract and then sell it later. Of course, real strawberries do begin to decline immediately but they were already purchased months or years ago in a futures market.
Thanks Rob I enjoy listening to your explanations
It is now my life's goal to qualify all of my initial thoughts on solving a problem as "in a 'spherical chickens in a vacuum' sort of way"
Very happy to find this video!
The graphics were cool in this video
One way or another, I don't think the predicted jet fuel prices from last year are holding up right now ;)
Also, great video!
Just wanna say thanks for your videos, always look forward to them!
What's on that bookcase?
Sapiens - Yuval Noah Harari
Soonish - Zach Weinersmith
Run Program - Scott Meyer
This is so interesting, wish the video was a bit longer. I think he was about to talk about how the algorithm reacts to paradoxes
Very very interesting, great video! It is pure gold. Since the term is dropped multiple times, the rational choice theory has its limits. Individual entirely rational actions can lead in sum to irrational outcomes.
The Dutch invented shipping insurance. It's a Dutch Book because if you set the numbers right the sponsor makes a profit regardless - either the trades work or they claim it from the insurer. The original was 'I always win', not 'I always lose', but in probability that's kind of the same concept, just flipped.
I love it! Really fascinating.
Super interesting from a mathematical and computer scientist's point of view.
Problem I already see is that with those contracts people blow a bubble of unrealistic prices for real goods by gambling. That leads to increasing prices for food and other real and basic resources so that people who already have hardly enough for a living (in developing countries for example) have to pay even more just to survive.
Great video!
Very difficult topic to explain. Well done!
One technical correction. "Most" futures contracts (as in most kinds, not most contracts) actually settle. If you forget to close out your contract (purchase an offsetting contract), you could find yourself the proud owner of a tank car of orange juice. Joy! Now what?* Of course, the way out is to close out your contract before the settlement date.
* That's basically the evidence the SEC (CFTC?) used in their case against the Hunt brothers in 1980 -- they held their contracts (LOTS of them) to maturity.
Miles is so smart, it literally hurts me to listen with full attention for too long at a time.
This is exactly why some Bayesians say that no probability is without prior. The only way to deal with probabilities on this sort of level is to be very explicit about what you know and don't know when you model your current state of knowledge.
Love you Rob!
When you say probability theory doesn't include a framework for including beliefs, that may be true for traditional frequentist probably theory, but it is absolutely a big part of Bayesian probability theory.
For a *really* good treatment of Bayesian probability theory I'd highly recommend Jaynes' book "Probability Theory: The Logic of Science". He makes a big point of pointing out that probabilities should be treated as degrees of belief which absolutely depend on a person's knowledge and he lays out all the mathematics needed for "updating one's belief" when you get more information or discover something by analyzing it (like in your square root example). This rule is simply Bayes theorem.
I think you misinterpreted him. He wasn’t saying that probability theory doesn’t describe how to update one’s subjective probability based on new evidence (rather, he says the opposite, that it does. He is talking about Bayesian probability.), but that it doesn’t describe how to update one’s subjective probability over time based purely on one taking more time to reason out the logical implications of the things one already knows (or already thinks likely).
He says that most probability theory assumes “logical omniscience”. E.g. if X and Y are two statements that turn out to be logically equivalent, standard probability theory requires that P(X)=P(Y), but determining if two statements are equivalent takes time and computation, possibly very large amounts of it.
And if you haven’t had time to check yet, then it seems like your probabilities for X and Y have to have the potential to be different, even though X and Y might turn out to be logically equivalent.
This was really well explained!
22:00 Almost made me choke from laughing while eating...
I love Rob's tangents!
What a legend! He has Soonish on his bookshelf! AI isn't my area but this paper looks like a really interesting. Thanks for bringing it to my attention CP.
17:50 According to Gödel there might be statements which can't be proved or disproved in a finite amount of time. An example could be Riemann's hypothesis about the roots of his zeta function. So the confidence value would be 1 - but w/o provability.
Going into 2021, where are we at with this?
25:47 I'd point out that by "loads of money" you mean infinite money (as time approaches infinity). You can in fact make loads of money for very high but finite values of "loads", because this efficient trader is very slow. It does a lot of things "in a timely manner" based on a definition in the paper, but the definition of "timely manner" is not very timely.
For example, you could make a lot of money by buying a lot of "The thousandth digit of pi is 9" and selling a lot of shares for every other digit. You couldn't get *unboundedly* high amounts of money because the inductor would eventually learn that the thousandth digit is 9, but you could probably get a lot in the meantime because until it ends up figuring out you're right it'll value all of those at $0.10.
is there an implementation of explained algorithm?
I can not literally imagine that the computers we use are result of countless transitions and one of those transition is just pure mathematics.
Amazing ! Love it ! This concept is just super duper cool I'm so excited to read the paper now :3
Mathematician vs doubling cube: "Oh, powers of two".
Amazing video also estimates :D
just a question why do they always write on that dot matrix paper with green lines on it...I've never seen that paper before.
As a fan of MassEffect this explanation reminded me a LOT of how the Geth build a "Consensus" among them, and the more there are that communicate, the better they work.
