Vladimir Vapnik: Statistical Learning | Lex Fridman Podcast #5

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Title	:	Vladimir Vapnik: Statistical Learning \| Lex Fridman Podcast #5
Lasting	:	54.03
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I understand one thing from this conversation AI will not take over humans just because AI is missing intelligence
Comment from : @macromak4158

24:28
Comment from : @sarbajitg

125x
Comment from : @PhumlaniNxumalo

This is so good, wish there were more guests like the one in this vid nowadays too
Comment from : @goodlack9093

учащийся ПТУ разговаривает с учёным
Comment from : @urasigal9359

This is the most underrated interview I have ever come across It deserves MILLIONS of Views A genius who had a brilliant idea 30 years before he was appreciated
Comment from : @SassePhoto

Brilliant
Comment from : @JohanKarlsson

I CAN HYPOTHESISE EVEN THO GOD KNOWS ALL CONDITIONAL PROBABILITIES HE STILL NEEDS TO CONSIDER ALL THE OUTCOMES WITHOUT BIASWHICH IS IMPOSSIBLE FOR ANY OBSERVER
Comment from : @15997359

very wise man!
Comment from : @Arifi070

Couldn't grasp this one
Comment from : @nishanagarwal6068

What a brilliant mind !
Comment from : @Katharina643

Absolutely amazing video!
Comment from : @NoNTr1v1aL

Everything out of ramanujans mind came out of his intuition
Comment from : @hintergedankee

I wish Lex would've asked the meaning of life question to Mr Vapnik, that is always my favorite part of every pod Lex, round 2 please! Glad to know MrVapnik is still alive
Comment from : @GodofStories

The secret character of the podcast - the Duck
Comment from : @GodofStories

Invariance- 43:53 When mathematicians first created deep learning, they immediately recognized that they use way more training data than humans need How to decrease training data by 100x, and still have a high enough success> That is the real question of learning-intelligence - Vapnik
Comment from : @GodofStories

Fascinating Mr Vapnik's pure mathematics arguments are very much a sharp contrast, and welcome viewpoint on learning brbrMaybe a round 2 in many of your earlier pods, including MrVapnik here?
Comment from : @GodofStories

This is fascinating I had to pay more attention to appreciate the detail in MrVapnik's arguments I feel Lex was outmatched by just the pure mathematical arguments of MrVapnik, which is fairbrbr It would be hard for anyone who isn't a pure mathematician to contest him, and have a debate IT would be astonishing though to see a debate or discussion of mathematicians of this level Maybe Lex, can go into way more technical podcasts than the general, abstract, and cultural pods that he is doing more of these days Though, I still love he is still doing technical pods in various scientific topicsbrbrMaybe a round 2 in many of your earlier pods, including MrVapnik here?
Comment from : @GodofStories

Dear Mr Fridman, this is good video I am researching SVM and has a paper to introduce to you and Dr Vapnik Could you please let me know Dr Vapnik contact point? Thank you
Comment from : @slideai243

What?
Comment from : @charlesrump5771

This is a really good mental and hearing workout, his accent is really hard to listen to, but I like it
Comment from : @Dondlo46

What a spectacularly intelligent person A very different perspective than mainstream machine learning media
Comment from : @srh80

bdoes God play dice?/bbrbrGod is to our Universe what Gary gygax is to iDungeons & Dragons/ibrbrGod doesn't necessarily play with dice, but define what kinds of dice d6 d10 d20 etc should be the basis of his loose adventures that others play with under a DM who follows D&D rules which had an Intelligent Designer in Gary Gygax, There are other games which use dice, such as iMonopoly/i and therefore you can logically infer the existence of exouniverses that suppor alien life
Comment from : @____uncompetative

great work , thanks both
Comment from : @gorkhajankalyan29

Lex sound a bit nervious while interviewing Vapnik, although hard not to be in the face of him!
Comment from : @JoseAyerdis

Thanks a lot for the podcast , it was very interesting to listen
Comment from : @6pat

BACK UP IN THE INTRO HERE ALEXANDER
Comment from : @Andre_Foreman

Einstein discovered relativity from equations btw, he saw that time was not constant from those derived equations
Comment from : @g1org1dalaka1

Hi, what he meant by "predicate", please I google it but I found a different definitions
Comment from : @anas2k866

I think in 7:13 he says "residuals", not "details" (as in the subtitles) That's an important difference for the meaning of what he's saying
Comment from : @dljve

Based on the number of views this podcast with Vapnik is greatly underrated
Comment from : @teegnas

