Richard Feynman: Can Machines Think? 

Tq for uploading this sad lex😁 Appreciate it.

@Vendicar Kahn unfortunately I don't know but am interested so will follow this thread

Chomsky says that's like asking if submarines swim. You wanna call that swimming? Fine.

Very appreciated, tx. So strange to watch a (science) fiction ... from the future.

Heh, i saw a feynman video, immediate flytrap for my mind. and added bonus its you posting it. Thank you. Love your work. Have you looked into the impact of autocorrecting software for text, and how it may actually change the mind of the typist to better suit the corrector. If slow moving object suddenly is closer. Are you sure it was not like that maybe, a month ago. Or what was the median of language before auto correct? Is it better to choose a word suggested or spend more time manually typing your own "words" I think humanity is mistepping in this obscure observation. Auto corrected out of the correct voice that uniquely is you. And eventually the whole of all yous. We, or us if you like. I did not expect to be concerned about this. But I am.

More than anyone else?

Err.. car was already common that time. And many AI concepts were old, it is only popular now because recent tech is power enough to implement those theory, also partially due to marketing and buzzwords like (Machine learning AI Pro Plus xxx phone AI Blockchain) that make people think these are somehow new idea.

@@steveroger4570 There is actual footage of new york in the year he was born. If you are going to argue with that, I don't want to waste time refuting the rest of your comment.

Born: Richard Phillips Feynman, May 11, 1918, New York City, U.S.

zenmeister451 I see a few horse carriages in the photo you linked. Model T's mass production was only a few years prior to the year of his birth. So, yes, I would say horse/carriage was still prevalent at the time regardless of the photo you showed. By mid 20s I think would be the time cars take over horse carriages.

@@ripfire4 I never said that horses were not prevalent. That was not the point. I also said that in rural areas and other towns horses were still being used. I was just showing how prevalent cars were in New York at the time. The pic I sent shows a virtual sea of cars.

RU-vid: you're welcome.

@@stinger4712 Thanks RU-vid, very intelligent of you.

not intelligent yet @@d1dac0

He had no idea or experience of what intelligence is, but perhaps he does now; intelligence is to men (human beings) what flying is to bricks-they cannot experience it as-they-are; asleep-or just dreamers

Indeed, I've worked with AI and this is a point that I think escapes a lot of people. Intelligence, by its nature, is intrinsically flawed. Because to reason at higher and higher levels - which is a characteristic of intelligent thought - we're further and further abstracting away the fine details. Which is good on the one hand, of course, but it's also potentially bad. Because, as the saying reminds us, often "the Devil is in the details". Machines give perfect mathematical results. The more and more we make AI "human-like" in intelligence, the more mistakes it's going to make. And the crucial point is that this is intrinsic to what we're doing, not a failure of hardware or software. But an intrinsic failure of intelligence itself - to detect patterns, I must abstract. Through abstraction, I'm throwing away fine detail. But, you know: Chaos Theory. Fine detail is oftentimes crucial to accurate prediction and results. When the machine is asked to do maths, then it does so perfectly. But when the machine is asked to cast a value judgement over some patterns it's detected in inherently ambiguous language to predict the course of an inherently "fuzzy" real world out there... it'll start making mistakes. It will not be perfect anymore. As it's our great unique ability - and we love to flatter ourselves - humans often miss these subtleties of how our intelligence is a trade-off. "To err is to be human", as the saying goes. Well, I'd revise it to "to err is to be intelligent" and we must expect that the machines, in increasing their intelligence, will become... less trustworthy and reliable in their results. Don't get me wrong. Still incredibly valuable and to be pursued, and will be pursued to good and great effect. But just, you know, "manage your expectations".

@@klaxoncow I think he meant it as a joke about us recognizing computers showing intelligence by means of human laziness thanks to our design. Intelligence trying to use itself to scheme a more efficient or "lazy" way to do or not do something. Or as he put it, "If you want to create an intelligent machine you're going to get all kinds of crazy ways of avoiding labour." The weakness is our schemes to avoid work and its necessity is our relief. Side note, saying intelligence is intrinsically flawed seems like a gigantic philosophically arbitrary statement.

