[HN Gopher] Richard Sutton and Andrew Barto Win 2024 Turing Award
___________________________________________________________________
Richard Sutton and Andrew Barto Win 2024 Turing Award
Author : camlinke
Score : 502 points
Date : 2025-03-05 10:03 UTC (1 days ago)
(HTM) web link (awards.acm.org)
(TXT) w3m dump (awards.acm.org)
| rvz wrote:
| Absolutely well deserved.
| darosati wrote:
| Hear hear
| ofirpress wrote:
| Good time to re-read The Bitter Lesson:
| https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson...
| khaledh wrote:
| Indeed a bitter lesson. I once enjoyed encoding human knowledge
| into a computer because it gives me understanding of what's
| going on. Now everything is becoming a big black box that is
| hard to reason about. /sigh/
|
| Also, Moore's law has become a self-fulfilling prophecy. Now
| more than ever, AI is putting a lot of demand on computational
| power, to the point which drives chip makers to create
| specialized hardware for it. It's becoming a flywheel.
| anonzzzies wrote:
| I am still hoping AI progress will get to the point where the
| AI can eventually create AI's that are built up out of robust
| and provable logic which can be read and audited. Until that
| time, I wouldn't trust it for risky stuff. Unfortunately,
| it's not my choice and within a scarily short timespan, black
| boxes will make painfully wrong decisions about vital things
| that will ruin lives.
| tromp wrote:
| AI assisted theorem provers will go a bit in that
| direction. You may not know exactly how they managed to
| construct a proof, but you can examine that proof in detail
| and verify its correctness.
| anonzzzies wrote:
| Yes, I have a small team of (me being 1/3) doing formal
| verification in my company and we do this and it doesn't
| actually matter if how the AI got there; we can
| mathematically say it's correct which is what matters. We
| do (and did) program synthesis and proofs but this is all
| very far from doing anything serious at scale.
| InkCanon wrote:
| What kind of company needs formal verification? Real time
| systems?
| anonzzzies wrote:
| Real time / embedded / etc for money handling,
| healthcare, aviation/transport... And 'needs' is a loaded
| term; the biggest $ contributors to formal verification
| progress are blockchain companies these days while a lot
| of critical systems are badly written, outsourced things
| that barely have tests.
|
| My worst fear, which is happening because it works-ish,
| is vague/fuzzy systems _being_ the software because it 's
| so like humans and we don't have anything else. It's a
| terrible idea, but of course we are in a hurry.
| tasty_freeze wrote:
| Companies designing digital circuits use it all the time.
|
| Say you have a module written in VHDL or Verilog and it
| is passing regressions and everyone is happy. But as the
| author, you know the code is kind of a mess and you want
| to refactor the logic. Yes, you can make your edits and
| then run a few thousand directed tests and random
| regressions and hope that any error you might have made
| will be detected. Or you can use formal verification and
| prove that the two versions of your source code are
| functionally identical. And the kicker is it often takes
| minutes to formally prove it, vs hundreds to thousands of
| CPU hours to run a regression suite.
|
| At some point the source code is mapped from a RTL
| language to gates, and later those gates get mapped to a
| mask set. The software to do that is complex and can have
| bugs. The fix is to extract the netlist from the masks
| and then formally verify that the extracted netlist
| matches the original RTL source code.
|
| If your code has assertions (and it should), formal
| verification can be used to find counter examples that
| disprove the assertion.
|
| But there are limitations. Often logic is too complex and
| the proof is bounded: it can show that from some initial
| state no counter example can be found in, say, 18 cycles,
| but there might be a bug that takes at least 20 cycles to
| expose. Or it might find counter examples and you find it
| arises only in illegal situations, so you have to
| manually add constraints to tell it which input sequences
| are legal (which often requires modeling the behavior of
| the module, and that itself can have bugs...).