7:12 He said, "We are looking only residuals"
Comment from : @mehmetaliozer2403

For folks that are having a hard time understanding, Captioning the video should help
Comment from : @s25412

Спасибо, Лекс Очень интересно было послушать профессора Владимира Вапника
Comment from : @rashidskh

I love a lot of blah blah blah!! Great podcast!!!!
Comment from : @HooliganSadikson

The duck conversation was very intriguing and enjoyable
Comment from : @dynamicgecko1213

Wow! Incredible What an interview Like a series of Zen koans in mathematical form I especially loved Dr Vapnik's discussion of what a great teacher does Two questions: 1) as physics drives deeper into the nature of reality will we find that math is not just a model but can fully represent, ie is, reality; and 2) if other universes exist do they have the same mathematics? Thanks!
Comment from : @williamramseyer9121

Gg suggest moon sonata when i play this video Respect sir
Comment from : @alo1236546

Finding predicates is like learning disentangled representations: youtube/WYrvh50yu6s
Comment from : @tiberiusvetus9113

26:23 he is definitely right but we cannot wait 20 years for some brilliant mathematician to discover that In the meantime I think it is good to use DL which is not perfect but gets the job done
Comment from : @colouredlaundry1165

But there are no simple invariants for any complicated real-world classification task If there were, the machine learning would not be necessary We could just use straight computer code
Comment from : @RalphDratman

Mathematical explication of implicit invariants can be at least partially done for some senses and particular problems, in general sense encoding homeomorphisms But how to discover invariants when even a human observer doesn't see them or perceives incorrect invariants ))
Comment from : @javidq

The legendary Vapnik !!! Thank you Lex !
Comment from : @mlliarm

is Vladimir shitting all over deep learning? nice
Comment from : @theoracle666

25:56 Representer theorem says that optimal solution is on shallow networks, not on deep learning brbrbrbrI cannot understand why this holds Can sb explain or give me a reference?brThanks
Comment from : @manosangelis9826

Keep revisiting this and slowly understanding more This may be the best podcast on the channel
Comment from : @JohnGFisher

Wonderful Thank you
Comment from : @bornroller6603

Gold This is gold Very nice to hear others perspectives This guy is stubborn lol
Comment from : @williamscott1697

1 "I'm not sure that intelligence is just inside of us It may also be outside of us" br2 "I know for sure that you must know something more than digits"br3 Invariance theory might be the hope of understanding intelligence?
Comment from : @gavinlin6636

I understand some of what's being said here
Comment from : @1674-q4o

Think like Duck!
Comment from : @filmfranz

Thanks Lex, this talk was amazeballs!brAnyone got what the MIT guy's name was @52:27? brDodley? Or something
Comment from : @TennisNeedsMore

He shot down neural networks even for a hypothetical scenario, lol
Comment from : @GodsNode

NO IMAGINATION!!! lol
Comment from : @GodsNode

Those subtitles should probably "Weak and strong convergence" not "Big and strong "
Comment from : @torsteinsrnes4872

God Bless Vladmir Vapnik
Comment from : @SaveriusTianhui

Another interesting interview, but I think all of the interviews would be better with fewer leading questions and professing by the interviewer
Comment from : @bradleyedwards4604

is he saying @ 3:11 "setting" ?
Comment from : @channel-ug9gt

what is he saying at 1:35 ? "it is ???? described ", what is ???
Comment from : @channel-ug9gt

So in a way, the problem of intelligence or at least the basis regarding the concept of a good teacher hinges on metaphorical truth and linguistic precision
Comment from : @ilya1kravchenko468

I can't remember the time that I've really enjoyed a great conversation like this oneThese are good questions by Lex And I am so excited and thrilled by the intelligence of Vladimir Vapnik
Comment from : @kentthedev

Just another day I was thinking about "how come ideas are generated in different parts of the world within a definite time period simultaneously?" Glad to hear that a prominent mathematician thinks the same way (31:34) brIt's Platonic and poetic And I have heard many mathematicians say this sort of thing Ramanujan is also a great example that makes this theory interesting
Comment from : @itsalljustimages

