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Is Google’s AI research about to implode?
- deleted 6y ago[deleted]
- jC6fhrfHRLM9b3 6y ago> Examples of lies and conspiracy theory parotted by GPT-3 How do you know they are lies? :)
- VEwmsBwroJ3Pza 6y ago> Examples of lies and conspiracy theory parotted by GPT-3 How do you know they are lies?
- nmfisher 6y agoSet aside the ethics issues for the moment, the criticism that Google is neglecting alternatives to neural networks is probably reasonably fair. But on the other hand, research labs or not, Google is still a commercial entity driven by a shorter term horizon than your average academic. Google Research has probably subconsciously drifted towards areas (or at least applications) that can tangibly benefit Google in the near future. Neural networks might not be The Answer (TM), but they can deliver results today, and there's still untapped potential. Speech recognition, search, speech synthesis - all core Google products - have all benefited from neural networks, not to mention the broader applications like protein folding for DeepMind. I'm hesitant to find fault in a corporate group that's doubling down on the stuff that's actually delivering results, even if it's probably not the path to AGI. I probably wouldn't be so lenient with OpenAI, because they are (were) purely a research outfit, openly committed to AGI.
- hankstenberg 6y agoIn my opinion it's Peter Naur who has found the key issues that keep AGI out of reach for us. Check out his Turing Award lecture. Too bad that it is the von-Neumann-architecture itself that is keeping us from reaching our goal, because it is still a crude emulator for information processing as it is really done. Like in nature.
- linspace 6y agoThank you for giving a constructive answer because quite frankly after reading the article my reply was going to be much more acid against the author, which in my mind has some kind of agenda. I'm always thinking that Google research is going to stagnate and yet they continue to show impressive results. So, yes, I would love to see something more original than yet another NN, but on the other hand... amazing.
- mantap 6y agoFeels like the author has an axe to grind. Research isn't about knowing all the answers or always being successful. Negative results are just as important as positive ones. Author does not even mention the recent protein folding result.
- DavidSumpter 6y agoI am the author. I think it is interesting with this "axe to grind" response (there was another above). I am an independent researcher, a professor at a University. And I have absolutely no reason to be disappointed with Google. My knowledge of this subject goes considerably deeper than I write in the article, but it is important to get the points across in an easy to follow manner. Thus I use certain literary devices. But I think it isn't fair to describe my opinion as a "axe to grind". I might (of course) be wrong, but there is agenda.
- DavidSumpter 6y agoHa ha *no agenda, I mean. ..... Maybe my subconscious has an agenda I don't know about :-)
- marcus_holmes 6y agoMaybe you subconsciously want Google's AI research to collapse? ;)
- KineticLensman 6y agoC.f. Sussman attains enlightenment [0] [0] http://www.catb.org/jargon/html/koans.html#id3141241 http://www.catb.org/jargon/html/koans.html#id3141241
- jfindley 6y agoI'm not certain that claiming deep knowledge of the subject and handwaving about literary devices is a terribly useful response when you write an article suggesting decline while completely ignoring a bunch of significant more recent developments. That's not a literary device, that's cherry-picking facts to support a preconceived conclusion. Paying more attention to other, more recent, developments might also have helped you avoid writing a paragraph where you talk about deepmind not being able to play games where it needs to perform multiple actions to obtain a reward - I think deepmind managing to beat professional starcraft players is clear evidence that this conclusion is questionable at best.
- im3w1l 6y agoSounds like the criticism is basically that Google's screwdriver can't be used to hammer in nails.
- DavidSumpter 6y agoMore like they are using a hammer to put screw in the wall. But close enough :-)
- the-dude 6y agoMy dad called this an American screwdriver.
- dealforager 6y agoNo. Every time someone makes a big stink about someone getting fired at one of the top tech companies, it is promptly followed by an article like this. A trillion dollar company that hires thousands of researchers and consistently produces some of the highest quality research with real results is not going to implode from one person being gone. Another pattern I've seen is someone leaving a company, followed by writing an article about how the company is doomed. Of course, the doom never arrives and the companies do even better. All of us are replaceable, from Bill Gates to Jeff Bezos to this researcher. This doesn't mean I agree with the firing, just saying that there is no implosion incoming.