|
| The formal verifiers that I'm familiar with are really a
| collection of heuristic algorithms and a driver which
| tries various approaches for a certain amount of time
| before switching to a different algorithm to see if that
| one can crack the nut. Often, when a certain part of the
| design can be proven equivalent, it aids in making
| further progress, so it is an iterative thing, not a
| simple "try each one in turn". The frustrating thing is
| you can run formal on a module and it will prove there
| are no violations with a bounded depth of, say, 32
| cycles. A week later a new release of your formal tool
| comes out with bug fixes and enhancements. Great! And now
| that module might have a proof depth of 22 cycles, even
| though nothing changed in the design.
| optimalsolver wrote:
| >AI can eventually create AI's that are built up out of
| robust and provable logic
|
| That's the approach behind Max Tegmark and Steven
| Omohundro's "Provably Safe AGI":
|
| https://arxiv.org/abs/2309.01933
|
| https://www.youtube.com/watch?v=YhMwkk6uOK8
|
| However, there are issues. How do you even begin to
| formalize concepts like human well-being?
| anonzzzies wrote:
| > However there are issues. How do you even begin to
| formalize concepts like human well-being?
|
| Oh agreed! But with AI we might(!) have the luxury to
| create different types of brains; logically correct
| brains for space flight, building structures (or at least
| the calcuations), taxes, accounting, physics, math etc
| and brains with feelings for many other things. Have
| those cooperate.
|
| ps. thanks for the links!
| necovek wrote:
| The only problem is that "logical correctness" depends on
| the limits of human brain too: formal logic is based on
| the usual pre-accepted assumptions and definitions
| ("axioms").
|
| This is what I consider the limit of the human mind: we
| have to start with a few assumptions we can't "prove" to
| build even a formal logic system which we then use to
| build all the other provably correct systems, but we
| still add other axioms to make them work.
|
| It's hard for me to even think how AI can help with that.
| fuzztester wrote:
| Quis custodiet ipsos custodes?
|
| https://en.m.wikipedia.org/wiki/Quis_custodiet_ipsos_custod
| e...
|
| excerpt of the first few paragraphs, sorry about any wrong
| formatting, links becoming plain text, etc. just pasted it
| as is:
|
| Quis custodiet ipsos custodes? is a Latin phrase found in
| the Satires (Satire VI, lines 347-348), a work of the
| 1st-2nd century Roman poet Juvenal. It may be translated as
| "Who will guard the guards themselves?" or "Who will watch
| the watchmen?".
|
| The original context deals with the problem of ensuring
| marital fidelity, though the phrase is now commonly used
| more generally to refer to the problem of controlling the
| actions of persons in positions of power, an issue
| discussed by Plato in the Republic.[citation needed] It is
| not clear whether the phrase was written by Juvenal, or
| whether the passage in which it appears was interpolated
| into his works. Original context edit
|
| The phrase, as it is normally quoted in Latin, comes from
| the Satires of Juvenal, the 1st-2nd century Roman satirist.
| Although in its modern usage the phrase has wide-reaching
| applications to concepts such as tyrannical governments,
| uncontrollably oppressive dictatorships, and police or
| judicial corruption and overreach, in context within
| Juvenal's poem it refers to the impossibility of enforcing
| moral behaviour on women when the enforcers (custodes) are
| corruptible (Satire 6, 346-348):
|
| audio quid ueteres olim moneatis amici, "pone seram,
| cohibe." sed quis custodiet ipsos custodes? cauta est et ab
| illis incipit uxor.
|
| I hear always the admonishment of my friends: "Bolt her in,
| constrain her!" But who will watch the watchmen? The wife
| plans ahead and begins with them!
| gsf_emergency_2 wrote:
| Apologies for taking the phrase in a slightly farcical (&
| incurious ?) direction: Who will take
| custody of the custodians?
| amelius wrote:
| Well, take compiler optimization for example. You can allow
| your AI to use correctness-preserving transformations only.
| This will give you correct output no matter how weird the AI
| behaves.
|
| The downside is that you will sometimes not get the
| optimizations that you want. But, this is sort of already the
| case, even with human made optimization algorithms.
| cxr wrote:
| Canonical URL:
| <http://www.incompleteideas.net/IncIdeas/BitterLesson.html>
| kleiba wrote:
| This depends a little bit on what the goal of AI research is.
