Funkciigita de Guardian.co.uk#?I tiu artikolo titolis “Artefarita inteligento: kiom lerta ni volas niajn maŝinojn esti?” Estis skribita de Alex Hern, por La Observanto sabate 29 novembro 2014 19.00 UTC

el 2001: Al Space Odyssey por Klinga Kuristo Kaj RoboCop por la Matrico, kiom homoj trakti la Artefarita inteligenteco ili kreis pruvis fekunda distópicas teritorio por filmistoj. Pli lastatempe Spike Jonze la ŝi Alex Garland venonta Eksa Machina esplori kio povus esti ŝatas havi AI kreaĵoj vivantaj inter ni kaj, kiel Alan Turing fama testo foregrounded, kiom malfacila ĝi povus esti por diri la karno kaj sango de la splitoj kaj kodo.

Tiuj konzernoj estas eĉ gxenas iujn de Silicia Valo la grandaj nomoj: pasintmonate Telsa la Elon Musk priskribita AI kiel homaro "granda ekzisteca minaco ... ni devas esti tre zorgema". Kio multaj el ni ne konscias estas ke AI ne iu fora teknologio kiu nur ekzistas en filmo-faristo imagoj kaj komputila sciencisto laboritorioj. Multaj de niaj smartphones dungi rudimenta AI teknikoj traduki lingvojn aŭ respondi niajn demandojn, dum videoludoj uzas AI por generi kompleksajn, ĉiam cambiante videoludado scenaroj. Kaj tiel longe kiel Silicia Valo firmaoj kiel Google kaj Facebook daŭre akiras AI firmaoj dungas AI fakuloj, AI la IQ daŭrigos leviĝi ...

Ne Aj Steven Spielberg filmo?
Neniu argumentoj tie, sed la termino, kiu signifas "artefarita inteligenteco", havas pli famkonata historio ol Spielberg kaj Kubrick 2001 filmo. La koncepto de artefarita inteligenteco superas al la naskiĝo de komputado: Je 1950, nur 14 jaroj post difinanta la koncepto de ĝenerala intenco komputilo, Alan Turing demandis "Cxu masxinoj opinias??

AI
Jude Law kiel Gigolo Joe (kaj amikoj) en Spielberg kaj Kubrick 2001 AI movie. Foto: Allstar / Warner Bros / Sportsphoto Ltd

Estas iu kiu estas ankoraŭ ĉe la fronto de niaj mensoj 64 jarojn poste, plej ĵuse iĝante la kerno de Alex Garland nova filmo, Eksa Machina, kiu vidas juna viro demandis taksi la homaron de bela android. La koncepto ne estas miliono mejlojn forigita de kiuj proponas en Turing 1950 papero, Computing Machinery kaj Inteligenteco, en kiun li elspezata proponon por la "imitaĵo ludo" - kion ni nun scias kiel la testo de Turing. Hoki komputilo supren al teksto terminalo kaj gxi havis konversaciojn kun homa interrogador, dum reala persono faras la saman. La koro de la testo estas ĉu, kiam vi demandas la interrogador diveni kiu estas la homa, "La interrogador [volas] decidi erare kiel ofte kiam la ludo estas ludita tiel kiel ĝi faras kiam la ludo estas ludita inter viro kaj virino ".

Turing diris ke demandanta ĉu maŝinoj povis pasi la imitaĵo ludo estas pli utila ol la malpreciza kaj filozofie neklara demando de ĉu aŭ ne ili "pensas". "La originala demando ... Mi kredas esti tro sensignifa por meriti diskuton." Tamen, Li opiniis, ke por la jaro 2000, "La uzo de vortoj kaj ĝenerala edukita opinio estos ŝanĝita tiel ke oni povos paroli pri maŝinoj pensante sen atendanta esti kontraŭdirita".

Laŭ natura lingvo, he wasn’t far off. hodiaŭ, it is not uncommon to hear people talking about their computers being “confused”, or taking a long time to do something because they’re “thinking about it”. But even if we are stricter about what counts as a thinking machine, it’s closer to reality than many people think.

