Interesting Snippets

What does it mean that Google really is trying to build the Star Trek computer? I take it as a cue to stop thinking about Google as a “search engine.” That term conjures a staid image: a small box on a page in which you type keywords. A search engine has several key problems. First, most of the time it doesn’t give you an answer—it gives you links to an answer. Second, it doesn’t understand natural language; when you search, you’ve got to adopt the search engine’s curious, keyword-laden patois. Third, and perhaps most importantly, a search engine needs for you to ask it questions—it doesn’t pipe in with information when you need it, without your having to ask.
The Star Trek computer worked completely differently. It understood language and was conversational, it gave you answers instead of references to answers, and it anticipated your needs. “It was the perfect search engine,” Singhal said. “You could ask it a question and it would tell you exactly the right answer, one right answer—and sometimes it would tell you things you needed to know in advance, before you could ask it.

European buyers of the Ford Focus, a mid-sized car, can now leave it to drive itself and maintain a safe distance in steady traffic. The car can measure a parking space and steer itself into it. It reads road signs and admonishes the driver if he breaks the speed limit. Such gadgetry also increasingly makes decisions on the driver’s behalf and overrules him in an emergency, for instance, braking to avoid a crash.

unique EU-backed €1.5 million RoboLaw Project, Salvini is managing a team of roboticists, lawyers and philosophers (yes, philosophers) from a consortium of European universities, who are working hard to come up with proposals for the laws and regulations necessary to manage emerging robotics technologies in Europe

Arnold also sees virtual assistants as intellectual equalizers. A superb memory might cease to be an advantage as intelligent assistants are tasked with remembering names, dates and other details. Everyone will have the ability to see unusual but important connections between legal cases or patients’ symptoms, thanks to assistants that can identify relevant precedents or files.

IPsoft’s Eliza, a “virtual service-desk employee” that learns on the job and can reply to e-mail, answer phone calls and hold conversations, is being tested by several multinationals. At one American media giant she is answering 62,000 calls a month from the firm’s information-technology staff. She is able to solve two out of three of the problems without human help.

The team, led by Google’s Dr Jeff Dean, used the 16,000 processor array to create a brain-style ‘neural network’ with more than a billion connections…. The team then fed it random images culled from 10 million YouTube videos - and let it ‘learn’ by itself. Unsurprisingly, the machine focused in on cats. ‘We never told it during the training, ‘This is a cat,” said Dr. Dean. ‘It basically invented the concept of a cat.’

Google scientists created one of the largest neural networks for machine learning by connecting 16,000 computer processors, which they turned loose on the Internet to learn on its own. Presented with 10 million digital images found in YouTube videos, what did Google’s brain do? What millions of humans do with YouTube: looked for cats.

We’re generally faster learners than our technology, as long as we are given something that can be easily approached and mastered. We’re more plastic and malleable – what we do changes our brains – so the ‘wily’ technology (and it’s designers) will sieze upon this and use it… All of which leaves me wondering whether we are working towards Artificial Empathy, rather than Artificial Intelligence in the things we are designing…