GOOGLE HAS REVEALED the third-generation of its Tensor Processing Unit (TPU) designed to give powering and training artificial intelligence (AI) a kick up the backside.
Announced by Google chief executive Sundar Pichai at Google's I/O conference, TPU 3.0 is eight times more powerful than its predecessor at powering machine learning algorithms.
As a result, Google has added liquid cooling to its data centres to prevent the TPU 3.0 from getting all hot and bothered while its crunching code that helps computers figure out whether they should direct a self-driving car to plough into a tree in order to avoid hitting a dumb pedestrian in the middle of the road.
And that's about all we know, as Pichai decided to go on about a whole suite of new Google Assistant features rather than shed more light on TPU 3.0.
But really it just looks to be a more beefy follow-up to its predecessor, which was used to power AI tech and machine learning models Google uses to make its smart services... well.... smarter.
Previous TPU compute power, optimised for Google TensorFlow-based software, was leased out to developers through the Google Cloud. So we expect the same to happen here, which should give smart software makers the means to speed up their AI training and get clever code into production more quickly; after all, there's up to 1000 petaflops of performance on offer.
While details regarding the specs of TPU 3.0 are thin on the ground, we can expect the tech to not only be put to use with Google's own AI work and be leased to developers but also help power smart systems in areas such as healthcare.
"AI is going to impact many many fields, such as healthcare. Our AI systems offered more insights than humans did," said Pichai.
The bossman noted that Google's AI tech has helped doctors figure out when their patients get sick and work on preventative medicine and actions to avoid health issues such as the risk of cardiovascular problems.
While Google may not have made a song and dance about TPU 3.0, we expect it is and will be put to heavy use in Google's own AI work as well as that of others granted access to it. µ
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