"Perhaps the most important news of our day is that datasets -- not algorithms -- might be the key limiting factor to development of human-level artificial intelligence," according to Alexander Wissner-Gross in a written response to the question posed by Edge: "What do you consider the most interesting recent scientific news?" At the dawn of the dield of artificial intelligence, two of its founders famously predicted that solving the problem of machine vision would only take a summer. We now know that they were off by half a century. Wissner-Gross began to ponder the question of: "What took the AI revolution so long?" By reviewing the timing of the most publicized AI advances over the past 30 years, he found evidence that suggests a provocative explanation: perhaps many major AI breakthroughs have actually been constrained by the availability of high-quality training datasets, and not by algorithmic advances.
Apr-25-2016, 22:41:18 GMT