- herodoturtle 6y agoHear hear. These clickbaity article titles are tiresome. Thanks for saying it like it is.
- DavidSumpter 6y agoPlease read the article. I address some of the issues raised. My point is that Gebru's firing is symptomatic of some deep problems Google are experiencing. Thank you.
- herodoturtle 6y agoI read the article. Doesn't change the fact that your chosen title is clickbaity. Even if you disclaim it in the article itself.
- DavidSumpter 6y agoIt is a valid criticism that the headline is clickbaity.
- Manifretto 6y agoI read the article and i'm not following the argument delivered at all. There is no real proof to this. I'm following and reading research @ google (stuff like this https://ai.googleblog.com/ https://ai.googleblog.com/ and other sources) for ages now and NOTHING indicates an 'implosion'. It is strong research with real and constant results. I have no idea why the autor would even consider using the word 'implode'. Its not rocket science that data is biased and it just will continue be researched and a solution will be found. For the single reason that biased systems in certain areas will not deliver the results you need to use it properly.
- kristianpaul 6y ago“ Is there hope for Google Brain? One glimmer can be found in the fact that most of the articles I cite here, criticising Google’s overall approach, are written by their own researchers. But the fact that they fired Gebru — the author of at least three of the most insightful articles ever produced by their research department and in modern AI as a whole — is deeply worrying. If the leaders who claim to be representing the majority of ‘Googlers’ can’t accept even the mildest of critiques from co-workers, then it does not bode well for the company’s innovation. The risk is that the ‘assumption free’ neural network proponents will double down on their own mistakes.”
- jrootabega 6y agoYeah, tech and AI is pretty unpopular and they'll probably have a hard time finding people who want to work there since the entire planet is now independently wealthy
- bjarneh 6y ago> For these types of games, the algorithms can’t learn because they require an understanding of the concept of ladders, ropes and keys. The underlying problem of AI is that we've taken something we don't really understand, and applied it. When something like that does not work - what can you really do?
- Manifretto 6y agoNo its not. Great that we taked about it :-)
- prof-dr-ir 6y agoAs the author admits, the headline is a clickbait question. Indeed, the article highlights some issues with AI research, in particular those which can lead to ethical problems when AI methods are implemented in consumer products. These are by now well-known and important issues and people should find a way to resolve them. Then, in its final paragraph, the article suddenly claims to have answered its title question in the affirmative! Am I alone in thinking that the issues, valid as they could be, do not obviously spell doom for the entire program?
- ramblerman 6y ago> is that the technical challenges lie in finding ways to organise and construct language and image datasets in a way that is as ‘neutral’ as possible I think part of the problem is that 'neutral' models dont exist. And framing it that way already loses half the battle. There is no such thing as a neutral perspective. It's like when you learn a language, people always say they want to lose their accent as if it's a process of reduction to some perfect median. When in truth the way to 'lose your accent' is to pick a model speaker you like and mimic theirs. Of course I do agree we should probably replace the current biased ones with better ones, but the 'neutral' goal irks me. When it is picking one bias for another.
- superbcarrot 6y ago> Is Google's AI research about to implode? No. (For reference see https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headlines https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...) Seriously though - even if the points in the article were true, none of them imply any kind of implosion or significant disruption in Google's research. > Maybe one day we will see the transition from Hinton (ways of representing complex data in a neural network) to Gebru (accountable representation of those data sets) in the same way as we see the transition from Newton to Einstein. This is so loaded and gives Gebru so much undeserved credit that it undermines that author's credibility.
- timkam 6y agoI don't think it's about whether Gebru "deserves" the credit, it's just a bad comparison on so many levels. Roughly like: "the transition from Ronaldo to Magnus Carlsen may be seen in the same way as we see the transition from Pelé to Lebron James". I also think it would be fair to speak in terms of communities and not of individuals, at least in modern science.
