Apple has just managed to land one of Google's top Search & Artificial Intelligence (AI) executives, John Giannandrea, in a move that is a shot in the arm to catch up to the AI technology of its rivals.
In March, technology site The Information detailed seven years of infighting within the Siri team at Apple, with multiple attempts to reorganise the basic technology that underpins the feature falling prey to internal politics which limited attempts to improve the overall product.
Giannandrea's hiring is being widely viewed as a significant win for the iPad maker and demonstrates its intention to take on the likes of current AI leaders such as Google, Amazon and Facebook. Google acquired Metaweb in 2010 and turned its technology into its Knowledge Graph, the blurbs of information provided as the result of a Google search whenever typing in a person, place, or thing.
Considered a highly desired executive, especially as A.I. seems to steadily grow in prevalence and importance, John Giannandrea will help spearhead Apple's machine learning and A.I. strategy.
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John Giannandrea, Google's former chief of search, will join Apple and report directly to CEO Tim Cook, according to the report.
Now, with Giannandrea joining Apple's arsenal, the company is likely to recruit more top level talents and also improve its algorithms. Only in the previous year or so has Apple loosen its grip on its researchers enough to allow them to publish papers in the AI community. Last week, Windows' chief Terry Myerson departed after Microsoft announced that it would focus more on AI and the Cloud. Apple's Siri has been lagging far behind its competitors in the artificial intelligence market. Because of its stance on data collection, Apple still has no access to the massive data sets that Facebook and Google do.
Now, though, Apple is looking to expand Siri's reach. Machine learning experts are in high demand in Silicon Valley, with salaries often exceeding eight figures.
Giannandrea believes that AI won't make humans "obsolete", but is more concerned with the algorithmic bias that has already crept into many ML powered systems, as per an MIT Technology review.