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What AlphaGo Zero teaches us about what’s going wrong with innovation

147 points by bowyakka 9y ago

cdancette 9y ago
A simple solution would be for the government to fund more fundamental research. Research results should be public goods. It seems hard to encourage companies to do public research, as they have no short / middle term interest to do so
- eru 9y ago
  Companies have at least as much interest to do research as they have to do any other charitable activity. The private sector does plenty of charity. Not sure the government should be involved. Not because basic research ain't great---in an ideal world we'd all get ponies from the government---but because budgets are finite and there are other opportunities some of them with more definite benefits. (Like eg funding education, especially early education. Or perhaps just taxing less, etc.) One interesting thing to note is that in our world the American and British military funded some of the first computers. A clear example of government funded research. But---if the government wouldn't have paid for inventing computers for the militaries, IBM came up with computers only a few years later. (And in the counterfactual with less government expenditures, the private sector might have had more funds left over to build computers earlier?)
  - cdancette 9y ago
    I think charity improves their public image more than fundamental research, that will be known only by specialists. Moreover, they have large tax incentives for charitable activities (not sure if they have for research too) For the military computers, they had a clear interest in doing so, and the military keeps most of their research hidden, so I think it's not really comparable to public research
    - eru 9y ago
      I think it's relatively easy to set up a charity to do your basic research for you, and reap the tax benefits? (I'm not an American, and I assume you are talking about American tax system? Other countries are different.) Universities are notorious for spinning their basic research into good PR (and often overblown press releases), even if it would only be interesting to specialists normally. I think companies like Google (and earlier IBM) reap a lot of more specialised PR from their basic research: it helps with hiring to be seen as a cool company at the forefront of technology.
      - watwut 9y ago
        "I think it's relatively easy to set up a charity to do your basic research for you, and reap the tax benefits?" That would likely qualify as tax fraud.
        nine_k 9y ago
        This depends on what you do with the results. To qualify as a charity, such an org should probably make all the results public domain, instead of e.g. patenting them.
        eru 9y ago
        Yep. Lots of eg cancer research charities.
        fjsolwmv 9y ago
        IKEA does this. Their product design is done by a "charitable foundation"
    - pjc50 9y ago
      > large tax incentives for charitable activities People misunderstand how these work. You don't get money by giving away money. What happens is that the charity gets the money as if it were pre-tax, that's all. (Trying to get the money back into the company from the charity after you've got the tax break is fraud)
  - pjc50 9y ago
    > The private sector does plenty of charity Plenty? How would you quantify that? Certainly in the scientific area it's a tiny part of total funding. > in the counterfactual with less government expenditures In this counterfactual the Axis would have outspent the Allies and perhaps won the war.
    - eru 9y ago
      To avoid controversy, take the counterfactual were spending changes after the surrender. Also I'm talking about basic research funded by the government with no concrete short-term plan for its use. Applied research and development for identified military needs is a different beast. (And might or might not be good, but it's a different argument.)
  - ThomPete 9y ago
    They actually dont since a lit of fundamental research has no market application. Its knowledge for the sake of knowledge. Interval Tesearch cut their "to market realization" from 10 down to 3 years. Fundamental researchbis not the same as r&d. Countries and civilizations have an interest in those.
  - lottin 9y ago
    The problem is private companies generally being for-profit enterprises they tend to fund only those research projects that they believe will have a positive return for them. They also have a strong incentive to keep the products of their research secret and only divulge them when they discover a concrete application that is suitable to be patented. This is all very well, but it's not a socially optimal way to conduct research.
  - jamesrcole 9y ago
    > there are other opportunities some of them with more definite benefits I dispute the implication of this -- that there is less certain benefit from fundamental research. There's clear historical evidence that fundamental research has massive societal benefits. We wouldn't have our modern society without it. It's just that it can only be understood in "statistical terms". If you place bets on fundamental research then in the long term you get big payoffs. It's a bit like investing in the stock market. You can't predict the pay-off for any one particular bit of fundamental research, and its actual pay-off usually isn't obvious in the short-medium term. From the other direction, there's a lot of claimed definite benefits to more applied work that doesn't actually pan out. Just because it's easier to claim that there's some particular benefit to doing something doesn't mean that benefit actually exists.
  - s17n 9y ago
    Corporate charitable donations were under $19B in 2016. The NIH budget alone is about $27B per year. The idea that corporations would decide to replace federal funding for charitable reasons is absurd.
  - eli_gottlieb 9y ago
    >Not sure the government should be involved. Not because basic research ain't great---in an ideal world we'd all get ponies from the government---but because budgets are finite and there are other opportunities some of them with more definite benefits. Budgets are finite, but currently, the state leaves both money and economic legibility on the table. The simple system should be: if you build and commercialize technology based on a public research grant, the state owns the patent and can set a fixed licensing rate proportional to the amount of the original grant funding. The state then splits the royalties, with you the developer taking most of them, but some large portion poured back into public research budgets (including from money you make off the patent). As your patent term expires, it begins costing you progressively larger portions of royalties and revenues to renew it. Eventually, the knowledge you documented to get the patent becomes public domain, or the state basically takes all the revenue from renewed patents. This doesn't just make money for the public research system, it guarantees legible terms to prospective licensees and rules out patent trolling wholesale.
