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: <a href="https://qz.com/851066/almost-all-the-10-million-jobs-created-since-2005-are-temporary/" rel="nofollow">https://qz.com/851066/almost-all-the-10-million-jobs-created...</a><p>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.
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.<p>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.<p>Chess and go don't drive innovation, they are just a side effect of real innovation.
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.<p>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.<p>Medical research has advanced a lot with the invention of CRISPR.<p>CS has grown a lot in AI and quantum computing...
This article is off in so many dimensions.<p>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.<p>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?"<p>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).
A simple solution would be for the government to fund more fundamental research.<p>Research results should be public goods.<p>It seems hard to encourage companies to do public research, as they have no short / middle term interest to do so
"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: <a href="https://www.theguardian.com/technology/2017/may/11/tech-innovation-silicon-valley-juicero" rel="nofollow">https://www.theguardian.com/technology/2017/may/11/tech-inno...</a>
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.<p>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.
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.<p>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.
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.
Join Leela Zero in trying to replicate AlphaGo Zero: <a href="https://github.com/gcp/leela-zero" rel="nofollow">https://github.com/gcp/leela-zero</a><p>It's estimated that AlphaGo Zero took about 1700 GPU years to train. We can only reach this number by having a distributed effort.<p>400k games has currently been submitted to the Leela Zero project: <a href="http://zero.sjeng.org/" rel="nofollow">http://zero.sjeng.org/</a> . It's still playing in amateur level. (AGZ had about 30m self-play training).
This article implies a positive corelation between technology, research and employment, which is unsubstantiated. Employment rate is a function of politics.
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?