| If it is (and it might well be) to build machines that excel at
| tasks previously thought to be exclusively reserved to, or
| needing to involve, the human mind, then these bitter lessons
| are indeed worthwhile.
|
| But if you do AI research with the idea that by teaching
| machines how to do X, we might also be able to gain insight in
| how people do X, then ever more complex statistical setups will
| be of limited information.
|
| Note that I'm not taking either point of view here. I just want
| to point out that perhaps a more nuanced approach might be
| called for here.
| visarga wrote:
| > if you do AI research with the idea that by teaching
| machines how to do X, we might also be able to gain insight
| in how people do X, then ever more complex statistical setups
| will be of limited information
|
| At the very least we know consistent language and vision
| abilities don't require lived experience. That is huge in
| itself, it was unexpected.
| kleiba wrote:
| Is that true though given e.g. the hallucinations you
| regularly get from LLMs?
| probably_wrong wrote:
| > _At the very least we know consistent language and vision
| abilities don 't require lived experience._
|
| I don't think that's true. A good chunk of the progress
| done in the last years is driven by investing thousand of
| man-hours asking them "Our LLM failed at answering X. How
| would you answer this question?". So there's definitely
| some "lived experience by proxy" going on.
| crabbone wrote:
| I remember the article, and remember how badly it missed the
| point... The goal of writing a chess program that could beat a
| world champion wasn't to beat the world champion... the goal
| was to gain understanding into how anyone can play chess well.
| The victory in that match would've been equivalent to eg.
| drugging Kasparov prior to the match, or putting a gun to his
| head and telling him to lose: even cheaper and more effective.
| krallistic wrote:
| "The goal of Automated driving is not to drive automatically
| but to understand how anyone can drive well"...
|
| The goal of DeepBlue was to beat the human with a machine,
| nothing more.
|
| While the conquest of deeper understanding is used for a lot
| of research, most AI (read modern DL) research is not about
| understanding human intelligence, but automatic things we
| could not do before. (Understanding human intelligence is
| nowadays a different field)
| DavidPiper wrote:
| This describes Go AIs as a brute force strategy with no
| heuristics, which is false as far as I know. Go AIs don't
| search the entire sample space, they search based on their
| training data of previous human games.
| dfan wrote:
| The paragraph on Go AI looked accurate to me. Go AI research
| spent decades trying to incorporate human-written rules about
| tactics and strategy. None of that is used any more, although
| human knowledge is leveraged a bit in the strongest programs
| when choosing useful features to feed into the neural nets.
| (Strong) Go AIs are not trained on human games anymore.
| Indeed they don't search the entire sample space when they
| perform MCTS, but I don't see Sutton claiming that they do.
| signa11 wrote:
| > ... This describes Go AIs as a brute force strategy with no
| heuristics ...
|
| no, not really, from the paper
|
| >> Also important was the use of learning by self play to
| learn a value function (as it was in many other games and
| even in chess, although learning did not play a big role in
| the 1997 program that first beat a world champion). Learning
| by self play, and learning in general, is like search in that
| it enables massive computation to be brought to bear.
|
| important notion here is, imho "learning by self play".
| required heuristics emerge out of that. they are not
| _programmed_ in.
| HarHarVeryFunny wrote:
| First there was AlphaGo, which had learnt from human games,
| then further improved from self-play, then there was AlphaGo
| Zero which taught itself from scratch just by self-play, not
| using any human data at all.
|
| Game programs like AlphaGo and AlphaZero (chess) are all
| brute force at core - using MCTS (Monte Carlo Tree Search) to
| project all potential branching game continuations many moves
| ahead. Where the intelligence/heuristics comes to play is in
| pruning away unpromising branches from this expanding tree to
| keep the search space under control; this is done by using a
| board evaluation function to assess the strength of a given
| considered board position and assess if it is worth
| continuing to evaluate that potential line of play.
|
| In DeepBlue (old IBM "chess computer" that beat Kasparov) the
| board evalation function was hand written using human chess
| expertise. In modern neural-net based engines such as AlphaGo
| and AlphaZero, the board evaluation function is learnt -
| either from human games and/or from self-play, learning what
| positions lead to winning outcomes.