Blade Runner’s ‘Voight-Kampff’ test, designed to distinguish replicants from humans based on their emotional response to questions.

So AI exists already?
It depends. We are still nowhere near to passing Turing’s imitation game, despite reports to the contrary. En junio, a chatbot called Eugene Goostman successfully fooled a third of judges in a mock Turing test held in London into thinking it was human. But rather than being able to think, Eugene relied on a clever gimmick and a host of tricks. By pretending to be a 13-year-old boy who spoke English as a second language, the machine explained away its many incoherencies, and with a smattering of crude humour and offensive remarks, managed to redirect the conversation when unable to give a straight answer.

The most immediate use of AI tech is natural language processing: working out what we mean when we say or write a command in colloquial language. For something that babies begin to do before they can even walk, it’s an astonishingly hard task. Consider the phrase beloved of AI researchers – “time flies like an arrow, fruit flies like a banana”. Breaking the sentence down into its constituent parts confuses even native English speakers, let alone an algorithm.

Is all AI concerned with conversations?
Not at all. Fakte, one of the most common uses of the phrase has little to do with speech at all. Some readers will know the initials AI not from science fiction or Alan Turing, but from video games, where it is used to refer to computer-controlled opponents.

In a first-person shooter, Ekzemple, the AI controls the movements of the enemies, making them dodge, aim and shoot at you in challenging ways. In a racing game, the AI might control the rival cars. As a showcase for the capabilities of AI, video games leave a lot to be desired. But there are diamonds in the rough, where the simplistic rules of the systems combine to make something that appears complex.

Take Grand Theft Aŭto V, where the creation of a city of individuals living their own lives means that it’s possible to turn a corner and find a fire crew in south central LA having a fist-fight with a driver who got in the way of their hose; aŭ Dwarf Fortress, where caves full of dwarves live whole lives, richly textured and algorithmically detailed. Those emergent gameplay systems show a radically different way that AI can develop, aimed not at fully mimicking a human, but at developing a “good enough” heuristic that turns into something altogether different when scaled up enough.

So is everyone ploughing money into AI research to make better games?
Ne. A lot of AI funding comes from firms such as Apple and Google, which are trying to make their “virtual personal assistants”, kiel Siri kaj Google Now, vivi ĝis la nomo.

Sonas paŝo forigita de la scienco fikcio vizioj de Turing, sed la voĉo-kontrolita servoj estas efektive devanta fari preskaŭ ĉiuj samaj peza levo ke reala persono faras. Ili devas aŭskulti kaj kompreni la parolita vorto, determini kiel kio ili aŭdis koncernas la datumoj detentan, kaj tiam revenu rezulto, Ankaŭ en konversacia parolo. Ili ne estu provas trompi ni en pensanta ke ili estas homoj, sed ili ne estas malproksime. Ĉar ĉiuj kalkuloj estas farita en la nubo, des pli ili aŭdas, la bona ili estas je kompreno.

En la 2013 filmo Her, soleca Teodoro Twombly (Joakimo Phoenix) enamiĝas de mastruma sistemo.

However the leading AI research isn’t just aimed at replicating human understanding of the world, but at exceeding it. IBM’s Watson is best known as the computer that won US gameshow Jeopardy! Je 2011, harnessing its understanding of natural language to parse the show’s obtuse questions phrased as answers. But as well as natural language understanding, Watson also has the ability to read and comprehend huge bodies of unstructured data rapidly. In the course of the Jeopardy! taping, that included more than 200 million pages of content, including the full text of Wikipedia. But the real goal for Watson is to expand that to full access to the entire internet, as well as specialist data about the medical fields it will eventually be put to work in. And then there are the researchers who are just trying to save humanity.