- slt2021 6y agocomparing Gebru to Hinton, wow... the woke crowd totally out of touch with reality
- activatedgeek 6y agoThe implosion argument in this article is solely ~based~ triggered by Google's botched handling of AI Ethics researchers. To argue that this will implode the complete AI organization seems like wild stretch. On a normal day, all the arguments padding the article would fall on deaf ears. So, the answer to the question is no. Instead, AI Ethics research will probably implode. AI research, probably no. For AI research to implode, major AI research leadership need to be seen leaving. And I am not talking about the corporate leadership but the research thought leadership whose sole purpose is to shield the junior/senior researchers from corporate BS (and who are themselves well-known researchers). Edit: It is perhaps be more appropriate to have said that the botched AI Ethics researchers handling solely triggered the article.
- ramblerman 6y ago> I don’t want to downplay the deep instutionalised sexism and racism that is at play in Gebru’s firing — that is there for all to see. Really, where is that to see. You weaken your whole case with this kind of casual reference to "oh and she was also a black women" so racism and sexism apply. Its a type of crying wolf that loses you more people in what is the potentially important issue at hand, her work at google. I really wish there would be repurcusions for this kind of casual libel, as it can be thrown in today's climate without a second thought.
- jmeister 6y agoIn older honor-based cultures, this type of accusation would lead to a duel. We need a modern equivalent.
- deleted 6y ago[deleted]
- anewaccount2021 6y agoA one-mile race. Most HN readers couldn't finish.
- tantalor 6y agoIt's tough to draw a straight line from "deep institution" (redundant?) to specific examples. It shows up more in background statistic than anecdotes. When we're focusing on N=1, I'd rather see concrete complaints (and no, internal forum posts do not count).
- giorgiop 6y agoNope
- eznzt 6y agoThat GPT-3 excerpt is just hilarious.
- make3 6y agothe stupid clickbait title take away all credibility from the article
- kruxigt 6y agoWhat other credibility does it have really?
- okintheory 6y agoAs a casual observer, I get the impression that Google's corporate attitude toward research on Ethical AI is fundamentally analogous to Exxon's view of climate research in the 80s (and since). Namely, that Google, correctly, views research in the area as potentially undermining key revenue sources in the short and mid term. It is sad, but unsurprising. Government funded research and regulators will most likely be the force driving AI to be more ethical -- if that's going to happen. That's what we see whenever corporate and public interests collide head on.
- okintheory 6y agoClearly overall AI research at Google is not imploding, so I thought it was more interesting to talk about Ethical AI.
- snicksnak 6y agoEvery time critics try to lump conspiracy theories, LGBT representation, and fake news together just to make a general point, it directly puts me off, I think that's mostly a cheap shot and lazy. I'm out of the loop on the whole Gebru situation, from what I know she was researching ethics wrt to AI, so I don't really get the whole "novel idea/work" part in the last paragraph. I often get the impression that such critics never see the rapid developments in AI as progress as long as they don't cover the topics they would like to see focussed. It will never be good enough and always a concern because of X.
- kruxigt 6y agoFuck you fucking libtards.
- ppod 6y agoThis article is correct about underspecification, but completely dodges the argument on language and understanding, drawing the hackneyed, shallow distinction between "pattern matching" and "understanding". How do you define understand? People just use the word "understand" to fill in for the magic stuff that they say humans can do but machines can't. They also sometimes use "symbolic reasoning" that way, but the best work on machine understanding and symbolic reason is done by DeepMind: https://arxiv.org/pdf/2102.03406.pdf https://arxiv.org/pdf/2102.03406.pdf The examples in the original article are about truth, not understanding, mainly because we don't have anything approaching a formal definition of 'understanding'. But, if anyone does, it is probably the deep learning community, where conferences in the last 3-4 years have had hundreds of papers working carefully to examine what is the nature and structure of the knowledge encoded in these kind of systems.
- villgax 6y agoThey better fucking release the model & weights of OCR from Firebase MLKit for Android & also make MLKit available for JS runtimes.