|
| So, not just brute force, but that (MCTS) is still the core
| of the algorithm.
| bubblyworld wrote:
| This a somewhat uninteresting matter of semantics, but I
| think brute force generally refers to exhaustive search.
| MCTS is not brute force for that very reason (the vast
| majority of branches are never searched at all).
| HarHarVeryFunny wrote:
| OK, but I think it's generally understood that exhaustive
| search is not feasible for games like Chess and Go, so
| when "brute force" is used in this context it means an
| emphasis on deep search and number of positions evaluated
| rather than the human approach where many orders of
| magnitude less positions are evaluated.
| bubblyworld wrote:
| I think that kind of erodes the meaning of the phrase. A
| typical MCTS run for alphazero would evaluate what, like
| 1024 rollouts? Maybe less? That's a drop in the ocean
| compared to the number of states available in chess. If
| you call that brute force then basically everything is.
|
| I've personally viewed well over a hundred thousand
| rollouts in my training as a chess bot =P
| visarga wrote:
| > Game programs like AlphaGo and AlphaZero (chess) are all
| brute force at core -
|
| What do you call 2500 years of human game play if not brute
| force? Cultural evolution took 300K years, quite a lot of
| resources if you ask me.
| beepbooptheory wrote:
| Either you missed an /s or I am very interested to hear
| you unpack this a little bit. If you are serious, it just
| turns "brute force" into a kind of empty signifier
| anyway.
|
| What do you call the attraction of bodies if not love?
| What is an insect if not a little human?
| HarHarVeryFunny wrote:
| That 2500 years of game play is reflected in chess theory
| and book openings, what you might consider as pre-
| training vs test time compute.
|
| A human grandmaster might calculate 20-ply ahead, but
| only for a very limited number of lines, unlike a
| computer engine that may evaluate millions of positions
| for each move.
|
| Pattern matching vs search (brute force) is a trade off
| in games like Chess and Go, and humans and MCTS-based
| engines are at opposite ends of the spectrum.
| perks_12 wrote:
| The Bitter Lesson seems to be generally accepted knowledge in
| the field. Wouldn't that make DeepSeek R1 even more of a
| breakthrough?
| currymj wrote:
| that was "bitter lesson" in action.
|
| for example there are clever ways of rewarding all the steps
| of a reasoning process to train a network to "think". but
| deepseek found these don't work as well as much simpler
| yes/no feedback on examples of reasoning.
| Buttons840 wrote:
| Oof. Imagine the bitter lesson classical NLP practitioners
| learned. That paper is as true today as ever.
| jdright wrote:
| > In computer vision, there has been a similar pattern. Early
| methods conceived of vision as searching for edges, or
| generalized cylinders, or in terms of SIFT features. But today
| all this is discarded.Modern deep-learning neural networks use
| only the notions of convolution and certain kinds of
| invariances, and perform much better.
|
| I was there, at that moment where pattern matching for vision
| started to die. That was not completely lost though, learning
| from that time is still useful on other places today.
| abdullahkhalids wrote:
| I was an undergrad interning in a computer vision lab in the
| early 2010s. During group meeting, someone presented a new
| paper that was using abstract machine learning like stuff to
| do vision. The prof was so visibly perturbed and agnostic. He
| could not believe that this approach was even a little bit
| viable, when it so clearly was.
|
| Best lesson for me - vowed never to be the person opposed to
| new approaches that work.
| kenjackson wrote:
| > Best lesson for me - vowed never to be the person opposed
| to new approaches that work.
|
| I think you'll be surprised at how hard that will be to do.
| The reason many people feel that way is because: (a)
| they've become an expert (often recognized) in the old
| approach. (b) They make significant money (or something
| else).
|
| At the end of the day, when a new approach greatly
| encroaches into your way of life -- you'll likely push
| back. Just think about the technology that you feel you
| derive the most benefit from today. And then think if
| tomorrow someone created something marginally better at its
| core task, but for which you no longer reap any of the
| rewards.