Oh God, we’re all going to die?
Eble. The fear is that, once a sufficiently general-purpose AI such as Watson has been created, its capacity will simply scale with the processing power available to it. Moore’s law predicts that processing power doubles every 24 monatoj, so it’s only a matter of time before an AI becomes smarter than its creators – able to build an even faster AI, leading to a runaway growth in cognitive capacity.

But what does a superintelligent AI actually do with all that capacity? That depends on its programming. The problem is that it’s hard to program a supremely intelligent computer in a way that will ensure it won’t just accidentally wipe out humanity.

Suppose you’ve set your AI the task of making paperclips and of making itself as good at making paperclips as possible. Pretty soon, it’s exhausted the improvements to paperclip production it can make by improving its production line. What does it do next?

“One thing it would do is make sure that humans didn’t switch it off, because then there would be fewer paperclips,” explains Nick Bostrom in Salon revuo. Bostrom’s book, Superintelligence, has won praise from fans such as SpaceX CEO Elon Musk for clearly stating the hypothetical dangers of AI.

The paperclip AI, Bostrom says, “might get rid of humans right away, because they could pose a threat. #Anka?, you would want as many resources as possible, because they could be used to make paperclips. Like, Ekzemple, the atoms in human bodies.”

How do you fight such an AI?
The only way that would work, according to some AI theorists such as Ray Kurzweil, a director of engineering at Google, is to beat it to the punch. Not only do humans have to try to build a smart AI before they make one accidentally, but they have to think about ethics first – and then program that into it.

Post kiam #?iu, coding anything simpler is asking for trouble. A machine with instructions to “make people happy”, Ekzemple, might just decide to do the job with electrodes in brains; so only by addressing one of the greatest problems in philosophy can we be sure we’ll have a machine that understands what it means to be “good”.

tiel, all we have to do is program in ethics and we’ll be fine?
Puto, not quite. Even if we manage to not get wiped out by malicious AI, there’s still the issue of how society adapts to the increasing capability of artificial intelligence.

The Industrial Revolution was characterised by the automation of a number of jobs that previously relied on manual labour. There is little doubt that it represented one of the greatest increases in human welfare ever seen. But the upheaval at the time was momentous and something we could be about to see again.

Elon Musk on the dangers of AI.

What steam power did for physical labour, AI could do for mental labour. jam, the first casualties are starting to become clear: the minicab dispatch office has little place in a world of Hailo Kaj Uber; the job of a stockbroker has changed beyond all recognition thanks to the introduction of high-frequency trading; and ever since the construction of the Docklands Light Railway in the 1980s, the writing has been on the wall for train drivers.

And the real changes are only just beginning. en novembro, Goldman Sachs led a $15m funding round for Kensho, a financial data service that uses AI techniques to pump out financial analysis at a rate no human analyst could match. And it can do it while taking stock of the entirety of the huge amount of financial data available, something humans simply can’t cope with.

Kensho’s analytical notes could then be passed on to a high-frequency trading firm such as Athena, which will use the insights to gain an edge of milliseconds on the market – that’s enough to make money, if you’re trading with billions of dollars. Once the trading has affected the market, it might be written up for Forbes by Narrative Science, which uses algorithms to replace financial journalists. Post kiam #?iu, most business stories follow a common template, and the data is already available in a structured format, so why waste time getting people involved at all?

On aggregate level, these changes are a good thing. If the work of millions of people is covered by algorithms, then output goes up, hours worked go down, and we move one step closer to a Jetsons-style utopia.

En la fino, it will be OK?
Assuming we avoid the superintelligent AIs wiping us out as an afterthought, manage to automate a large proportion of our jobs without creating mass unemployment and societal unrest, and navigate the tricky boundaries of what personhood entails in a world where we can code passable simulacra of humans, then yes, it should be fine.

Gardanto.Co.Uk ? Gardanta Sciigo & Amaskomunikilaroj Limigita 2010

Eldonita tra la Gardanta Sciigo #Pa?ta?o Kromsoftvaro Por WordPress.

Rilatita Artikolojn

25649 0