Google Update: Smartphones have fast become the new frontier of
artificial intelligence. Algorithms that used to run in the cloud,
beaming results down to our devices via the internet, are now being
replaced by software that runs directly on phones and tablets. Facebook
is doing it, Apple is doing it, and Google is (perhaps) doing it slightly more than anyone else.
The latest example of mobile AI from the Silicon Valley search giant is the release of MobileNets
,
a set of machine vision neural networks designed to run directly on
mobile devices. The networks come in a variety of sizes to fit all sort
of devices (bigger neural nets for more powerful processors) and can be
trained to tackle a number of tasks.
MobileNets can be used to analyze faces, detect common
objects, geolocate photos, and perform fine-grained recognition tasks,
like identifying different species of dogs. These tools are extremely
adaptable, and could be put to a number of different uses, including
powering augmented reality features, or creating apps to help the
disabled. Google says the performance of each neural net differs from
task to task, but overall, its networks either meet or approach recent
state-of-the-art standards.
For consumers, this is going to mean more mobile apps
with AI functions as developers start incorporating these tools. Running
these sort of tasks directly on-device has a number of benefits for
everyday users, including faster performance, greater convenience (you
don’t have to connect to the internet), and better privacy (your data
isn’t being sent off-device).
Apple pushed the latter angle particular when it released a set of machine learning APIs for developers
(named CoreML) earlier this month, and both Facebook and Google have
created their own frameworks for building mobile-first. Even Snapchat is
working on putting image recognition on your phone,
releasing its first academic paper on the subject this week. The next
step for mobile AI? Specially designed mobile processors. Both Google
and Apple have dropped hints they might be crafting such silicon, and
ARM has already released a first early batch.
Theverge
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