A set of tools that developers can use to incorporate machine learning techniques into their apps – Core ML, was very recently introduced by Apple Inc. Amid all of the new hardware and iOS updates the news was little noticed. But analysts say that this small bit of news is important.
The presumption that Apple is preparing to introduce a new kind of processor, presumably just for iPhones at first, that could make trendy machine learning workloads run more efficiently was indicated by the capabilities of Core ML which, analysts say, are a “dead giveaway”. These are the assumptions and opinion of Reza Zadeh, CEO of image recognition startup Matroid, one person inhabiting the world of machine learning.
A company would only release something like Core ML “if there’s a really intense piece of hardware that it was going do compile down into,” said Zadeh, who built the machine learning algorithms for Twitter’s Who to Follow feature before starting Matroid last year.
“All those converters and everything, it’s a dead giveaway there’s going to be some intense [processor] available down the line.”
Alphabet’s Google unveiled a custom tensor processing unit or TPU, was unveiled six months after the company introduced its TensorFlow open-source framework for machine learning in November 2015.
Something similar with the launch of Core ML, is being done by Apple, Zadeh thinks. processors that could be plunked into smaller devices, as opposed to data centers, where Google’s TPUs are located, are being worked upon in the meantime by startups like Deep Vision and Mythic.
Another startup that was acquired by Intel in 2016 was Movidius, which touts its vision processing unit for drones and other gadgets.
Apple’s plans to build an artificial intelligence (AI) chip were reported in some media last month. For certain computations in the iPhone 7 last year, this would build on the inclusion of the inclusion of a field programable gate array (FPGA).
While also providing ways to use their own models, machine learning models that developers can drop right into iOS, macOS and tvOS apps can also be provided by Core ML.
just making smart calculations given a certain amount of previous data, following the movement of things in video frames or recognize objects in images would be allowed for apps drawing on Core ML.
Current iPhones and iPads are the one where these processes can run. While also lengthening battery life, it’s reasonable to think Apple wants to improve performance on future hardware. Zadeh said that, instead of devices’ central processing units (CPUs) and graphics processing units (GPUs), which are not always optimized for those computing duties, it could do that sending machine learning workloads to a dedicated AI chip.
Zadeh said that in the next few decades, emerging specialized processors like the rumored Apple AI chip could become the computational workhorse.
(Adapted from CNBC)