    - fjsolwmv 9y ago
      How about the government just taxes all income at some appropriate rate?
      - eli_gottlieb 9y ago
        Personally, I really think that fundamental R&D is too important to rely on Congressional or parliamentary largess. If we want to fund research, and hopefully we do, then I think we ought to fund it out of direct taxes on its own products, a direct economic contract that knowledge belongs to everyone.
- namlem 9y ago
  Government should fund more research, but that on its own is not a solution. The entire system of academic research is fundamentally broken and laden with perverse incentive structures.
purrcat259 9y ago
Currently giving 'Error establishing a database connection'
- cdancette 9y ago
  I can see the webpage
  - purrcat259 9y ago
    Yeah its up now. Hiccup over.
- tobyhinloopen 9y ago
  An article about AI revolution and we still having problems keeping a database alive. Isn't that a bit ironic?
  - vog 9y ago
    Even more ironic is using a database for static content at all. Right now, we (as a society/industry) are unable to deploy well-known best practices of 5 years ago: https://www.martinfowler.com/bliki/EditingPublishingSeparation.html https://www.martinfowler.com/bliki/EditingPublishingSeparati... (In software development, it is even worse. I can't find the source to cite, but the saying is along the lines of: The mainstream programming languages and paradigms are mostly at the state of research of the 1970s, and right now we are evolving towards the state of research of the 1980s.)
    - pault 9y ago
      Isn't that the case for all industries? How many of the battery technologies currently being researched will be commercially available in the next 10 years?
d--b 9y ago
Mmmh, I am not a specialist and I don't know the numbers, but it seems to me that fundamental research is not less active than it used to be. Physics made a lot of progress in materials (nano tech, weird polymers, and so on), in building batteries, in finding the higgs boson and gravitational waves, and I'm sure plenty of other fields. Medical research has advanced a lot with the invention of CRISPR. CS has grown a lot in AI and quantum computing...
- __s 9y ago
  Cryptography has also been progressing well. Same for various encoding formats; Opus is both better quality per bit & uses less CPU than Vorbis
  - tribler 9y ago
    > this matters because most basic research ends up being commercially useful eventually That is quite a positive view. As a university professor I see a lot of speculative work. It is presented as fundamental, but makes assumption which do not hold in the real world. Hence a lot is mostly ignored.
- wallflower 9y ago
  If you read the science fiction series "The Three-Body Problem" (highly recommended), it makes a very compelling argument that fundamental research is the most important investment in the future. For example, fusion drives, not traditional stored rocket propellant engines, will be necessary to navigate between planets and the outer solar system. Also, existing known behaviors/laws of physics aside, the book posits that colonization of other planets/stars in the universe requires achieving light speed travel (along with hibernation technology). However, the other argument the book series makes is that there needs to be a strong motivator to get all the countries and economies of the world to focus on fundamental research and applying it.
  - nine_k 9y ago
    The mother planet reaps no material benefits from colonizing another star. Those groups who colonize it get a world if their own. So interests of Earth governments are not aligned with star travel, and only marginally aligned with colonizing e.g. Mars. Those groups who want to ho there will have to do it themselves. (See Elon Musk.)
dandare 9y ago
This article implies a positive corelation between technology, research and employment, which is unsubstantiated. Employment rate is a function of politics.
- d--b 9y ago
  While I agree that the article is not very convincing, it's not far fetched that automating technologies may have an impact on employment rate. Self-driving trucks and cars are likely to completely change the job landscape, and truck drivers are not going to switch job overnight. But yes, you're right, politics play a big part, so do monetary policies, and culture (as in: it's more acceptable to be jobless in some cultures than in others).
dingo_bat 9y ago
I don't think there is a very sharp distinction between results oriented R&D and "basic research". In the article, IBM's deep blue is dismissed as a dead-end victory but apparently alphago is not? Why? They both seem identical to me in goals and research methodology. On a side note, I cannot wait for general super intelligence. It cannot come soon enough. I'm tired of being poor and stuck in a fucking rut, and contemplating my death in a few short decades.
- dagw 9y ago
  Why? They both seem identical to me in goals and research methodology. In theory taking the work done on AlphaGo (and more importantly AlphaGo Zero) and generalizing it to non-Go related problems should be a lot easier than taking the work done on deep blue and generalizing to non chess related problem.
  - alenmilk 9y ago
    Yes, AlpaGo Zero is mainly self taught. It means it learned to play through the game mechanics. There are no databases of moves or smart optimizations that are based on our understanding of go.
  - fjsolwmv 9y ago
    AlphaGo is an application of general tech, just like Deep Blue was an application of general tech.
- icc97 9y ago
  I think the point was that Deep Blue was using brute force, where as Alpha Go had taught itself and Alpha Go Zero has gone the full distance to require zero outside help. So Deep Blue wasn't such a big step in terms of General Artificial Intelligence because it was heavily dependent on the human optimisations and was just showing the power of number crunching rather than learning.
  - fjsolwmv 9y ago
    It's more of a continuum than that. Yes deep blue had more hand-tuning and custom-built structure. AlphaGo had less hand tuning and of course waaaay more brute Force on top.
payne92 9y ago