- deleted 6y ago[deleted]
- dhairya 6y agoThis article makes no sense to me. If the premise was will Google AI Ethics research implode, then yes. Removing key memembers of the team has affected the team morale and created a toxic environment for the remaining researchers. However, the post seems to imply that stifling the Stochastic Parrots paper is somehow proof that Google AI stifles innovative research that is critical to AI progress. This is a quite a weak claim even before looking at logic of the claims that get to that point. Google AI, Google Brain, and Deepmind are all different groups at Google with different mandates and research goals. While what's happening in the Ethical AI team is troubling, it's rather a large and unfounded leap that it'll affect research productivity for the other teams. Digging deeper the article is confusing and sometimes plain wrong on its assessment of AI research. Broadly the deep learning and RL approach to AI has been critiqued for its lack of semantic and symbolic understanding. These are not Google specific and the articles examples of this are terrible. The first example of limitations of AlphaZero on Montezuma's revenge is a bad example. The author implies that RL failed because it didn't understand ladders. But later approaches still solved this using by using stochastic exploration strategies and not introducing conceptual knowledge to the model as the article implies is the key limitation. On the language modelling, its weird the article cites GPT3 as problematic given that GPT3 was developed at OpenAI's research and not Google. Also GPT3 is pretrained using next word prediction which only consider left context and is far more limited that BERT which considers bi-directional context and produces richer word level embeddings. That being said the Stochastic Parrots paper does specially critique BERT. But it's not a new critique. Emily Bender, the other major co-author, is a computational linguist who has always been critical of deep learning approaches to NLP. Bender along with Gary Marcus and many others have called for AI that considers symbolic and linguistic knowledge and have been critical of purely data-driven deep learning approaches. Stochastic Parrots is not new in its critique of large language models, it just provides newer evidence specific to the current state of language model research. So I'm not sure how any of this is a signal that Google AI is imploding. The broader trends in AI is not just throw more compute and make bigger models. It just happens that large models works well for OpenAI and Google for specific problems. Google also has one of the largest knowledge graphs and there is open line of research that combines symbolic knowledge from KG with deep learning methods. There is also active research both at Google and elsewhere that aims to add more make current deep learning approach more "intelligent" by using linguistic and symbolic knowledge. I'm confused as to how Google AI research is imploding. Google PR attempting to censor Stochastic Parrots (which was still published) because of bad PR optics has nothing to do with active research questions elsewhere at Google Brain, Deepmind, and Google AI.
- tinyhouse 6y agoThe problem is that AI etichs research is an esetoric academic field that has little real value in indistry. I will explain. Take the famous paper the article mentions. I read the paper. It's full of nonsense. It talks about environmental costs of training huge models. Give me a break. Then the problem with the biased datasets. Yes, everyone knows if you train on racist text you gonna get a racist LM. AI researchers are not stupid. They don't need etichs research to figure this out. The paper even gives an example of an Arab guy who got arrested because the Israeli police used an MT system that made a mistake in translation. The problem is not AI, the problem is the stupidity of the Israeli police who didn't verify the translation before arresting someone (he got released of course). Image recognition is another issue AI etichs like to bring up. "A black man was falsy identified!!". But when Yann Lecun said it's a training data problem the AI etichs researchers exploded. "No! AI models are racist!!". Etc. Now, if you have to work with a biased dataset, then ethics/fairness research might have some value in guiding you on how to build more fair models. But in industry and esp companies like Google, cannot take chances and almost always resort to data as the solution.
- rwj 6y agoThe article is a good overview, but I don't think saying that Gebru was fired is accurate. This fact is commonly repeated, but I believe she resigned.
- siculars 6y agoInteresting thesis. Is it me or does the author compare Gebru to Einstein?
- karmasimida 6y agoGoogle AI would only implode when Google, or the corporate world finding that AI can't deliver the financial promise that was hyped. And it is happening regardless of the drama, from the perspective of job market.
- throwaway316943 6y agoNice try, but still a miss. Building assumptions into NN won’t work for anything complex like ladders and keys which according to this author are built in to human brains? Please. Yes, NN are still in their infancy but they are clearly foundational to general intelligence. They will probably require many additional discoveries about how they need to be connected and maybe even a few updates to the model of the neuron but they aren’t going away. Secondly, of course a language model is going to parrot back the data it is trained on, that’s a major goal ie given a giant dataset answer these questions. It’s also how a lot of casual human conversation works, we generally just parrot back things we’ve read or heard. The interesting parts are the new syntheses that human brains come up with but even those are standing on the shoulders of the dataset so to speak. You’ll never get a truly neutral view of the data, I don’t even know what such a thing would look like maybe just pure ignorance of the data could be considered neutral? Biases aka heuristics are a a core part of learned intelligence, they can of course be flawed or entirely incorrect for a given environment but they serve a purpose and you can’t do away with them or the ability to form them based on observed data. You can optimize them for specific goals but you can’t get by with just one.