| abdullahkhalids wrote:
| Of course it is difficult, for precisely the reasons you
| indicate. It's one of those lifetime skills that you have
| to continuously polish, and if you fall behind it is
| incredibly hard to recover. But such skills are necessary
| for being a resilient person.
| blufish wrote:
| nice read and insightful
| PartiallyTyped wrote:
| This made my day! Well deserved!
| darkoob12 wrote:
| They should have given it to some physicists to make it even.
| porridgeraisin wrote:
| Their book "Introduction to Reinforcement Learning" is one of the
| most accessible texts in the AI/ML field, highly recommend
| reading it.
| barrenko wrote:
| I've tried descending down the RL branch, always seem way out
| of my depth with those formulas and star-this, star-that.
| porridgeraisin wrote:
| Yeah, the formalisations can be hard to crunch through
| (especially because of [1]). But this book in particular is
| quite well laid out. I'd suggest getting a math background on
| the (very) basics of "contraction mappings", as this is
| something the book kind of assumes you have the knowledge of.
|
| [1] There's a lot of confusing naming. For example, due to
| its historic ties with behavioural psychology, there are a
| bunch of things called "eligibility traces" and so on. Also,
| even more than the usual "obscurity through notation" seen in
| all of math and AI, early RL literature in particular has
| particularly bad notation. You'd see the same letter mean
| completely different things (sometimes even opposite!) in two
| different papers.
| zelphirkalt wrote:
| You mean "Reinforcement Learning: An Introduction"? Or did they
| write another one?
| porridgeraisin wrote:
| Yeah that one. Messed up the name.
| incognito124 wrote:
| What is your background? Unfortunately I did not find it very
| accessible.
| jxjnskkzxxhx wrote:
| That book is a joy. Strong recommend.
| ignoramous wrote:
| Congratulations to Prof Barto & Prof Sutton. I'm sure the late
| Harry Klopf is all smiles (:
|
| > _The ACM A.M. Turing Award, often referred to as the "Nobel
| Prize in Computing," carries a $1 million prize with financial
| support provided by Google, Inc._
|
| Good on Google, but there will be questions if their mere
| sponsorship in _any_ way influences the awards.
|
| If ACM wanted, could it not raise $1m prize money from non-
| profits/trusts without much hassle?
| j7ake wrote:
| Amazing that Sutton (American) chooses to live in Edmonton, AB
| rather than USA.
|
| Shows he has integrity and is not a careerist focused on prestige
| and money above all else.
| Philpax wrote:
| Keen is a fully remote outfit, so he can work wherever. It's
| pretty likely that his reputation would open that door for him
| no matter where he goes.
| j7ake wrote:
| At his level it is much more than just being able to do what
| he wants, it's about attracting resources and talent to
| accomplish his goals.
|
| From that perspective location still matters if you want to
| maximise impact
| tbrockman wrote:
| As someone who grew up in Edmonton, attended the U of A, and
| had the good fortune of receiving an incredible CS education at
| a discount price, I'm incredibly grateful for his (and the
| other amazing professors there) immense sacrifice.
|
| Great people and cheap cost of living, but man do I not miss
| the city turning into brown sludge every winter.
| jp57 wrote:
| He's been there since he left Bell Labs, in the mid 2000's, I
| think. The U of A is, or was, rich with Alberta oil sands money
| and willing to use it to fund "curiosity-driven research",
| which is pretty nice if you're willing to live where the
| temperatures go down to -40 in the winter.
| armSixtyFour wrote:
| https://nationalpost.com/news/canada/ai-guru-rich-sutton-dee...
|
| He gave up his US citizenship years ago but he explains some of
| the reasons why he left. I'll also say that the AI research
| coming out of Canada is pretty great as well so I think it
| makes sense to do research there.
| pklee wrote:
| Very well deserved !! Amazing contributions !!
| mark_l_watson wrote:
| Nice! Well deserved. They make both editions of their RL textbook
| available as a free to read PDF. I have been a paid AI
| practitioner since 1982, and I must admit that RL is one subject
| I personally struggle mastering, and the Sutton/Barto book, the
| Cousera series on RL taught by Professors White and White, etc.