This article is off in so many dimensions. Fundamental research is not less active, but it's happening in different places (e.g. the Google Brain team). Find the most profitable companies and you'll find the research. And to suggest a computer Go player, taught in a few days, is a "marginal improvement" over decades of "AI research": as my kids say, "wut?" If anything, today's deep learning driven AI is a prime example of how fundamental research can work (neural networks were considered research "fringy" by many until about 10 years ago).
- nkurz 9y ago
  And to suggest a computer Go player, taught in a few days, is a "marginal improvement" over decades of "AI research": as my kids say, "wut?" Maybe I'm the one that has it backward, but I'm pretty sure that Harford would not agree with the statement that Alpha Go Zero is only a "marginal improvement". To the contrary, he says that Alpha Go is an "outlier", and uses it as an example of the sort of "speculative research" we should be doing more of: "Productivity and technological progress are lacklustre because the research behind AlphaGo Zero is not typical of the way we try to produce new ideas." Apparently he should have been clearer, but I took the article as a call for more real research of the type that produced Alpha Go, and fewer of the "pragmatic shortcuts" and "brute-force approaches that taught us little but played strong chess"
  - mannykannot 9y ago
    There seems to be a mismatch between the headline and the article itself. I see this quite often, and I think it is often due to headlines being written by editors, or even editorial assistants. The author's choice of examples, featuring a counter-example prominently, seems odd - perhaps it is to capitalize on the interest in AlphaGo Zero. The article is something of an anachronism, in that it would have worked better immediately after Deep Blue (or even after Watson/Jeopardy).
- jamesrcole 9y ago
  > Fundamental research is not less active, but it's happening in different places (e.g. the Google Brain team). Find the most profitable companies and you'll find the research. Aren't you contradicting yourself a bit there? If it's only/mainly the most profitable companies and the topics of interest to them, then that hardly indicates fundamental research is very active. There can't be that many fundamental research positions across those companies. (caveat: the article is currently unavailable "Error establishing a database connection" so i'm not entirely clear if it's just about fundamental research in AI areas or not).
timthelion 9y ago
It is strange to read this, remembering how Microsoft has been lambasted time and again for doing so many interesting things with Microsoft Research and hardly ever taking any of them to the product stage. Is Microsoft unique in it's too much R and not enough D approach?
- agumonkey 9y ago
  I feel Microsoft accelerated the D phase recently. F#, I remember some typed OS after Midori being mentionned.
- munin 9y ago
  MSR has been heavily prioritized onto doing products and commercialization, stimulated by a re-org. In my research area, there have been a number (more than ten) of high profile departures of researchers from MSR, frequently going back to academia, which is madness.
makomk 9y ago
The big question this fails to ask is: full employment of what kind? Recent research has found that nearly all of the net job growth is in "alternative work", meaning temporary jobs, contract workers, freelancers, etc: https://qz.com/851066/almost-all-the-10-million-jobs-created-since-2005-are-temporary/ https://qz.com/851066/almost-all-the-10-million-jobs-created... Now think about the kind of innovation that companies like Uber and Deliveroo represent. While ostensibly they might be tech companies, in reality their business models revolve around a workforce of contractors who lack employment benefits and job stability. Their innovation is primarily in making more people work for less and take on all the risk.
- jjaredsimpson 9y ago
  Criticism of the -- what I believe to be -- inevitable post-work post-scarcity economy is rooted in the false idea that employment provides meaning to those employed. But proclaiming the "Value of Work" is just arguing for the "Merits of Drudgery." I can't wait to not work ever again. The weak reply that, "doctors have valuable employment that gives them meaning," is completely beside the point. Doctors like helping people or the challenge of solving an ailment or they like the high status of being a doctor in society or the high pay. But they don't like paperwork, or interacting with insurance companies. Most work is like that. Low status, repetitive, boring, meaningless. Trading the best hours of the day of the best years of your youth is a terrible bargain, but persists because it is connected to survival and status. Break the connection and humanity prospers.
  - topmonk 9y ago
    When I think about UBI, I keep picturing a group of pidgeons fighting over pieces of bread. I don't see UBI as freedom. It shares a lot with slavery, in that someone else is feeding you, and therefore has control over you. What I hope for in the future is a fully independent machine that each person owns and is capable of caring for them, by providing food, shelter, etc. and is capable of building a clone of itself. In this way, you truly are free, having a machine which you own, and can shutdown and leave at anytime if you wish.
GuB-42 9y ago
Projects like DeepBlue and AlphaGo are not fundamental innovation nor research, they are just PR stunts that show the expertise of the company making them. TBH, winning a game of chess or go has little value in itself, except for the limited market of selling chess or go software. The reason they are doing that is mostly for publicity. IBM makes computers, and they show how good they are at it by having one beat top players at chess, and Google makes machine learning based products and they use AlphaGo to show how good they are at it. Chess and go don't drive innovation, they are just a side effect of real innovation.
- dsacco 9y ago
  While I understand your cynicism in the practical applicability of a chess or go-playing AI, I think you are significantly underestimating the theoretical innovations contributed to the field every time these models are substantially improved. Much of the work that goes into improving something like AlphaGo is cross-applicable and cross-pollinated to other research projects, and gradually trickles out into other domains with much more real-world impact.
  - JustFinishedBSG 9y ago
    > I think you are significantly underestimating the theoretical innovations contributed to the field every time these models are substantially improved. I think you are overestimating, there isn't a single interesting theoretical insight in AlphaGo's papers.