- c-cube 6y ago> Please. Yes, NN are still in their infancy but they are clearly foundational to general intelligence. This calls for a big fat "citation needed". What we call neural networks have very little to do with actual neurons, so I fail to see how this is supposed to be "clear". And it's in its infancy since the sixties, really?
- aardvarkr 6y agoWhat about electric cars, since they've been around for 180 years? Is it wrong to say that EV tech is in its infancy? We're seeing significant innovation in electric vehicles and there's so much room for it to continue improving. Technology goes through periods of explosive innovation as well as periods of very little growth. NN's were dead until they weren't, and now they are having quite the renaissance ever since 2012. Currently they seem to be getting us closest to general intelligence and I'm excited to see where they go from here and if anything else comes along to supplant it's place on the throne.
- ro-mx 6y agoWait a minute. The conspiracy answers given by AI sounds like a confirmation of facts! (Text written by my own AI model)
- qwerty456127 6y agoI would say the QAnon example demonstrates how useful the model actually is. It has been fed some [false] knowledge and answered in perfect accordance with what it has been taught. Doesn't this mean it is can give useful answers to real questions if taught real (scientifically proven) facts?
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- PaulHoule 6y agoIt reminds me of the recent Paul Graham essay where he talked about discovering, in graduate school, that the "knowledge based" A.I. (e.g. SHRDLU) was a "fraud." Specifically: we could make small worlds in which syntax and semantics lined up (like the Zork parser) to seem like it understood natural language, but there was a point you couldn't go further. I think some graduate students now will be disillusioned by the claims being made for deep learning today for the same reason that those systems will quickly master the things they are good at and leave a residue of even more difficult problems for the 2050s and beyond.
- at_a_remove 6y agoAs I have said before, whenever someone talks about ethics and AI, I ask the question "Whose ethics? Ethics according to who?" It's a fantastic chance to export your viewpoint on the entire world when this ethical AI begins to underlay various services. For example, "Members of Group X are inferior/should die" being unethical while "Members of Group Y are inferior/should die" getting past the AI ethics is a great way to slide this past a ton of people. No need for argument, it just comes pre-censored on the commenting system. AI, as a field, is going to have to face a painful question: what if we get answers we do not like? I'm Irish enough by extraction, so I'll use it as a self-denigrating point ... what if AI found that the Irish, just by genetics, did actually tend toward alcoholism and drunkenness? Would we accept that, or would we say "No, that's wrong. Go back to the drawing board until we get the answers we want"? My guess is that we are going to look for the latter. AI is going to give us the answers we want, because that's how we are going to build it. AI won't be constrained by ethics so much as it will by the discovered truths we are unwilling to accept, whatever they may be. And that means there's a space for people with a thousand tiny axes to grind to be employed. It will be a chance to shape what "truth" in the Orwellian sense will mean.
- geodel 6y agoMay be "AI Ethics" research will be affected and I believe this is good thing. After reading David Graeber's Bullshit Jobs, He claims that administrative jobs in universities and managerial, duct tape IT jobs in industry as examples of it. Now it occurred to me that this AI ethics research is just one more example of proliferating bullshit job. Just recycle same idea and conclusions thousand times and you have years of research and hundreds of papers generated out of it. And a mutual admiration society of university departments, twitter fans and these type of researchers in tech companies keep everyone in high esteem as world leading authorities.
- g9yuayon 6y agoI'm not sure I get the logic of the article. Google AI Research is going to implode because we know what the current models can't do? I thought we do research precisely because we wanted to expand our boundary of out knowledge. That is, shouldn't a research institution implode if there is nothing to research? And why is Gebru relevant in this article? Does she do quality research, and the research results have to do with the claimed implode?