@@klaxoncow a dumb person isn't "more human" than a smart one. the humanlikeness of an ai isn't measured by its mistakes

@@jgunther3398 Yeah, I said nothing like what you're trying to abstract it down to, and I never made any reference to anyone or anything being "dumb" or "smart" whatsoever. But I thank you for providing demonstrative proof of what I was saying. Your intelligence has abstracted what you think I said and, unfortunately, lost much of the crucial "fine detail" in actually comprehending what I was really saying. Which has lead you to error, in characterising my position with a strawman. And, no, that's not because you're "dumb", it's actually because you have intelligence. An ability to abstract, summarise, pull the wheat from the chaff, etc. I mean, in this case, I'd challenge you've actually done it incorrectly. But it is a characteristic of intelligence itself that you could do it at all. As AI becomes more human-like, expect it to start failing similar cognitive hurdles as well.

From Brazil, the otherside of the world, just passing by to say that I am cheering and hoping you make it!

@@Pedro14ceara Thank you for the kind words

Asha kori apni ekhono lege achen, Bhai. Ei level er passion britha jaye na

If you keep doing what you love, and that progressively improves your abilities, persistence will eventually make you better than the conventional physicist. First, develop the discipline to improve step by step. Then step by step towards your dreams. This comment is two years old to me. How are things going?

Dude, don't give up! 👍😎👍

Great knowing you watch Lex Fridman channels

Fancy seeing you here.

THIS MATTERS🤣🤣

Not surprised to find you here as well bro!

You r everwhere on my youtube algo dude

That’s when you know someone is really smart. They can speak about complex things in simple language.

I have a Calculus prof at my University who teaches just like that. Best professor I ever had and damn near aced all 3 of my Calculus courses cause of him. Having a charismatic professor will literally change your life.

That’s part of his charm with his new york accent

Born and bred in Brooklyn!

It’s Colin Quinn.

At his time he already had thought about perverse instantiation. That's crazy

Last genius

There's this guy called Alan Turing, he talked about this in a paper in 1950

@@_yiannis Pretty sure everyone here knows who Alan Turing is lol, but yes, he broached this subject as well

people, still today, are poo pooing on AI, saying it will never do this and never do that. They never learn XD

@SteppenWolff100 Correct!

@SteppenWolff100 the interesting question though is why "most highscool and college students" dont see "finding hings out" as a pleasure. Are there really kids who are more curios than others? Maybe, but I'm sure almost everyone has something he is curios about. If, for example, you put one of the best artists at this time in front of the very same audience, would they listen to him with same interest as to Fenyman? I would like to believe that as soon as someone finds his passion, he is just as involved in learning new things as those students are in their respective field.

@SteppenWolff100 interesting insight from across the world. Thanks.

@Karan K why? Religion teaches nothing of how the world works.

@Karan K That's very nice. Except that none of them do. So there is that. But hey, why bother with facts when you have alternative facts?

I want that shirt.

Where can i buy that shirt

@@gokurocks9 he was actually the DUDE of all scientist 😎😎😎

This is pretty much how I picture him being all the time. If you haven’t read it yet you should check out his book “Surely You’re Joking, Mr. Feynman”. It’s an autobiographical look at his shenanigans and it’s hilarious and intriguing.

@@BrandonAdamPhotography I am actually a Feynman geek so those all actually read it quite inside out.. more liking for Feynman as a person as important as a scientist to me..

We could also interpret that as showing how little we put6 own effort into human evolution. E.g. when someone says: "This calamity is gonna happen in 40 years" and in 40 years that is what is happening, you could say that's an amazing prophecy, but you could also say that's a shameful example of humankind's folly.

A brilliant thinker

He wrote several books !

Minds like his are the ones that should be kept in the jars from Futurama.

@Bob You gotta stop being such a sports guy, man.

You’re assuming he’d want dinner with you. 😉

Steve Jobs isn't even in the same realm as Feynman.