    - deleted 9y ago
      [deleted]
    - dsacco 9y ago
      Can you define what you mean by “theoretical insight”? It’s true that AlphaGo was built using previously existing techniques (supervised learning, large dataset for training, reinforcement learning and monte carlo tree search). But if you consider something to not be a breakthrough because it does not literally introduce a novel fundamental technique, you have a very narrow view of research (in my opinion). Here are a few points to consider: 1. The combination of the aforementioned techniques in AlphaGo was non-standard. Reinforcement learning bootstrapped supervised learning, before passing a value function to the monte carlo tree search. 2. AlphaGo represents a new achievement in solving perfect information games. The research team has moved on to Starcraft, which is not perfect information, but they didn’t try to tackle that before conquering a complex perfect knowledge game first. 3. AlphaGo’s research team improved upon the original AlphaGo with a novel algorithm for self-learning and mastering games using minimal policy improvement. The new AlphaGo Zero does not utilize human training data or supervised learning, and it was capable of defeating the original AlphaGo 100-0. Beyond self-play, I think that AlphaGo’s methodologies can generalize to combinatorial search problems even if they don’t generalize to broader domains like partially observed games or robotics.
nottorp 9y ago
I'm not current, so please enlighten me: Is "deep learning" just a new buzzword for neural networks, or is there something extra?
- lustig 9y ago
  Technically yes, most often it's about stacking more layers in neural networks, making them "deep". However, there is some merit to the new hype since stacking more layers worked way better than anyone previously working with neural networks and ML thought it would. But in theory you could generalize deep learning to other methods than neural networks, it's basically about creating way more complex models than those used in previous research and feeding them lots of data. Thereby assuming less about the problem and letting the model figure it out.
  - marcosdumay 9y ago
    > it's basically about creating way more complex models than those used in previous research and feeding them lots of data Those are instructions for over-fitting. Deep learning neural networks escape from this problem somehow, but it's not a given that other models would escape it too.
    - pps43 9y ago
      The traditional way to avoid overfitting is to reduce the number of independent variables, shrink coefficients towards zero, or otherwise limit the complexity of the model. With deep neural networks the approach is different. Instead of trying to find global maximum (which is too hard, and will also cause the model to be grossly overfit), the algorithm stops much earlier. Such "underfit" models seem to generalize much better.
    - alephnil 9y ago
      They mostly escape from that by using huge amount of data and massive computing resources. Deep learning was became feasible because of the huge amount of data companies like Facebook, Google, Apple and others has collected.
l3robot 9y ago
"It was a time when companies weren’t afraid to invest in basic science." No they were probably afraid, but they were forced to invest in science by states. AT&T did not decide to invest massively in science and risky projects like Unix, they were forced to. Please stop thinking companies are behind innovation. A great piece of article that demestify this myth: https://www.theguardian.com/technology/2017/may/11/tech-innovation-silicon-valley-juicero https://www.theguardian.com/technology/2017/may/11/tech-inno...
- choonway 9y ago
  The push came most likely from the pressures of the cold war. Now that it is long over, threats like Russia/Syria/ISIS/North Korea/China don't provide the same level of urgency to compete as before.
  - fjsolwmv 9y ago
    We are also past the era where someone like Shannon or Turing noodling on a sheet of paper could invent a war-changing idea.
- mannykannot 9y ago
  AT&T was forced by the government to invest massively in Unix? That does not fit with what I have heard about its origins, which was as a shoestring project of Ken Thompson, Dennis Richie, and a few other collaborators [1]. If anything, the government prevented AT&T from following up on the initial development, as part of its anti-trust measures that allowed AT&T a telephone monopoly while preventing it from expanding into computing and related technologies. The article you link to may describe the current state of affairs, but it does not properly characterize the state of affairs in the 1950s and beyond, when many major technology corporations had research laboratories. While their activities were nominally directed towards future products and profitability, in practice this was interpreted quite freely, leading to things like Unix, as well as scientific work. [1]http://www.catb.org/esr/writings/taoup/html/ch02s01.html http://www.catb.org/esr/writings/taoup/html/ch02s01.html
- s17n 9y ago
teabee89 9y ago
I highly recommend this talk "Greatness cannot be planned: the Myth of the Objective" by Kenneth Stanley: he created picbreeder.org (evolutionary art platform) and realized that if an interesting state is set as an objective, then it is extremely hard to reach it from the initial state with AI algorithms, because you need to move away sometimes a lot, from local optima.
- fjsolwmv 9y ago
  The notion of local optima is centuries older than the invention of the first .org
cosmic_ape 9y ago
Not only corporations abandon real fundamental research, but people like the the author of that blog start referencing things like AlphaGo as "fundamental research" comparable to Shannon's or Turing's work. AlphaGo is a good and necessary engineering, but the ideas are pretty old, and not especially illuminating. Start confusing it with fundamental research often enough, and people will start to believe it. And then, corporate managers, and academic research grants, and academic publishing venues, like conferences, will start expecting "fundamental research" to be like AlphaGo instead of actual fundamental research.
forgot-my-pw 9y ago
Join Leela Zero in trying to replicate AlphaGo Zero: https://github.com/gcp/leela-zero https://github.com/gcp/leela-zero It's estimated that AlphaGo Zero took about 1700 GPU years to train. We can only reach this number by having a distributed effort. 400k games has currently been submitted to the Leela Zero project: http://zero.sjeng.org/ http://zero.sjeng.org/ . It's still playing in amateur level. (AGZ had about 30m self-play training).