Let's just hope we don't create something exactly similar and they exile us from the planet :D
Ngl getting exiled is the fifth best case scenario, and probably not happen
*Bringing the 'wisdom of markets' into AI research (and codifying it) intuitively seems like something that will be a game changer. It just makes sense, as it's how the world (and many natural systems within it) work.*
You're sort of looking at it backwards. Mathematics informs the structure and implementation of markets, as well as models of how they behave in the real world. Mathematics also informs computery stuff in exactly the same way. It's like saying "bringing Maxwell's equations into the structure of computers, the way it structures everything else, might just be a game changer." And what do you think people have been doing all along?
Look to the natural world instead. Things like evolutionary algorithms. Will they, in the end, be all that useful? I don't know but you'd be adding something to the algorithmist's toolbox that isn't already there.
There are not enough serious videos about computer intelligence
27 quality minutes!
20:00 I now understand why futures markets are a thing.
Do, would the AI become a Laplace's Demon if you let It to know more?
7:53 Time
10:10 Seeing part of the process eliminates some wrong answers.
17:20 Well-Calibrated
19:02 Prediction Markets
If you can't use 1 or 0 probability, then it's ensuring the logic will fail because of the Halting Problem, instead of having limiting "Renormalization" boundaries, (I guess that's the logical objective of calculating probabilities in the first place). Very interesting discussion, thank you.
class Task extends Goal {
// you have the robot inherit you're overall goals so that they don't obstruct those while pursuing specific task
}
Maxwell Jann // TODO: make AI a human
where is the video where he talks about - should and is as ways to describe what is and what we want - he was talking about always needing two shoulds in order to express a wish in order to state a logic construct for comeing up with that wish!?? would really like to watch that video again. got stuck with me
Can you do a video on honeypots, honeynets, and honeyfarms?
Maybe I’ll try to peek at that paper (my old brain is hurting already). But it seems to me that formal specifications and rational choice theory are good but limited; they only work to the extent of one’s understanding of the universe of discourse (even if you were logically omniscient). But it seems like the unaccounted for possibilities are a pretty serious concern in these cases - I guess I’m just restating the basic problem of induction. Which isn’t to say that it’s not useful to try and optimize what can be done re. what we do know and the limited resources available to process that knowledge (I am a card carrying Bayesian) just that a dose of humility re. any conclusions seems useful.
Whats hillarious about this is that instantly beeing able to process the stuff around you, is the semipossible superpower of sherlock holmes.
Had a brain freeze watching this. At one point my brain slammed the door and shouted through the letter box, come back Tomorrow.
Oooh, I see that copy of Iain M Banks' "Consider Phlebas" on the shelf... nice.
in the part about the gathering evidence and accumulating enough beliefs to narrow your probability down, I actually sort of see it like a -- imagine a hologram to be your understanding of the thing. you see the hologram by perceiving many images of it from many different angles, each helping you to formulate a better understanding of what is being shown (for me, probabilities are not really like numbers, but more like blurry images that slowly make more and more sense with time), so even if you perceive it from all angles, you can never really "see" the hologram for what it really is. the more angles I see of it, it'll create a sort of meta-logical understanding of what it really is which I can now apply to things of similar nature.
so, how do you notice things of similar nature? well, I guess you could recognise aspects of details of the thing, but I personally "feel" it, and then the similar aspects start to show themselves.
what I'm trying to say is, while watching this video, I'm realising that I perceive things a bit backwards. like he said, the probability theory assumes logical omniscience and so therefore, if the pattern is not understood, it cannot be recognised. the brilliance to my approach is actually the assumption that never is it possible to perceive the whole thing at once (omniscience), and so therefore a gradually sharper understanding of what's happening in the image, allows for that continual revelation of what the probability really is, that logical omniscience assumes.
So, like, hindsight.
Does having a bunch of algorithms trading their predictions on a market have any better or worse or different consequences than doing Bayesian inference on their validity?
Lem "Summa Technologiae" on shelf.
The none dogmatism property is interesting, nice word to use instead of agnosticism.
I guess that logical induction must be perfected before they continue developing self driving cars. There are so many variables in such a short amount of time that it will have for computations.
Robs hair is back!!!!!!!!!!!!1 YEAH!!!!!!!!!!!
I'm skeptical this approach works well in presence of randomness. Take a problem where a nondeterministic T machine is much faster than a regular one. Now consider betting on such a problem in presence of randomness. In such a case you can't have a condition about market not being beatable since someone could always get lucky and verify the answer.
Why there isn't transcriber?
what does this say about the nature of uncertainty, i mean is it an artifact of our ignorance, or is there something inherent in the physical processes that makes it so?
Isn't converging on a probability of 0 or 1 in contradiction to nondogmatism as it is essentially an approximation? To make an estimation of what an estimation is would seem to indicate an inaccuracy rather than an imprecision or a problem with applicability not application.
23:24 super cool if every trader would affect the system equally. Reality is that the ones who will bet more, will affect the price more, and if her/his prediction is off, then humanity's predictions is off.
