The
lineup of Google Coral developer hardware available at
launch.

Google

  • Google introduced Coral, a line of hardware to help
    hackers build and experiment with AI-powered
    gadgetry. 
  • It’s similar in principle to popular minicomputers like
    the Raspberry Pi, but with some Google special sauce — it uses
    a custom Google processor, customized for AI, and is designed
    to run the Google-created TensorFlow AI software.
  • This could help Google spread the word of the
    already-popular TensorFlow, while also staking its claim in
    edge computing.
  • Edge computing refers to the concept of putting more
    intelligence on a device, rather than in the cloud. Indeed,
    some believe that edge computing could be a larger market than
    cloud computing.

Google has quietly launched Google Coral, a line of relatively
cheap hardware aimed at helping developers experiment with
building gadgetry powered by artificial intelligence. 

On its website, Google
Coral has product listings for a $150 motherboard, a $75 USB
device to bring AI to existing systems, and a $25 camera that
slots into the board. The listings were
first spotted by the Verge

“Coral offers a complete local AI toolkit that makes it
easy to grow your ideas from prototype to production,” writes
Google in a
blog post announcing Coral

In theory, it’s more than a little bit like the Raspberry Pi, the
pioneering
$35 minicomputer
, which is mega-popular among hackers as an
easy and cheap way to build experimental hardware and other
oddities. 

In practice, the Coral lineup appears to come with lots of Google
special sauce.

The processor on the Google Coral developer board is an Edge TPU,
a chip specifically designed by the search giant to bring AI to
low-powered devices like cameras and home appliances. It’s also
designed to run TensorFlow Lite, a version of Google’s very
popular open source AI framework designed, again, for low-powered
devices. 

It’s important to note that these devices aren’t actually much
good at training AI algorithms — as
the Verge notes
, you’ll need much more powerful hardware for
that. Rather, these are good for putting those algorithms to
work, and helping gather the real-world data to refine them.

And this may be the real significance of Google Coral, as the
company looks to stake its claim in so-called
edge computing
, the market that many industry insiders
believe could be bigger than the cloud. 

Read more: 

The
CEO of Hewlett Packard Enterprise tells us why the company is
‘under-appreciated’ and how it can beat Amazon in a market that’s
bigger than cloud computing

The big idea behind edge computing is to bring more intelligence
to devices like phones, TVs, appliances, factory robots, and even
self-driving cars and other vehicles. While the cloud brings
unprecedented levels of supercomputing power to anything with an
internet connection, there’s a serious latency problem; you don’t
want your self-driving car waiting to get a response from the
server while it figures out whether to stop at a traffic light.

The solution, then, is to give the device (or car, or robot)
enough computing power to make decisions on its own. The massive
processing power of the cloud can help formulate, analyze,
improve, and generally fine-tune the algorithm, while the device
itself has enough AI to run the algorithm quickly and
accurately. 

Hack away and spread the gospel of TensorFlow

Cloud players like
Microsoft Azure
and Amazon Web Services both already have
their own plays for edge computing, while legacy companies like
Intel and
Hewlett Packard Enterprise
see the opportunity to gain ground
after largely losing out in cloud computing. Indeed, Intel offers
its own cheap AI hardware to developers.  

For Google’s part, TensorFlow and its Lite variant — open source
projects that are free to use — have basically become the
standard software for powering artificial intelligence, with the
Facebook-created PyTorch as its primary competition. In mid-2018,

Microsoft even bought a startup powered by the Google-created
TensorFlow.

On Wednesday, Google
also announced that TensorFlow had been downloaded 41 million
times as of November
, and that TensorFlow Lite is running on
2 billion phones and other mobile devices. Google itself uses
TensorFlow Lite to run the Google Assistant, Google Photos, and
even Google Search on phones.

Which is a very long way to come back around to Google Coral. By
reaching out to developers with tools that make it relatively
cheap and easy to hack away at new hardware projects, it could
very well spread the gospel of TensorFlow and the Edge TPU. 

That’s good for Google in the long haul, because while TensorFlow
might be free software, Google Cloud offers developers plenty of
services for powering these devices on the backend. Indeed,
Google says in its blog entry that Coral is made to integrate
nicely with Google Cloud’s internet of things (IoT) backend
services. 

That, in turn, only stands to boost Google Cloud’s reputation as
the best place to run TensorFlow apps, which could help it build
its credibility in both AI and edge computing — a plus as it
pushes against the leading Amazon Web Services and second-place
Microsoft Azure clouds. 

It’s a playbook that’s worked for Google before: Kubernetes, a
very popular open source tool for managing large-scale cloud
infrastructures,
became a cloud standard because developers love it so much
.
If developers come to love Google Coral, too, it could make
Google Cloud a more attractive place for developers in the next
big thing.

Meanwhile, Google’s rivals are doing their own kinds of outreach
to AI developers. Microsoft recently resurrected the
Xbox’s failed Kinect accessory as a $400 AI-powered camera for
developers
, while
Amazon is letting developers program their own self-driving toy
cars

Get the latest Google stock price here.

(Excerpt) Read more Here | 2019-03-06 19:56:35
Image credit: source

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