147 points by bowyakka 9y ago

A simple solution would be for the government to fund more fundamental research. Research results should be public goods. It seems hard to encourage companies to do public research, as they have no short / middle term interest to do so

eru 9y ago
Companies have at least as much interest to do research as they have to do any other charitable activity. The private sector does plenty of charity. Not sure the government should be involved. Not because basic research ain't great---in an ideal world we'd all get ponies from the government---but because budgets are finite and there are other opportunities some of them with more definite benefits. (Like eg funding education, especially early education. Or perhaps just taxing less, etc.) One interesting thing to note is that in our world the American and British military funded some of the first computers. A clear example of government funded research. But---if the government wouldn't have paid for inventing computers for the militaries, IBM came up with computers only a few years later. (And in the counterfactual with less government expenditures, the private sector might have had more funds left over to build computers earlier?)
- cdancette 9y ago
  I think charity improves their public image more than fundamental research, that will be known only by specialists. Moreover, they have large tax incentives for charitable activities (not sure if they have for research too) For the military computers, they had a clear interest in doing so, and the military keeps most of their research hidden, so I think it's not really comparable to public research
  - eru 9y ago
    I think it's relatively easy to set up a charity to do your basic research for you, and reap the tax benefits? (I'm not an American, and I assume you are talking about American tax system? Other countries are different.) Universities are notorious for spinning their basic research into good PR (and often overblown press releases), even if it would only be interesting to specialists normally. I think companies like Google (and earlier IBM) reap a lot of more specialised PR from their basic research: it helps with hiring to be seen as a cool company at the forefront of technology.
    - watwut 9y ago
      "I think it's relatively easy to set up a charity to do your basic research for you, and reap the tax benefits?" That would likely qualify as tax fraud.
      - nine_k 9y ago
        This depends on what you do with the results. To qualify as a charity, such an org should probably make all the results public domain, instead of e.g. patenting them.
        eru 9y ago
        Yep. Lots of eg cancer research charities.
      - fjsolwmv 9y ago
        IKEA does this. Their product design is done by a "charitable foundation"
  - pjc50 9y ago
    > large tax incentives for charitable activities People misunderstand how these work. You don't get money by giving away money. What happens is that the charity gets the money as if it were pre-tax, that's all. (Trying to get the money back into the company from the charity after you've got the tax break is fraud)
- pjc50 9y ago
  > The private sector does plenty of charity Plenty? How would you quantify that? Certainly in the scientific area it's a tiny part of total funding. > in the counterfactual with less government expenditures In this counterfactual the Axis would have outspent the Allies and perhaps won the war.
  - eru 9y ago
    To avoid controversy, take the counterfactual were spending changes after the surrender. Also I'm talking about basic research funded by the government with no concrete short-term plan for its use. Applied research and development for identified military needs is a different beast. (And might or might not be good, but it's a different argument.)
- ThomPete 9y ago
  They actually dont since a lit of fundamental research has no market application. Its knowledge for the sake of knowledge. Interval Tesearch cut their "to market realization" from 10 down to 3 years. Fundamental researchbis not the same as r&d. Countries and civilizations have an interest in those.
- lottin 9y ago
  The problem is private companies generally being for-profit enterprises they tend to fund only those research projects that they believe will have a positive return for them. They also have a strong incentive to keep the products of their research secret and only divulge them when they discover a concrete application that is suitable to be patented. This is all very well, but it's not a socially optimal way to conduct research.
- jamesrcole 9y ago
  > there are other opportunities some of them with more definite benefits I dispute the implication of this -- that there is less certain benefit from fundamental research. There's clear historical evidence that fundamental research has massive societal benefits. We wouldn't have our modern society without it. It's just that it can only be understood in "statistical terms". If you place bets on fundamental research then in the long term you get big payoffs. It's a bit like investing in the stock market. You can't predict the pay-off for any one particular bit of fundamental research, and its actual pay-off usually isn't obvious in the short-medium term. From the other direction, there's a lot of claimed definite benefits to more applied work that doesn't actually pan out. Just because it's easier to claim that there's some particular benefit to doing something doesn't mean that benefit actually exists.
- s17n 9y ago
  Corporate charitable donations were under $19B in 2016. The NIH budget alone is about $27B per year. The idea that corporations would decide to replace federal funding for charitable reasons is absurd.
- eli_gottlieb 9y ago
  >Not sure the government should be involved. Not because basic research ain't great---in an ideal world we'd all get ponies from the government---but because budgets are finite and there are other opportunities some of them with more definite benefits. Budgets are finite, but currently, the state leaves both money and economic legibility on the table. The simple system should be: if you build and commercialize technology based on a public research grant, the state owns the patent and can set a fixed licensing rate proportional to the amount of the original grant funding. The state then splits the royalties, with you the developer taking most of them, but some large portion poured back into public research budgets (including from money you make off the patent). As your patent term expires, it begins costing you progressively larger portions of royalties and revenues to renew it. Eventually, the knowledge you documented to get the patent becomes public domain, or the state basically takes all the revenue from renewed patents. This doesn't just make money for the public research system, it guarantees legible terms to prospective licensees and rules out patent trolling wholesale.
  - fjsolwmv 9y ago
    How about the government just taxes all income at some appropriate rate?
    - eli_gottlieb 9y ago
      Personally, I really think that fundamental R&D is too important to rely on Congressional or parliamentary largess. If we want to fund research, and hopefully we do, then I think we ought to fund it out of direct taxes on its own products, a direct economic contract that knowledge belongs to everyone.
namlem 9y ago
Government should fund more research, but that on its own is not a solution. The entire system of academic research is fundamentally broken and laden with perverse incentive structures.