This was incredible
Comment from : @JoshTechBytes

💖
Comment from : @jessicahardesty3358

Wow what an interesting conversation, thank you so much Lex for the video, really appreciate it and looking forward to more of such videos, cheers
Comment from : @qorod123

very interesting person
Comment from : @Kareem-hl8hj

Beauty and poetry! Again, thanks Lex!
Comment from : @sebastianavalos2055

I have to express my gratitude for uploading stuff like this, Thanks so much Lex and thanks to Dr Vapnik for taking the time to express some of the insights he has gained throughout his life
Comment from : @ung-k4c

haha I liked his response to the AlphaGo question!brbrOn the other hand, I think it's missleading Just like in maths, a problem's difficulty should be gauged by how hard it seems before solving it, not how hard it is in hinsight
Comment from : @GuillermoValleCosmos

I strongly disagree with Vapnik on his opinion about intuition He seems dogmatic in his dismissal of the idea, however, through history we have seen a number of human phenotypes that produce significant intellectual achievement One such phenotype that appears to be convergent in many individuals who have made tremendous achievements and cracked open entire academic disciplines (eg Einstein) is that of the visionary Someone who is able to intimately understand a problem so that they may sufficiently abstract it to allow for giant leaps of progress by using intuition or visualization rather than iterative logical steps I feel like Vapnik may be more of the literal, autistic type of individual who is very good at specializing and using brute force logic to iterate from axioms to a model within his discipline brI would not be too quick to discount the role of intuition particularly in the more demanding, technical fields such as pure mathematics and theoretical physics as opposed to machine learning and statistics
Comment from : @douglasholman6300

I am not sure if we can derive theory of inteligence purely from math In physics the problems are easier, because we can create meaningful equations, which can guide us The examples could be Max plank quantization of energy or Albert Einstein retativity theory or Dirac's anti particles or currently string theory brbrOn the other hand in biology, chemistry, there is less insight from equations For example effects of protein folding are very difficult to deduce from equations and we have to use computation instead The same could be with intelligence that it has mathematical description, but is very messy and does not adhere to our sense of mathematical beaty This could of course change as we find more connections and built consistant theory, so initially messy ideas become more and more intuitive and beautiful, but the core does not changebr brUsing beauty and elegance of math as heuristic is a little bit dangerous For example geocentric theory at the time had nicer description than heliocentric theory The reason was that we had to made more correction term to heliocentric theory to match the precision of geocentric theory It was, because they didn't use elipse to describe motion, but instead compositions of circular motions were used Only after emprical findings of Kepler we switched to elipsesbrbrAnother more anecdotal example would be the dynamo theory of WALTER M ELSÄSSER describing why plantes have magnetic fields He told his theory to Albert Einstein, but “he didn’t much believe it He simply could not believe that something so beautiful could have such a complicated explanation" in words of Einsten assistan (Einstein prefered not to tell his opinion) The theory was correct, Einstein's intuition was wrong (Source: top of 3rd page of pdf -> wwwgeosocietyorg/documents/gsa/memorials/v24/Elsasser-WMpdf) brbrAlso currently string theory is getting some backlash, because of lack of results despite decade long effort This theory has some promising connections and seems to be a perfect fit for missing element in our understanding of physics, but there are also some ugly parts, like need for more dimensions or too many possible universesbrbrSo we have to be carefull to not be too much focused on mathematical beauty, nature can just be messy or we might not have a mathematical tools to appreciate it's beauty
Comment from : @FlyingOctopus0

Ground Truths guide us all <3
Comment from : @AbhijeetSaxenaIN

His comment about music is similar to the ideas in GEB!
Comment from : @Quarky_

really interesting conversation, thank you!
Comment from : @koozdra

With each interview, I'm getting more interested in the subject Thank you for the great content!
Comment from : @martisl

Thank you for uploading such a beautiful interview! I enjoyed this video so much!
Comment from : @3145mimosa

I can't help but wonder if professor Vapnik could have expressed his thoughts a bit better if the interview was done in Russian
Comment from : @343clement

amlbookcom/ helped me understand his discussion on "expressiveness or diversity of functions" and the VC dimension "Learning from Data" book
Comment from : @cppmsg

Great stuff, thought the editing somewhat breaks the flow Why not put the whole conversation as is? I like the stutters and misunderstanding of questions type conversation :-) There is something there as well
Comment from : @jigarkdoshi888

Great conversation! But I beg to differ with Vladimir Vapnik on the role of imagination in discoveries Imagination and human intuition plays an active role in extending the existing laws and axioms, and to construct theories to fit observations What he had worked on might not have required imagination and intuition, but when it comes to theorizing and extending the existing laws, or the language of mathematics itself (or physics) human intuition and imagination will be essentialbrbrEvery sub-domain people specialize in will have its own unique demands
Comment from : @sreramk1494