@@mattjames4978 yes he would have dinner, he just couldn't stop talking

Yeah I was thinking it would be cool to see his reaction to today’s tech - vision processing and machine learning and AI. He’s be proud. But he pretty much predicts it all when he said “it’s really hard to come up with a problem that computers won’t ever solve”’

Or maybe he would be worried ;)

They already had found that back when he gave this lecture, it just took longer.

Putting my one dime to the idea. I think he would have laughed at the idea of using a black box called "Neural Network" to find patterns in a way that the person who built it didn't understand it himself. He seems to be the kind of person who likes well-defined things we understand more than the mess that deep learning is right now!

@@bigphatballllz The concept of a neural network was first described mathematically in 1873, Feynman for sure knew what they were.

There's actually a technique of explaining named after him ... "The Feynman Technique". The Feynman Technique is a method of learning or studying that was famously used by physicist Richard Feynman. Known for his ability to explain complex topics in simple, intuitive ways, Feynman created a method for learning that involves four basic steps: 1. **Choose a Concept**: Choose the concept or topic you want to understand and start studying it. Once you know what it is about, take a piece of paper and write the name of the concept at the top of the page. 2. **Teach it to a Child**: Write out an explanation of the concept on your page as if you were teaching it to a child. Not just any child, but a child who is old enough to understand basic terms and relationships, but is still a beginner in terms of the topic. Use simple language and avoid jargon. Make sure your explanation is so simple that even a child can understand it. 3. **Identify Gaps and Go Back to The Source Material**: When you pinpoint the areas where you struggle (where you forgot something important, weren't able to explain it, or simply have a shaky understanding), go back to the source material and re-learn it until you have a basic understanding. 4. **Review and Simplify (Optional)**: If you followed the first three steps and are able to explain the concept in simple terms, you’re done. If you want to be sure of your understanding, you can try to simplify your explanation even more or try to explain it to an actual child or a peer. The Feynman Technique exploits the fact that teaching is one of the most powerful ways to learn and solidify your understanding of a concept. By pretending to teach the concept to someone else, you can identify gaps in your understanding. And by simplifying the concept to the level of a child, you're forced to really understand the concept at a deeper level.

His perspective of looking at universe and life is beautiful

He said that if you can't explain a concept or idea simply you don't understand it. Isn't this a problem with many college and university professors?

Very high charisma to go with that knowledge

​@@Jeff-66interesting use of chat gpt for this summary

With the right definitions, it can.

​@@papesldjnsjkfjsn Ignorance is a bliss

@@kosmic2615 bruh im so sorry i read it "with the right definitions, *I* can"

Symphony? Yes it can: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-03xMIcYiB80.html

@@thelifeaquatica Is that hot garbage supposed to be the best AI can do?

Claude Shannon is one of the most underrated scientists in modern times. At Berkeley, 3 graduate classes were devoted to Shannon’s research at MIT alone on information theory

feynman gave a solid argument that jet engines will never be able to think 🙂

@@jgunther3398 😄😂Yes, exactly! And that, of course, was Shannon's point: If by "machine" we always mean something that has the same level of internal complexity and interactivity with its environment that a jet engine does, then, of course, a "machine" can never think.

"A machine" is not "50 machines."

@@HironikSpear47 cool

@@HironikSpear47 not the case.

@Karan K *You* are nothing but a JOKE.

because the machine is being programmed by humans.....just making it quicker to calculate only aspects covered. A machine can never invent only a man's inate ingenuity can....

Didn’t Steve Jobs say he payed attention to lazy workers cause they found the most efficient way to do things

areemeteek

New York accent lol

*DHOTS*

CHEAT AHHH !

I was wondering what this meant until he said it.

Hey, I’m doing physics here!

I wish I could hear him speak on GPT-3

Then again, in a different video he speaks about pseudoscience and non-verifiable statements. Machine Learning has A LOT of that. That part, I'm certain, he would not like.

Neural networks were used back in the 50's

Not sure he would have would love it. ML finds lots of correlations between things but can't explain them and sometimes the connections are not even related just strangely correlated. It can give hints at things but it can't explain anything without human judgement. Seeing that something has a co incidental relation without explanation isn't really science.

@@OffTheBeatenPath_ yes but they didn’t have the speed and computing power we have now. Computers were simply too slow back then to see the benefits which we are now discovering.