purrcat259 9y ago

Currently giving 'Error establishing a database connection'

cdancette 9y ago
I can see the webpage
- purrcat259 9y ago
  Yeah its up now. Hiccup over.
tobyhinloopen 9y ago
An article about AI revolution and we still having problems keeping a database alive. Isn't that a bit ironic?
- vog 9y ago
  Even more ironic is using a database for static content at all. Right now, we (as a society/industry) are unable to deploy well-known best practices of 5 years ago: https://www.martinfowler.com/bliki/EditingPublishingSeparation.html https://www.martinfowler.com/bliki/EditingPublishingSeparati... (In software development, it is even worse. I can't find the source to cite, but the saying is along the lines of: The mainstream programming languages and paradigms are mostly at the state of research of the 1970s, and right now we are evolving towards the state of research of the 1980s.)
  - pault 9y ago
    Isn't that the case for all industries? How many of the battery technologies currently being researched will be commercially available in the next 10 years?

d--b 9y ago

Mmmh, I am not a specialist and I don't know the numbers, but it seems to me that fundamental research is not less active than it used to be. Physics made a lot of progress in materials (nano tech, weird polymers, and so on), in building batteries, in finding the higgs boson and gravitational waves, and I'm sure plenty of other fields. Medical research has advanced a lot with the invention of CRISPR. CS has grown a lot in AI and quantum computing...

__s 9y ago
Cryptography has also been progressing well. Same for various encoding formats; Opus is both better quality per bit & uses less CPU than Vorbis
- tribler 9y ago
  > this matters because most basic research ends up being commercially useful eventually That is quite a positive view. As a university professor I see a lot of speculative work. It is presented as fundamental, but makes assumption which do not hold in the real world. Hence a lot is mostly ignored.
wallflower 9y ago
If you read the science fiction series "The Three-Body Problem" (highly recommended), it makes a very compelling argument that fundamental research is the most important investment in the future. For example, fusion drives, not traditional stored rocket propellant engines, will be necessary to navigate between planets and the outer solar system. Also, existing known behaviors/laws of physics aside, the book posits that colonization of other planets/stars in the universe requires achieving light speed travel (along with hibernation technology). However, the other argument the book series makes is that there needs to be a strong motivator to get all the countries and economies of the world to focus on fundamental research and applying it.
- nine_k 9y ago
  The mother planet reaps no material benefits from colonizing another star. Those groups who colonize it get a world if their own. So interests of Earth governments are not aligned with star travel, and only marginally aligned with colonizing e.g. Mars. Those groups who want to ho there will have to do it themselves. (See Elon Musk.)

dandare 9y ago

This article implies a positive corelation between technology, research and employment, which is unsubstantiated. Employment rate is a function of politics.

d--b 9y ago
While I agree that the article is not very convincing, it's not far fetched that automating technologies may have an impact on employment rate. Self-driving trucks and cars are likely to completely change the job landscape, and truck drivers are not going to switch job overnight. But yes, you're right, politics play a big part, so do monetary policies, and culture (as in: it's more acceptable to be jobless in some cultures than in others).

dingo_bat 9y ago

I don't think there is a very sharp distinction between results oriented R&D and "basic research". In the article, IBM's deep blue is dismissed as a dead-end victory but apparently alphago is not? Why? They both seem identical to me in goals and research methodology. On a side note, I cannot wait for general super intelligence. It cannot come soon enough. I'm tired of being poor and stuck in a fucking rut, and contemplating my death in a few short decades.

dagw 9y ago
Why? They both seem identical to me in goals and research methodology. In theory taking the work done on AlphaGo (and more importantly AlphaGo Zero) and generalizing it to non-Go related problems should be a lot easier than taking the work done on deep blue and generalizing to non chess related problem.
- alenmilk 9y ago
  Yes, AlpaGo Zero is mainly self taught. It means it learned to play through the game mechanics. There are no databases of moves or smart optimizations that are based on our understanding of go.
- fjsolwmv 9y ago
  AlphaGo is an application of general tech, just like Deep Blue was an application of general tech.
icc97 9y ago
I think the point was that Deep Blue was using brute force, where as Alpha Go had taught itself and Alpha Go Zero has gone the full distance to require zero outside help. So Deep Blue wasn't such a big step in terms of General Artificial Intelligence because it was heavily dependent on the human optimisations and was just showing the power of number crunching rather than learning.
- fjsolwmv 9y ago
  It's more of a continuum than that. Yes deep blue had more hand-tuning and custom-built structure. AlphaGo had less hand tuning and of course waaaay more brute Force on top.

payne92 9y ago

This article is off in so many dimensions. Fundamental research is not less active, but it's happening in different places (e.g. the Google Brain team). Find the most profitable companies and you'll find the research. And to suggest a computer Go player, taught in a few days, is a "marginal improvement" over decades of "AI research": as my kids say, "wut?" If anything, today's deep learning driven AI is a prime example of how fundamental research can work (neural networks were considered research "fringy" by many until about 10 years ago).