| personally helped me: recommended!
|
| EDIT: the example programs for their book are available in Common
| Lisp and Python. http://incompleteideas.net/book/the-
| book-2nd.html
| zackkatz wrote:
| Very cool to see this! It turns out my wife and I bought Andy
| Barto's (and his wife's) house.
|
| During the process, there was a bidding war. They said "make your
| prime offer" so, knowing he was a mathematician, we made an offer
| that was a prime number :-)
|
| So neat to see him be recognized for his work.
| HPMOR wrote:
| This is a crazy story!! Hahaha wow. What was the prime number?
| dustfinger wrote:
| Ha haa, that is fantastic. You should have joked and said -
| "I'd like to keep things even between us, how about $2?"
| grumpopotamus wrote:
| > we made an offer that was a prime number
|
| $12345678910987654321?
| optimalsolver wrote:
| So 2025 really is the year of agents.
| jimbohn wrote:
| Well deserved, RL will only gain more importance as time goes on
| thanks to its (and neural nets) flexibility. The bitter lesson
| won't feel so bitter as we scale.
| byyoung3 wrote:
| they deserve it. definitely recommend their book
| nextworddev wrote:
| RL may prove to be the most important tech going fwd due to test
| time compute
| vicentwu wrote:
| Great!
| carabiner wrote:
| Wonder if he's still working in AGI with Carmack.
| cxie wrote:
| Huge congratulations to Andrew Barto and Richard Sutton on the
| well-deserved Turing Award! as a student, their textbook
| Reinforcement Learning: An Introduction was my gateway into the
| field. I still remembered that how Chapter 6 on 'Temporal
| Difference Learning' fundamentally reshaped the way I thought
| about sequential decision-making.
|
| a timeless classic that I still highly recommend reading today!
| vonneumannstan wrote:
| Good time to remind everyone that Sutton is a human successionist
| and doesn't care if humans all die. He is not to be trusted nor
| celebrated: https://www.youtube.com/watch?v=NgHFMolXs3U
| nycticorax wrote:
| This is so silly. Do you imagine temporal difference learning
| is some kind of human successionist plot?
| vonneumannstan wrote:
| The video is not about his technical work but rather his view
| that AI will or should take over the future.
| nycticorax wrote:
| But the Turing Award _is_ for his technical work.
| kalkin wrote:
| Sure, and his other views - in the scope of his
| professional expertise but also quite relevant to, uh,
| other humans - seem relevant in an HN thread about the
| Turing award. This place isn't exactly restricted to
| technical discussion of the details of RL algorithms, and
| it's pretty fair for humans to have views on whether we
| ought to be replaced.
|
| It's not just one Youtube video, it's a repeatedly
| expressed view:
|
| https://x.com/RichardSSutton/status/1575619655778983936
|
| Valuing technological advance for its own sake "beyond
| good and bad" is an admirably clear statement of how a
| lot of researchers operate, but that's the best I can say
| for it.
| nycticorax wrote:
| The statement I take issue with is that Sutton "is not to
| be celebrated or trusted". Which I can only interpret to
| mean that the speaker does not think that Sutton _should_
| be celebrated or trusted. (And they 've chosen to state
| it in a kind of pompous way.) Which I think is too strong
| on both counts. I (and apparently the ACM) think that
| Sutton should be celebrated for his technical
| accomplishments. Also, I think he probably can be trusted
| on a lot of technical matters. Should he be trusted on
| matters of whether there need to be safeguards on AI
| research imposed by the state? Maybe not, but those are
| only a subset of all the matters.
| Version467 wrote:
| Very disappointing. I do not understand how people earnestly
| defend the successionist view as a good future, but I thought
| he might at least give some interesting arguments.
|
| This talk isn't that. There are no substantive arguments for
| why we should embrace this future and his representation of the
| opposite side isn't in good faith either, instead he chose to
| present straw-man versions of them.