Don’t forget to also thank Feinman.

Right now we have 0, so we need about 10,000 more

Most of the best are on RU-vid 🙂

Teaching what ?

we need teachers with spines. He defines things clearly and in a no nonsense way, which is pretty much the antithesis of the level of discourse in 2020. Everything has to be obfuscated and twisted to fit political narratives now, and anyone that asks questions is a heretic to be burned at the stake

And yet if parents thoughts their children even more than they do today to be decent human beings the progress in one generation would be higher than 10,000 Feynman could do in hundred Generations. Or maybe not. Richard would know the answer :D

We likely have many people like that today, but the centralization of power of the US-capitalist-imperialist domination over global affairs conditions societal organization into fixating on fewer and fewer individuals, in part as an expression of fear-driven scarcity imposed, and so those few 'preachers' might still be an expression of the problem. If you want more people like that around, you have to realign attention and support onto the many others who are on that level and maybe even beyond because they didn't focus effort on self-promotion. (Selfishness tends to limit holistic intelligence. - Or in simpler terms as my teaching mantra: "Fear makes stupid.")

​@Dowlphwin show us on the doll where the US-capitalist-imperialists touched you. You're safe here.

Exactly! ;)

What things?

Provocative thesis: It's nothing special. 😉 Many people have made accurate predictions based on simply understanding the systems of fools. And that's just the people you know about because they compromised with the system. Imagine what realms of understanding people can reach if they don't make their enlightenment dependent on status quo support. ● The Buddha is revered, and so many people who are very revered to a large degree merely repeat what the Buddha said. ● Few people call Karl Marx a prophet. ... Maybe because he expected people to understand what he said instead of just worship it. But he basically explained what would happen, for certain, inevitably, and it's not that difficult to understand why, but it is hard to overcome a belief system that wants to deny that understanding in order to protect itself.

@@Dowlphin it is

Which pictures feature a bridge.

​@@Dowlphin hey man try to predict what will happen inthe future and you know intelligent he is

​@@DowlphinGo take a shower you filthy Brony. You aren't smart.

GANs: Now jack looks like Elon Musk.

@@psy_duck8221 lol

These neural networks run on GPUs that can run a large number of algorithms in parallel.

@@anteconfig5391 A large number of the same algorithm

@@anteconfig5391 Forget the GPUs, visual recognition can run on a Raspberry Pi.

How do you do strike-throughs?

Wait until you find out about t-shirts with pockets.

@@efisgpr what? is there such a thing???!!!!

@@efisgpr that has to be illegal

ew

@@lukejo7994 ok

One of the smartest men to ever live had trouble comprehending exponential progression... What hope do I have...

In fact generative models like GANs can be thought of doing some sort of "thinking" through backpropagation - the discriminator and the generator force each other to think in certain way

Dude, 8:15 the man was ahead of his time in all senses.

yeah but... I mean... not bad huh

AI cannot be a new species unless it is programmed to be. But I have doubts about that programming possibility in the real world out of any simulation. The reason for my doubt is well known: there is not possible silicon life in the universe. About that Feynman "lero lero" (Brazilian expression) of mechanical cheetah etc etc it reminds me an ancient dinner in the MIT when there we've found Asimov, Searle, Minsk who hastily discussed about future trends of AI issues. Minsk have came to be in almost an argument with Asimov due to the Asimovian perspective on the central aspect of (future) AI. It was a memorable dinner that could be labelled General Intelligence Could Be a Mechanical Chee-tah or Whatever? Searle is still alive. He knows why that title! LoL

@@DumbledoreMcCracken To correct you and preach further on your notion ;) - *You know about - ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-JM77aTk1XyI.html

Pardon me if I think I can infer from your comment, that it's necessary to define "think", to define "intelligence", before making any comparisons. It was an observation I had, as soon as I saw the title of this video-"How can we say that something thinks, without defining first what thinking is?"

Kurzweil doesn't talk about human emotion, just emotion. Many animals with brains, possibly all animals with brains, have emotion. Emotion might be a result of biological brain evolution, or it might be a fundamental component of any optimal solution for general intelligence.