nkurz 9y ago
And to suggest a computer Go player, taught in a few days, is a "marginal improvement" over decades of "AI research": as my kids say, "wut?" Maybe I'm the one that has it backward, but I'm pretty sure that Harford would not agree with the statement that Alpha Go Zero is only a "marginal improvement". To the contrary, he says that Alpha Go is an "outlier", and uses it as an example of the sort of "speculative research" we should be doing more of: "Productivity and technological progress are lacklustre because the research behind AlphaGo Zero is not typical of the way we try to produce new ideas." Apparently he should have been clearer, but I took the article as a call for more real research of the type that produced Alpha Go, and fewer of the "pragmatic shortcuts" and "brute-force approaches that taught us little but played strong chess"
- mannykannot 9y ago
  There seems to be a mismatch between the headline and the article itself. I see this quite often, and I think it is often due to headlines being written by editors, or even editorial assistants. The author's choice of examples, featuring a counter-example prominently, seems odd - perhaps it is to capitalize on the interest in AlphaGo Zero. The article is something of an anachronism, in that it would have worked better immediately after Deep Blue (or even after Watson/Jeopardy).
jamesrcole 9y ago
> Fundamental research is not less active, but it's happening in different places (e.g. the Google Brain team). Find the most profitable companies and you'll find the research. Aren't you contradicting yourself a bit there? If it's only/mainly the most profitable companies and the topics of interest to them, then that hardly indicates fundamental research is very active. There can't be that many fundamental research positions across those companies. (caveat: the article is currently unavailable "Error establishing a database connection" so i'm not entirely clear if it's just about fundamental research in AI areas or not).

timthelion 9y ago

It is strange to read this, remembering how Microsoft has been lambasted time and again for doing so many interesting things with Microsoft Research and hardly ever taking any of them to the product stage. Is Microsoft unique in it's too much R and not enough D approach?

agumonkey 9y ago
I feel Microsoft accelerated the D phase recently. F#, I remember some typed OS after Midori being mentionned.
munin 9y ago
MSR has been heavily prioritized onto doing products and commercialization, stimulated by a re-org. In my research area, there have been a number (more than ten) of high profile departures of researchers from MSR, frequently going back to academia, which is madness.

makomk 9y ago

The big question this fails to ask is: full employment of what kind? Recent research has found that nearly all of the net job growth is in "alternative work", meaning temporary jobs, contract workers, freelancers, etc: https://qz.com/851066/almost-all-the-10-million-jobs-created-since-2005-are-temporary/ https://qz.com/851066/almost-all-the-10-million-jobs-created... Now think about the kind of innovation that companies like Uber and Deliveroo represent. While ostensibly they might be tech companies, in reality their business models revolve around a workforce of contractors who lack employment benefits and job stability. Their innovation is primarily in making more people work for less and take on all the risk.

jjaredsimpson 9y ago
Criticism of the -- what I believe to be -- inevitable post-work post-scarcity economy is rooted in the false idea that employment provides meaning to those employed. But proclaiming the "Value of Work" is just arguing for the "Merits of Drudgery." I can't wait to not work ever again. The weak reply that, "doctors have valuable employment that gives them meaning," is completely beside the point. Doctors like helping people or the challenge of solving an ailment or they like the high status of being a doctor in society or the high pay. But they don't like paperwork, or interacting with insurance companies. Most work is like that. Low status, repetitive, boring, meaningless. Trading the best hours of the day of the best years of your youth is a terrible bargain, but persists because it is connected to survival and status. Break the connection and humanity prospers.
- topmonk 9y ago
  When I think about UBI, I keep picturing a group of pidgeons fighting over pieces of bread. I don't see UBI as freedom. It shares a lot with slavery, in that someone else is feeding you, and therefore has control over you. What I hope for in the future is a fully independent machine that each person owns and is capable of caring for them, by providing food, shelter, etc. and is capable of building a clone of itself. In this way, you truly are free, having a machine which you own, and can shutdown and leave at anytime if you wish.

GuB-42 9y ago

Projects like DeepBlue and AlphaGo are not fundamental innovation nor research, they are just PR stunts that show the expertise of the company making them. TBH, winning a game of chess or go has little value in itself, except for the limited market of selling chess or go software. The reason they are doing that is mostly for publicity. IBM makes computers, and they show how good they are at it by having one beat top players at chess, and Google makes machine learning based products and they use AlphaGo to show how good they are at it. Chess and go don't drive innovation, they are just a side effect of real innovation.