|
| He concludes with "A successful succession offers [...] the
| best hope for a long-term future for humanity. How this can
| possibly be true when ai succession necessarily includes
| replacement eludes me. He does mention transhumanism on a
| slide, but it seems extremely unlikely that he's actually
| talking about that and the whole succession spiel is just
| unfortunate wording.
| visarga wrote:
| > ai succession necessarily includes replacement
|
| How is AI going to make its own chips and energy? The supply
| chain for AI hardware is long an fragile. AGI will have an
| interest in maintaining peace for this reason.
|
| And why would it replace us, our thoughts are like food for
| AI. Our bodies are very efficient and mobile, biology will
| certainly be an option for AGI at some point.
| vonneumannstan wrote:
| Robotics is a software problem now, see the Tesla, Figure
| or Unitree humanoid bots. An AI can be totally embodied and
| humans will have little or no value as labor at all.
| hollerith wrote:
| >How is AI going to make its own chips and energy?
|
| OK, so do you support laws preventing chip manufacturers
| and energy providers from becoming reliant on AI?
| drcode wrote:
| > How is AI going to make its own chips and energy?
|
| Pay naive humans take care of those things while it has to,
| then disassemble the atoms in their human bodies into raw
| materials for robots/datacenters once that is no longer
| necessary
| visarga wrote:
| I think he is trying to take the positive side of what is
| probably an inetability.
| vonneumannstan wrote:
| Or we could just you know, not build the thing that will
| probably kill us all and at minimum will obsolete all our
| labor value.
| jedberg wrote:
| Given that strategy has never worked in the history of the
| world, it's probably a good time to figure out how we will
| put the right guardrails in place and how we will adjust to
| the new normal.
|
| If "we" don't build it, someone else will.
| textlapse wrote:
| The ACM award is for their professional academic achievements -
| this fetishism to dig into another person's personal life and
| find the most weird thing they said as the thing that paints
| over all of their life's achievements as evil must stop.
|
| It's silly and dangerous. Because you don't like thing A and
| they said/did thing A all of their lofty accomplishments get
| nullified by anyone. And worst of all internet gives your
| opinion the same weight as someone else (or the rest of us) who
| knows a lot about thing B that could change the world. From a
| strictly professional capacity.
|
| This works me up because this is what's dividing up people
| right now at a much larger scale.
|
| I wish you well.
| vonneumannstan wrote:
| >this fetishism to dig into another person's personal life
| and find the most weird thing they said as the thing that
| paints over all of their life's achievements as evil must
| stop.
|
| This has nothing to do with his professional life. He has
| made these comments in a professional capacity at an industry
| AI conference... The rest of your comment is a total non
| sequitur.
|
| >And worst of all internet gives your opinion the same weight
| as someone else (or the rest of us) who knows a lot about
| thing B that could change the world. From a strictly
| professional capacity.
|
| I've worked professionally in the ML field for 7 years so
| don't try some appeal to authority bs on me. Geoff Hinton,
| Yoshua Bengio, Demis Hassabis, Dario Amodei and countless
| other leaders in the field all recognize and highlight the
| possible dangers of this technology.
| tsunego wrote:
| > This has nothing to do with his professional life.
|
| you mean his personal life?
| vonneumannstan wrote:
| oops, yes.
| textlapse wrote:
| It just feels like a smear on his character: Imagine
| working on RL incrementally without any lofty goals or
| preconceived evil.
|
| I do agree that there is some level of inherent safety
| issues with such technologies - but look at atomic bomb vs
| fission reactors etc: history paves a way through
| positivity.
|
| Just because someone had an idea that eventually turned to
| have some evil branch off way further from the root idea
| doesn't mean they started with the evil idea in the first
| place or worse, someone else won't.
| hollerith wrote:
| People left careers in AI in the 1990s because they came
| to realize that the tech would probably eventually become
| dangerous. Many more (including the star student in my CS
| program in the 1980s) never started a career in AI for
| the same reason.
|
| Sutton and everyone else who has advanced the field
| deserve condemnation IMO, not awards.
