James Thompson on the lessons of AlphaGo for intelligence research:
Very interestingly, getting more computer power does not help AlphaGo all that much. Between the first match against the professional European Champion Fan Hui and then the test match against World Champion Lee Sedol, AlphaGo improved to a 99% win rate against the 6 month earlier version. Against the world champion Lee Sedol, AlphaGo played a divine move: a move with a human probability of only 1 in 1000, but a value move revealed 50 moves later to have been key to influencing power and territory in the centre of the board. (The team do not yet have techniques to show exactly why it made that move). Originally seen by commentators as a fat finger miss-click, it was the first indication of real creativity. Not a boring machine. […] The creative capabilities of the deep knowledge system is only one aspect of this incredible achievement. More impressive is the rate at which it learnt the game, going up the playing hierarchy from nothing, 1 rank a month, to world champion in 18 months, and is nowhere near asymptote yet. It does not require the computer power to compute 200 million positions a second that IBMs Deep Blue required to beat Kasparov. Talk about a mechanical Turk! AlphaGo needed to look at only 100,000 positions a second for a game that was one order of magnitude more complicated than chess. It becomes more human, comparatively, the more you find out about it, yet what it does now is not rigid and handcrafted, but flexible, creative, deep and real. …
And on an optimistic note:
What about us poor humans, of the squishy sort? Fan Hui found his defeat liberating, and it lifted his game. He has risen from 600th position to 300th position as a consequence of thinking about Go in a different way. Lee Sedol, at the very top of the mountain till he met AlphaGo, rated it the best experience of his life. The one game he won was based on a divine move of his own, another “less than 1 in 1000” moves. He will help overturn convention, and take the game to new heights. […] All the commentary on the Singularity is that when machines become brighter than us they will take over, reducing us to irrelevant stupidity. I doubt it. They will drive us to new heights.
Not at all convinced right now that Ex Machina isn’t the most darkly brilliant movie ever made.
Selmer Bringsjord, “computer scientist and chair of the Department of Cognitive Science at Rensselaer Polytechnic Institute” (source):
“We are heading into a black future, full of black boxes.”
That’s what the arrival of AI looks like from our side.
Andrea Castillo takes a look at Urbit:
Some developers are seeking to transcend our internet feudalism by minimizing the number of third parties one must patronize to participate in digital society. Open-source operating systems like Linux allow people to take more control over their own computers. Bitcoin substitutes trust in a single payment processor for trust in a cryptographically secure, peer-to-peer network. BitTorrent, similarly, allows individuals to share files using a distributed network that cannot be immediately shut down by targeting any one entity. And several new projects aim to extend this logic to personal computing more generally. There’s OpenBazaar, a distributed marketplace platform that wants to be the “Bitcoin of Amazon” — a censorship-resistant e-commerce protocol that empowers buyers and sellers to transact peacefully without a middleman. There’s the InterPlanetary File System, or IPFS, which would operate as a kind of BitTorrent for the World Wide Web. […] But there is only one project that aims to just start this whole networking thing completely from scratch. It’s an “operating function” called Urbit, and it is by far the most fascinating and bizarre of these attempts to reboot computing. …
Scott Aaronson (interviewed):
… after all the forbidding-sounding verbiage you read in popular books, quantum mechanics is astonishingly simple — once you take the physics out of it! In fact, QM isn’t even “physics” in the usual sense: it’s more like an operating system that the rest of physics runs on as application software. It’s a certain generalization of the laws of probability. It says nothing directly about electrons, photons, or anything like that. It just talks about lists of complex numbers called amplitudes: how these amplitudes change as a physical system evolves, and how to convert them into the probability of seeing this or that result when you measure the system. And everything you’ve ever heard about the “weirdness of the quantum world,” is simply different logical consequences of this one change to the rules of probability. This makes QM, as a subject, possibly more computer-science friendly than any other part of physics. In fact, even if our universe hadn’t been described by QM, I suspect theoretical computer scientists would’ve eventually needed to invent quantum computing anyway, just for internal mathematical reasons.
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.
‘Computers’ used to be humans. ‘Secretaries’ mostly still are. It’s hard to imagine this situation lasting many decades. Given the obvious potential of reliable machine secretarial assistance, for navigating increasingly complex, information and communication saturated lives, it’s a zone of innovation peculiarly suited to the emergence of an AI-based ‘killer app.’
From the Wired link:
As it stands today, Clara helps coordinate meetings — via email — and generally manages your online calendar. When you’re trying to set up a phone meeting with someone, you cc: Clara, and the tool arranges a time that works for everyone and mails calendar invites. You also can ask it to add a meeting to your calendar, something I did just minutes before writing this sentence. Diede van Lamoen, who juggles myriad phone meetings each week, chatting with people across the globe, has used the tool for a year, and he says it saves him enormous amounts of time. “It’s been a godsend,” he says. “I can outsource all the scheduling.”
Among the (many) residual qualifications, Clara still has a Turk-style back end. Nevertheless, prepping the market for these applications is going to pay off eventually. By the time they arrive, they’ll seem indispensable, and be digested even faster than smart phones.