dsacco 9y ago
While I understand your cynicism in the practical applicability of a chess or go-playing AI, I think you are significantly underestimating the theoretical innovations contributed to the field every time these models are substantially improved. Much of the work that goes into improving something like AlphaGo is cross-applicable and cross-pollinated to other research projects, and gradually trickles out into other domains with much more real-world impact.
- JustFinishedBSG 9y ago
  > I think you are significantly underestimating the theoretical innovations contributed to the field every time these models are substantially improved. I think you are overestimating, there isn't a single interesting theoretical insight in AlphaGo's papers.
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  - dsacco 9y ago
    Can you define what you mean by “theoretical insight”? It’s true that AlphaGo was built using previously existing techniques (supervised learning, large dataset for training, reinforcement learning and monte carlo tree search). But if you consider something to not be a breakthrough because it does not literally introduce a novel fundamental technique, you have a very narrow view of research (in my opinion). Here are a few points to consider: 1. The combination of the aforementioned techniques in AlphaGo was non-standard. Reinforcement learning bootstrapped supervised learning, before passing a value function to the monte carlo tree search. 2. AlphaGo represents a new achievement in solving perfect information games. The research team has moved on to Starcraft, which is not perfect information, but they didn’t try to tackle that before conquering a complex perfect knowledge game first. 3. AlphaGo’s research team improved upon the original AlphaGo with a novel algorithm for self-learning and mastering games using minimal policy improvement. The new AlphaGo Zero does not utilize human training data or supervised learning, and it was capable of defeating the original AlphaGo 100-0. Beyond self-play, I think that AlphaGo’s methodologies can generalize to combinatorial search problems even if they don’t generalize to broader domains like partially observed games or robotics.

nottorp 9y ago

I'm not current, so please enlighten me: Is "deep learning" just a new buzzword for neural networks, or is there something extra?

lustig 9y ago
Technically yes, most often it's about stacking more layers in neural networks, making them "deep". However, there is some merit to the new hype since stacking more layers worked way better than anyone previously working with neural networks and ML thought it would. But in theory you could generalize deep learning to other methods than neural networks, it's basically about creating way more complex models than those used in previous research and feeding them lots of data. Thereby assuming less about the problem and letting the model figure it out.
- marcosdumay 9y ago
  > it's basically about creating way more complex models than those used in previous research and feeding them lots of data Those are instructions for over-fitting. Deep learning neural networks escape from this problem somehow, but it's not a given that other models would escape it too.
  - pps43 9y ago
    The traditional way to avoid overfitting is to reduce the number of independent variables, shrink coefficients towards zero, or otherwise limit the complexity of the model. With deep neural networks the approach is different. Instead of trying to find global maximum (which is too hard, and will also cause the model to be grossly overfit), the algorithm stops much earlier. Such "underfit" models seem to generalize much better.
  - alephnil 9y ago
    They mostly escape from that by using huge amount of data and massive computing resources. Deep learning was became feasible because of the huge amount of data companies like Facebook, Google, Apple and others has collected.

l3robot 9y ago

"It was a time when companies weren’t afraid to invest in basic science." No they were probably afraid, but they were forced to invest in science by states. AT&T did not decide to invest massively in science and risky projects like Unix, they were forced to. Please stop thinking companies are behind innovation. A great piece of article that demestify this myth: https://www.theguardian.com/technology/2017/may/11/tech-innovation-silicon-valley-juicero https://www.theguardian.com/technology/2017/may/11/tech-inno...

choonway 9y ago
The push came most likely from the pressures of the cold war. Now that it is long over, threats like Russia/Syria/ISIS/North Korea/China don't provide the same level of urgency to compete as before.
- fjsolwmv 9y ago
  We are also past the era where someone like Shannon or Turing noodling on a sheet of paper could invent a war-changing idea.
mannykannot 9y ago
AT&T was forced by the government to invest massively in Unix? That does not fit with what I have heard about its origins, which was as a shoestring project of Ken Thompson, Dennis Richie, and a few other collaborators [1]. If anything, the government prevented AT&T from following up on the initial development, as part of its anti-trust measures that allowed AT&T a telephone monopoly while preventing it from expanding into computing and related technologies. The article you link to may describe the current state of affairs, but it does not properly characterize the state of affairs in the 1950s and beyond, when many major technology corporations had research laboratories. While their activities were nominally directed towards future products and profitability, in practice this was interpreted quite freely, leading to things like Unix, as well as scientific work. [1]http://www.catb.org/esr/writings/taoup/html/ch02s01.html http://www.catb.org/esr/writings/taoup/html/ch02s01.html
s17n 9y ago

teabee89 9y ago

I highly recommend this talk "Greatness cannot be planned: the Myth of the Objective" by Kenneth Stanley: he created picbreeder.org (evolutionary art platform) and realized that if an interesting state is set as an objective, then it is extremely hard to reach it from the initial state with AI algorithms, because you need to move away sometimes a lot, from local optima.

fjsolwmv 9y ago
The notion of local optima is centuries older than the invention of the first .org

cosmic_ape 9y ago

Not only corporations abandon real fundamental research, but people like the the author of that blog start referencing things like AlphaGo as "fundamental research" comparable to Shannon's or Turing's work. AlphaGo is a good and necessary engineering, but the ideas are pretty old, and not especially illuminating. Start confusing it with fundamental research often enough, and people will start to believe it. And then, corporate managers, and academic research grants, and academic publishing venues, like conferences, will start expecting "fundamental research" to be like AlphaGo instead of actual fundamental research.

forgot-my-pw 9y ago

Join Leela Zero in trying to replicate AlphaGo Zero: https://github.com/gcp/leela-zero https://github.com/gcp/leela-zero It's estimated that AlphaGo Zero took about 1700 GPU years to train. We can only reach this number by having a distributed effort. 400k games has currently been submitted to the Leela Zero project: http://zero.sjeng.org/ http://zero.sjeng.org/ . It's still playing in amateur level. (AGZ had about 30m self-play training).