Apple is expanding its presence folks. The company is ramping up its Seattle workforce with an eye upon increasing its machine learning and artificial intelligence smarts. The company confirmed the same to GeekWire.
Apparently, Apple is renting out more floors at Two Union Square. The company already leases a couple of floors at the 56-floor skyscraper. However, it will now rent more and fill them with people learned in machine learning and AI. The folks deployed here will be working upon Apple’s own projects.
While we don’t have a particular name from the company, it is probably safe to assume that at least some of the people deployed here will be working upon Siri, Apple’s AI powered assistant that has been lagging as compared to its Microsoft and Amazon peers.
Meanwhile, Apple has been quietly building up its own machine learning and AI wing. For instance, the company acquired Turi only last year, for a reported $200 million. Apple’s portfolio also includes companies like Perceptio and VocalIQ. Al of these companies operated in different areas of of application of AI. Since then, Apple hasn’t really made a groundbreaking revelation in its own artificially intelligent systems however, setting up new offices with a worforce dedicated in that direction could be the first hint that something major was afoot.
Meanwhile, the Cupertino giant’s push in the realm of AI isn’t coming none to early. Many of its competitors such as Microsoft, Amazon, Google have already been hard at work upon improving the capabilities of their artificial intelligences. The latter two have even launched dedicated devices (Echo, Dot, Tap, Google Home) to house their assistants. So yeah, the iPhone maker would appear to be lagging somewhat. However, with this move perhaps, the company would be able to breather fresh life into its AI and ML projects.
Meanwhile, the company is also in the process of shifting a significant portion of its employees to the all new Apple Park. It will be interesting to see whether the company decides to divide its machine learning teams in multiple parts or keeps all of them in one place.
