Accelerationism @ ZH

After outlining Deutsche Bank’s recent comprehensive denunciation of ECB monetary policy (aka financial crack-cocaine), Zero Hedge remarks modestly:

Why does all of this sound familiar? Oh yes, because we have been warning about all of this since the day the Fed launched QE, and we warned that there is no way such unorthodox policy ends well. Seven years later the chief economist of Europe’s biggest bank admits we were spot on. We expect many more strategists and economist to make comparable admissions, if they don’t already behind closed doors. […] On the other hand, “groupthink” as DB calls it, surrounding Draghi and the central planners is impenetrable, and sadly all of this will be ignored. Which is why the only real way this final bubble is resolved, is when it bursts. Which is also something we have said long ago: instead of fighting the central banks, just let them achieve their goals as fast as possible. […] Ultimately, it is now too late to change anything anyway, plus the economic, finacnial and social collapse will inevitably come, whether in one month or a decade. The best that those who are paying attention can do is prepare. As for everyone else… they can find comfort in their echo chambers which ignore the reality that their actions create.
(UF emphasis.)

Quotable (#167)

Sam Kriss on Left Accelerationism:

[Inventing the Future by Nick Srnicek and Alex Williams] consistently refers to its future not as communism, but “postcapitalism.” It’s a world without work, but also without the commons. “The theory of the Communists,” write Marx and Engels, “may be summed up in the single sentence: Abolition of private property.” But here, private property remains untouched. The productive apparatuses are to be fully automated, removing workers as much as possible from every stage of the production process: who, then, will own them? Who will own the commodities that these apparatuses produce? And if humanity is unburdened from the need to work and left to produce freely in the pursuit of its own self-expression, who will own that? Without anything to oppose bourgeois property, the result could be fully monstrous: a bloated, gluttonous ruling class engaged in limitless production, and recapturing any losses when the new peons come to spend their universal basic pittance. The propertied classes would fuse with an automaton that requires no human parts except for ownership to form a single apparatus; Utopia as a cyborg dictatorship.

This future has, in fact, already been described – it’s E.M. Forster’s 1909 science-fiction story The Machine Stops. Here, all of humanity lives in tiny cells within the body of the vast subterranean Machine. The Machine produces all their consumer goods, it provides them with anything they might want or need at a moment’s notice, it speaks to them, and allows them to speak to each other through video-messaging. People tend not to leave their cells; it’s not forbidden, but it’s certainly not encouraged. Full automation. Universal basic income. A networked society. In the end the Machine starts to slowly disintegrate. Billions die, and Forster, who had something of a reactionary streak, can only see this as a good thing. Who owns the Machine? The Machine does.

Quotable (#151)

Nvidia CEO Jen-Hsun Huang on recent advances in deep learning:

… The system basically learns by itself using a lot of data and computation. If you keep showing it pictures of an orange, it eventually figures out what an orange is—or a Chihuahua versus a Labrador versus a small pony. Amazing things happened in 2015: Microsoft and Google beat the best human at image recognition for the first time. Baidu beat humans in recognizing two languages. Microsoft and the China University of Technology and Science taught a computer network how to take an IQ test, and it scored better than a college postgraduate. … […] AI has been plodding along for 50 years in research. And all of a sudden last year something happened. This new way of doing AI called deep learning is so tractable, so understandable — a tool you can apply so that you can create one single network to be trained to learn multiple languages and animals and things. And that you and I and some data scientists and engineers can train it. Last year AI went from research concept to engineering application. And all these engineers at Facebook and Google and others are taking this deep learning concept with all these frameworks, which is basically another word for tools, and turning these ideas into things of practical use. And now you’re seeing all these Internet companies announcing these practical uses. All of the industries are just exploding. Two years ago we were talking to 100 companies interested in using deep learning. This year we’re supporting 3,500. We’re talking about medical imaging, financial services, advertising, energy discovery, automotive applications. In two years’ time there has been 35X growth.

Game Over

Go is done, as a side-effect of general machinic ‘beating humans at stuff’ capability:

“This is a really big result, it’s huge,” says Rémi Coulom, a programmer in Lille, France, who designed a commercial Go program called Crazy Stone. He had thought computer mastery of the game was a decade away.

The IBM chess computer Deep Blue, which famously beat grandmaster Garry Kasparov in 1997, was explicitly programmed to win at the game. But AlphaGo was not preprogrammed to play Go: rather, it learned using a general-purpose algorithm that allowed it to interpret the game’s patterns, in a similar way to how a DeepMind program learned to play 49 different arcade games.

This means that similar techniques could be applied to other AI domains that require recognition of complex patterns, long-term planning and decision-making, says Hassabis. “A lot of the things we’re trying to do in the world come under that rubric.”

UF emphasis (to celebrate one of the most unintentionally comedic sentences in the history of the earth).

We’re entering the mopping-up stage at this point.

Eliezer Yudkowsky is not amused.

The Wired story.

Divergence II

The 21st century is looking like a nightmare for egalitarians, according to UBS. The bank anticipates an “automation and connectivity” explosion on a scale amounting to a fourth industrial revolution, widening gaps within and between nations:

These changes will have very different effects on nations, businesses and individuals. Automation will continue to put downward pressure on the wages of the low skilled and is starting to impinge on the employment prospects of middle skilled workers. By contrast the potential returns to highly skilled and more adaptable workers are increasing. Among corporations, a wide range of traditional businesses – especially those that act as intermediaries – can be expected to suffer. Many labor-intensive firms should be able to boost profit margins as they substitute costly workers for cheaper robots or intelligent software. And a range of entirely new companies and sectors will spring into existence. For nations, the largest gains from the Fourth Industrial Revolution are likely to be captured by those with the most flexible economies, adding a further incentive for governments to trim red tape and barriers to business.

The default outcome benefits the capitalism-competent. The Guardian is among those concerned.

Left Accelerationism

The hard-core version from Peter Sunde:

I’m hoping Donald Trump wins this year’s election. For the reason that it will fuck up that country so much faster then if a less bad President wins. … Hopefully technology will give us robots that will take away all the jobs, which will cause like a massive worldwide unemployment; somewhat like 60 percent. People will be so unhappy. That would be great, because then you can finally see capitalism crashing so hard. There is going to be a lot of fear, lost blood, and lost lives to get to that point, but I think that’s the only positive thing I see, that we are going to have a total system collapse in the future. Hopefully as quick as possible. I would rather be 50 then be like 85 when the system is crashing.

Quotable (#122)

Nick Dyer Witheford (in conversation) on the variants of far Left politics under advanced capitalism:

… it’s clear that capitalism is creating potentials – not just technological, but organizational potentials – which could be adapted in a transformed manner to create a very different type of society. The evident example is the huge possibilities for freeing up time by automation of certain types of work. For me, the problem both with Paul [Mason]’s work, which I respect, and with the accelerationists, is there is a failure to acknowledge that the passage from the potential to the actualization of such communist possibilities involves crossing what William Morris describes as a “river of fire.” I don’t find in their work a great deal about that river of fire. I think it would be reasonable to assume there would be a period of massive and protracted social crisis that would attend the emergence of these new forms. And as we know from historical attempts in the 20th Century to cross that river of fire, a lot depends on what happens during that passage. So there is, if one could put it that way, a certain automatism about the prediction of the realization of a new order in both these schools, which we should be very careful about.

(What automation wants — be definition — is more of itself. There’s a name for that, and it isn’t ‘communism’.)

The abstract for this talk gives a sense of the diagnosis.