Google AI on Raspberry Pi: Now you get official TensorFlow support

Google's TensorFlow team makes it a whole lot easier to get AI up and running on a Raspberry Pi.
Written by Liam Tung, Contributing Writer

Video: How to set up your Raspberry Pi 3 Model B+.

Besides putting a Raspberry Pi to work on a mini Mars rover, it's now going to be a lot easier to use Google's TensorFlow artificial-intelligence framework with the low-powered computer.

Developers with Raspberry Pi have already been able to use TensorFlow in a variety of ways to add deep-learning models so that cheap or expensive hardware can do things like image classification.

SEE: Cheat sheet: TensorFlow, an open source software library for machine learning TechRepublic

While TensorFlow can be used on Linux, Windows, Android, macOS, and iOS, it's hard to find cheaper hardware than the $35 Raspberry Pi.

But as noted by Pete Warden, a software engineer and lead of the TensorFlow mobile and embedded team, running TensorFlow on Raspberry Pi "has involved a lot of work".

However, the TensorFlow group's recent work with the Raspberry Pi Foundation should make it more straightforward for developers using the Python programming language to build AI applications on hardware integrated with a Raspberry Pi device.

"Thanks to a collaboration with the Raspberry Pi Foundation, we're now happy to say that the latest 1.9 release of TensorFlow can be installed from pre-built binaries using Python's pip package system," wrote Warden of TensorFlow release 1.9.

Those using Raspberry Pi Foundation's Debian Stretch-based Raspbian 9 can install TensorFlow by running two simple commands to begin writing TensorFlow programs in no time.

SEE: NASA shows the world its 20-year virtual reality experiment to train astronauts: The inside story cover story PDF

Lowering the bar for running TensorFlow on Raspberry Pi obviously is a win for Google's developers given the popularity of the developer board, which last year reached the 14 million units sold milestone. Raspberry Pi founder Even Upton is upbeat about its prospects for Pi users too.

"It is vital that a modern computing education covers fundamentals and forward-looking topics," said Upton.

"With this in mind, we're very excited to be working with Google to bring TensorFlow machine learning to the Raspberry Pi platform. We're looking forward to seeing what fun applications kids (of all ages) create with it."

A case in point that already combines TensorFlow with Raspberry Pi is the self-driving Donkey Car, which can be built for about a 10th of the cost of NASA's mini Mars rover.


Getting TensorFlow to run on Raspberry Pi "has involved a lot of work".

Image: osde8info/Flickr

Previous and related coverage

Raspberry Pi meets AI: The projects that put machine learning on the $35 board

Explore the projects pushing the limit of what's possible on the budget board.

Raspberry Pi space rover: NASA open-sources its mini Mars robot

Now you can have you're own six-wheel, rock-climbing rover robot for Earth exploration.

Raspberry Pi goes Android Auto: Now you can build your own cheap car head unit

Why buy a finished Android Auto head unit when you can hack one together with a Raspberry Pi 3?

Raspberry Pi's 'app store' lands with new Raspbian OS update

Raspberry Pi Foundation is hungry for beginners to try out its device, hence a new setup wizard and app store.

How NASA chooses tech for the International Space Station, and why AI could help get us to Mars

Tech support, but in space: A look at the tech which astronauts use on the ISS.

Raspberry Pi-style Renegade Elite runs Android Oreo on six-core, 4K board

If you're specifically not looking for a Raspberry Pi, the Renegade Elite could be the board of choice.

Google includes a Raspberry Pi in a DIY smart speaker kit CNET

The updated kits are rolling out to Target and include everything you need to build your own smart speaker or smart camera.

Raspberry Pi: A cheat sheet TechRepublic

Everything you need to know about the tiny, ultra-cheap computer that has taken the world by storm.

Editorial standards