Silicon Valley loves a new fad. To judge by the spate of fundraising by start-ups in recent weeks, it has found one in an idea that is more than half a century old: artificial intelligence. “This is the hot place to be at the moment,” says Stephen Purpura, whose own AI company, Context Relevant, has raised more than $44m since it was founded in 2012. By his reckoning, more than 170 start-ups have jumped on the AI bandwagon. The newcomers to AI believe that the technology has finally caught up with the hopes, bringing a heightened level of intelligence to computers. They promise a new way for humans to interact with machines — and for the machines to encroach on the world of humans in unexpected ways. “Technologically, it’s a paradigm shift from putting commands into a box to a time when computers watch you and learn,” says Daniel Nadler, another of the AI hopefuls. His company, Kensho, raised $15m recently in pursuit of an ambitious goal: to train computers to replace expensive white-collar workers such as financial analysts. [...] The basic uses for the technology fall into several different areas. Thanks to improved pattern recognition capabilities, identifying images — a notoriously hard problem for computers — has become far easier. Vicarious, one of the most ambitious companies in this area, recently raised $72m, after demonstrating that it can solve Captchas, the visual puzzles that are used by websites to distinguish humans from computers. The same technology is also being used to help computers “understand” language — a problem known as natural language recognition. That is one of the techniques behind systems such as IBM’s Watson, which queries large bodies of information to arrive at a most likely answer. A third popular use rests on trying to identify relevance — whether that means personalising online content and other recommendations, or more effectively targeting advertising. As often with a promising new idea, some of the first applications have been in the financial markets, although the amount of money at stake makes those involved wary of talking. “If your financial application works, why disclose it and arbitrage it away?” says Babak Hodjat, chief scientist of Sentient Technologies. His company draws massive computing power from data centres to run full-blown simulations of financial markets: by applying “evolutionary algorithms” that try to learn from how markets react in different circumstances, it hopes to develop models for predicting how they will behave in future.
Posted on: Sun, 04 Jan 2015 18:26:05 +0000