@@theBaron0530 That was an interesting "thought".. How could you possibly define something that is 'first order' that literally defines the 'second order' problem space of linguistics for which you are referring to.. It's like the 'simulation' in totality trying to comprehensively define itself , when it lacks the means to 'look in', from outside itself >> because if it had the means to 'see' from outside then it would be "more than simulation" .. A system space, cannot define itself using only itself.. To think about thining, is a second order operation.. unless you have the ability to 'step outside' your thinking or have something else to reference off, than you cannot define 'thought'.. and if you did find somthing else to "reference off" (sorry about my shitty terminology) then that information is now a product of "your" thinking, therefore unable to define the totality of the system.. I, dunno.. maybe (??)

The machine will never know the real world - the weakest link will always be the human operators who will always be feeding it biased, incomplete data... AI is a myth. Computer programs are getting better at what we would like them to do, but "AI" is just a buzzword.

16:33 damn, even the bugs are the same 😂

What the computer is really recognizing is still completely different from what we recognize. It's more like, they SIMULATE pattern recognition.

​@Michael Lubin Yeah, but don't we as humans simulate pattern recognition ourselves as well? AI/neural networks are just able to run a much, MUCH larger number of simulations simultaneously from which to draw their concepts/conclusions much more quickly than the human brain in it's current state allows us the capacity to run? Isn't the human brain slowly built up through a person's lifetime in the same manner that a neural network is built via a machine learning model? I mean, like, isn't the whole of a human's experience basically logged and framed in our brains as what essentially is nothing more than some form of logic tree or SQL database or something to that effect? It's almost like the only difference between a human and an AI/neural network is in the hardware itself coupled alongside the underlying network architecture that is being built on said hardware over time?

Not true. You are fooled by hype.

@@ericamann2533 Can machines have emotions and morality ?

@@UTKARSHARJUNdefine emotions and morality.

Never be sorry for your english, you rather should ask for improvements!

Dude your English is in the top percentile, most natives would have serious trouble understanding what the fuck any of that meant lol. Besides that, yeah that is generally applicable to what he was saying.

@@GarrettX001 Thank you for your kindness. I am a Brazilian from a mix of different bloods German, Danish (strong) Oriental Jew (strong) Portuguese etc (all mixed) and despite the fact of different origins we basically only speak Portuguese. Recently I was really cogitatum (well, it is Latim: freely thinking about) to make a RU-vid bilingual channel of science in this country with Anglo Saxon (English spoken natives, Americans, British) partners but the fact is that my English is poor. I am still studying a lot. Some really good channel here in Portuguese idiom is very difficult but it is not impossible. There are, say, no more than reasonably good channels here. Maybe I could yield a kind of interview framework (only audio with slide show) channel casted with the bright English spoken scientists of the English spoken peoples of countries like it happens in the Event Horizon, I would guess. It is hard. Google translator doesn't solve many barriers, for instance, in math (yes, math is also spoken during lectures). Google also doesn't have equation search, say, using latex. Those types of educational handicaps and others (more common ones, like good local structure) are harder in countries like Brazil.

@Chaotic Amphibian what! That’s amazing! Do you have any stories?

​@Chaotic Amphibian for real .?

This is false. Feynman was dumb until he met his wife.

Lol maybe he matured late, wasn't he married at like 19 or 20

Only because we provide near unlimited training data with captcha's and the like.

it wasn't considered "impossible". He said it himself - it just takes too long with the computational capacity and memory we have at a time. Human can do this faster. Therefore teaching a machine to do it would be impractical. And he later said the same thing about weather prediction (not much different from facial recognition conceptually) - right now machines are slow; but will probably get a lot faster and will be able to account for more parameters, as technology evolves. This is where we are now today. We have increased our capacity, and we have the algorithms. As a result we see a rise of AI in many fields.

I think he'd be tickled that people are watching this lecture on their phones.

Computer learning is still just mashing database query results together into various outputs that still may or may NOT be the results we're after.. a computer still has absolutely no way of telling what data is important in the real world.

Yes, but you need to butcher the word machine first