Anyway, the video was great, thanks :)
Depends on your timeline length. Over a 30 year length, I'm not sure if that's true.
and that why u need to remember.......remember as much as u can anyway
Dutch was the term used for most germanic communities 100-300 years ago in the USA. This is still the case with the Pennsylvania Dutch, who in turn refer to all that is outside their community as "English".
Make a video on how to think in recursion
Do I understand correctly? The minds which are thinking towards AGI safety engineering are using the paradigm of neoliberal commodity markets as the mathematical instrument for ‘value alignment’ in a formal system of reason. i.e a google adwords algorithm trading cheap reasons instead of cheap adverts. What are the other predicates of this system that aren’t philosophically grounded in Classical economic theory?
I think it was a 3. Also, this video was really cool.
SUMMARY OF THE PAPER courtesy of CHATGPT
Here are some notes on the "Logical Induction" paper:
Introduction: The paper introduces the concept of Logical Induction as a new framework for reasoning about uncertain or unknown information.
Background: The authors provide a brief overview of traditional induction methods based on probabilities and their limitations.
Logical Induction Framework: The framework is described in detail, including its mathematical foundations and the rules for making predictions based on past observations.
Advantages of Logical Induction: The authors argue that Logical Induction provides several advantages over traditional induction methods, including greater accuracy and flexibility.
Applications: The authors discuss potential applications of Logical Induction in fields such as machine learning and artificial intelligence.
Conclusion: The paper concludes by summarizing the benefits of Logical Induction and its potential for advancing the field of reasoning about uncertain information.
---------------
HOW IS THE LOGICAL INDUCTION FRAMEWORK IN THE PAPER DIFFERENT FROM TRADITIONAL LOGICAL INDUCTION
---------------
The Logical Induction framework proposed in the paper is different from traditional logical induction in several ways.
Integration of Induction and Deduction: Traditional logical induction is based solely on logical deduction, while the Logical Induction framework proposed in the paper combines elements of both induction and deduction.
Mathematical Rules: The Logical Induction framework is based on a set of mathematical rules, which define how to make predictions based on past observations. This is different from traditional logical induction, which relies on formal logic and inference rules.
Flexibility: The Logical Induction framework is more flexible than traditional logical induction, as it allows for the incorporation of uncertain or unknown information into predictions.
Accuracy: The authors argue that Logical Induction provides a more accurate approach to induction compared to traditional methods, as it takes into account both the logical relationships between variables and the empirical evidence from past observations.
Overall, the Logical Induction framework in the paper represents a departure from traditional logical induction, offering a more comprehensive and flexible approach to reasoning about uncertain information.
I've never forgot about htis guy since the "difference between a difficult problem and a very difficult problem...".
This reminds me of TRON where the various programs compete against each other to see which one is fittest or something.
So you're making the Dunning-Kruger-Effect measurable :D
I have a problem with the probability relationships as presented, compare 13:30:
P(A), P(B), and P(A and B)
Try wearing Bluetooth headphones at max volume and listening to the ending without going deaf
Terence McKenna is back
Now I am a few percent less confident that artificial intelligence will necessarily be rational and predictable.
14:30 who thinks he was thinking about a 'dutch oven' joke around then? lol
Could this algorithm apply to algorithmic stable coins?
As a framework for producing safe AI (and I do not know how to code this) how about making the primary goal of the AI "minimize the impact of actions on the world in the process of achieving a task." This might make its utility more difficult to realize, but it should be safer. By "impact" I mean an increase of entropy. A human body is more organized than a smear on the floor (stepping on a baby to make tea). Converting a human body into crystalline forms of its constituents produces more entropy in the form of heat than leaving it alone.
Yeah, people have looked at these kind of information-theoretic impact metrics for AI Safety. I made a video about it a while ago. I think links don't work well in comments but just go to my channel and/or search for "Avoiding Negative Side Effects: Concrete Problems in AI Safety part 1" and "Empowerment: Concrete Problems in AI Safety part 2"
Thank you.
Thanks for another great video with one of my favorite "mad scientists" (no offence ;).
And I feel I have to add that I to prefer the "long form" where the expert is allowed take their own, sometimes meandering, way to expand and explain their topic, and You only "gently steer" with Your question.
Jolly good job Sir :)
Best regards.
Thank you for scaring me with a superabstract paper. If you are all fancy for AI, you should probably consider to learn about didactics in the first place.
No wonder paper is "superabstract". The problem they are tackling is superabstract.
check bayesian stuff thats also a good logical induction with uncertainty
awesome
1 and 0 are not really probabilities: when you try to convert them to fractions you get 1/infinity or 1/1. True certainty (or 1 in this case) isn't really a prediction or a relation to the real world any more, because there's literally no possible observation you could make which could change it, not even direct observation.
But which number was under the cup?
reasoning.... that thing that would be really nice if more people did do...
Apparently, after leaving Middle Earth, Mr Frodo Baggins took an interest in learning about IT and Artificial Intelligence.
LOL
you mean Terence McKenna