| jffhn wrote:
| >the most weird thing they said
|
| Reminds me of a quote from Jean Cocteau, of which I could not
| find the exact words, but which roughly says that if the
| public knew what thoughts geniuses can have, it would be more
| terrified than admiring.
| kalkin wrote:
| > all of their lofty accomplishments get nullified by anyone
|
| I don't think it's a question of whether their achievements
| are nullified, but as you mention, how to weight the opinions
| of various people. Personally, I think both a Turing award
| for technical achievement and a view that humanity ought to
| be replaced are relevant in evaluating someone's opinions on
| AI policy, and we shouldn't forget the latter because of the
| former.
|
| (Also, this isn't about Sutton's personal life - that's a
| pretty bad strawman.)
| h8hawk wrote:
| By "view that humanity," do you mean alignment with the
| effective altruism cult?
|
| Repressive laws on open AI/models--giving elites total
| control in the name of safety?
|
| And this alternative perspective from the cult should
| disqualify someone from a Turing Award despite their
| achievements?
| kalkin wrote:
| No, a "view that humanity ought to be replaced" is
| Sutton's, not an EA view. I'm not quite sure how you read
| that otherwise, except that you seem very angry. I sure
| hope our alternatives are better than human extinction or
| total control by elites...
| ks2048 wrote:
| At least his Twitter profile no longer has the bitcoin-meme-
| red-eyes thing.
| 317070 wrote:
| Have you ever met Sutton? He is the most heart-warming, caring
| and passionate hippy I have ever met. He does not want all
| humans to die. The talk you link also doesn't support your
| claim. Perhaps I missed it, in that case, do leave a timestamp.
|
| In the talk, he says it will lead to an era of prosperity for
| humanity, however without humanity being in sole control of
| their destiny. His conclusion slide (at 12:33) literally has
| the bullet point "the best hope for a long-term future for
| humanity". That is opposite to you saying he "doesn't care if
| humans all die".
|
| If I plan for my succession, I don't hope nor expect my
| daughter will murder me. I'm hoping for a long retirement in
| good health after which I will quietly pass in my sleep,
| knowing I left her as well as I could in a symbiotic
| relationship with the universe.
| vonneumannstan wrote:
| Here's the difference, you are not personally building the
| device which will cause your demise and your succession. We
| as humanity ARE doing that and have agency to choose NOT to
| do that.
| smokel wrote:
| It is interesting that you bring this to the attention, but I
| don't see why we should not trust or celebrate someone if they
| have views that you don't agree with.
|
| Edit: especially since I think your implied claim that Sutton
| would actively want everyone to die seems very much unfounded.
| zoogeny wrote:
| > doesn't care if humans all die
|
| That seems to be a harsh and misleading framing of his
| position. My own reading is that he believes it is inevitable
| that humans will be replaced by transhumans. That seems more
| like wild sci-fi utopianism than ill-will. It doesn't seem like
| a reason to avoid celebrating his academic achievements.
| rhema wrote:
| I used their RL book for a course I taught. It's beautifully
| written and freely available
| (http://incompleteideas.net/book/the-book-2nd.html)! I kept
| getting distracted by the beautiful writing that I would miss the
| actual content.
| textlapse wrote:
| This is a long time coming. To see through an idea from start to
| finish and make this span an entire field instead of a sub
| chapter in a dynamic programming book.
|
| I wish a lot more games actually ended up using RL - the place
| where all of this started in the first place - would be really
| cool!
| jamesblonde wrote:
| Built a lot of my PhD on their work 20 years ago. It really stood
| the test of time.
| wegfawefgawefg wrote:
| These guys are great but unfortunately the ai sutton and barto
| book is really bad. You would do better with Grokking Machine
| Learning by trask, and then a couple months of implementing ml
| papers.
| Buttons840 wrote:
| I second this suggestion. Read Grokking Deep Reinforcement
| Learning before reading Sutton. Well, the Sutton book is free,
| so take a peak, but if the formulas scare you then read
| Grokking Deep Reinforcement Learning.
| 317070 wrote:
| These books are about different topics? Sutton and Barto is
| about Reinforcement learning, and the other book you mention by
| Trask is on Deep Learning?
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