Siri’s Inventors Are Building a Radical New AI
When Apple announced the iPhone 4S on October 4, 2011, the headlines were not about its speedy A5 chip or improved camera. Instead they focused on an unusual new feature: an intelligent assistant, dubbed Siri. At first Siri, endowed with a female voice, seemed almost human in the way she understood what you said to her and responded, an advance in artificial intelligence that seemed to place us on a fast track to the Singularity. She was brilliant at fulfilling certain requests, like “Can you set the alarm for 6:30?” or “Call Diane’s mobile phone.” And she had a personality: If you asked her if there was a God, she would demur with deft wisdom. “My policy is the separation of spirit and silicon,” she’d say.
Over the next few months, however, Siri’s limitations became apparent. Ask her to book a plane trip and she would point to travel websites—but she wouldn’t give flight options, let alone secure you a seat. Ask her to buy a copy of Lee Child’s new book and she would draw a blank, despite the fact that Apple sells it. Though Apple has since extended Siri’s powers—to make an OpenTable restaurant reservation, for example—she still can’t do something as simple as booking a table on the next available night in your schedule. She knows how to check your calendar and she knows how to use OpenTable. But putting those things together is, at the moment, beyond her.
Now a small team of engineers at a stealth startup called Viv Labs claims to be on the verge of realizing an advanced form of AI that removes those limitations. Whereas Siri can only perform tasks that Apple engineers explicitly implement, this new program, they say, will be able to teach itself, giving it almost limitless capabilities. In time, they assert, their creation will be able to use your personal preferences and a near-infinite web of connections to answer almost any query and perform almost any function.
“Siri is chapter one of a much longer, bigger story,” says Dag Kittlaus, one of Viv’s cofounders. He should know. Before working on Viv, he helped create Siri. So did his fellow cofounders, Adam Cheyer and Chris Brigham.
For the past two years, the team has been working on Viv Labs’ product—also named Viv, after the Latin root meaning live. Their project has been draped in secrecy, but the few outsiders who have gotten a look speak about it in rapturous terms. “The vision is very significant,” says Oren Etzioni, a renowned AI expert who heads the Allen Institute for Artificial Intelligence. “If this team is successful, we are looking at the future of intelligent agents and a multibillion-dollar industry.”
Viv is not the only company competing for a share of those billions. The field of artificial intelligence has become the scene of a frantic corporate arms race, with Internet giants snapping up AI startups and talent. Google recently paid a reported $500 million for the UK deep-learning company DeepMind and has lured AI legends Geoffrey Hinton and Ray Kurzweil to its headquarters in Mountain View, California. Facebook has its own deep-learning group, led by prize hire Yann LeCun from New York University. Their goal is to build a new generation of AI that can process massive troves of data to predict and fulfill our desires.
Viv strives to be the first consumer-friendly assistant that truly achieves that promise. It wants to be not only blindingly smart and infinitely flexible but omnipresent. Viv’s creators hope that some day soon it will be embedded in a plethora of Internet-connected everyday objects. Viv founders say you’ll access its artificial intelligence as a utility, the way you draw on electricity. Simply by speaking, you will connect to what they are calling “a global brain.” And that brain can help power a million different apps and devices.
“I’m extremely proud of Siri and the impact it’s had on the world, but in many ways it could have been more,” Cheyer says. “Now I want to do something bigger than mobile, bigger than consumer, bigger than desktop or enterprise. I want to do something that could fundamentally change the way software is built.”
No autoru izteikumiem labi redzam pašreizējo stāvokli: “Viv’s knowledge grows, so will its understanding; its creators have designed it based on three principles they call its “pillars”: It will be taught by the world, it will know more than it is taught, and it will learn something every day. As with other AI products, that teaching involves using sophisticated algorithms to interpret the language and behavior of people using the system—the more people use it, the smarter it gets. By knowing who its users are and which services they interact with, Viv can sift through that vast trove of data and find new ways to connect and manipulate the information.”
Nav izpratnes veidošanai nepieciešamas būtiskas komponentes: Mācīties nozīmē nevis lasīt un kopēt datus, bet iegūt savu jutekļu un izpildorgānu pieredzi un sasaistīt šo pieredzi ar runātā vai rakstītā valodā izteiktu, aprakstītu savējo un citu cilvēku pieredzi. Izprast nozīmē apziņā izveidot apkārtējās vides modeļus un lietot tos apkārtējās vides reakciju prognozēšanā. Domāt nozīmē ‘darbināt’ šos modeļus. Pagaidām viņu robots lieto programmētāju veidotus “sophisticated algorithms to interpret the language and behavior of people”, bet nelieto paša robota izveidotus ārējās pasaules modeļus (algoritmus) – kā Homo sapiens to dara. Jebkurā gadījumā, no raksta var labi redzēt stāvokli nozarē.
Varam droši teikt, ka tad, kad programmētāji iemācīs robotiem pašiem veidot tūkstošiem apkārtējās vides modeļus (un lietot, ti., ‘darbināt’ tos, aprakstot to darbību ar cilvēku valodas vārdiem), tad būs radīta mākslīga (un cilvēkiem saprotama) inteliģence. Ceļš ir zināms: ‘ģenētiski’ (programmātiski) ieliktas spējas, tendences. Imants Vilks.