
Google planning to bring AI and ML tools to Raspberry Pi - Lio
http://www.bbc.co.uk/news/technology-38742762
======
toisanji
I built a robot with tensorflow running on the raspberry pi to do autonomous
driving and computer vision:
[http://www.jtoy.net/portfolio/](http://www.jtoy.net/portfolio/)

I'm working on the next version to make it more useful, but all the technology
is not there yet, I want the robot to be able to understand speech and talk
back to users. I also want the robot to be able to play games with people. I
think the platform has a lot of potential. I want Google to release a low
power tensor processing unit made for the pi to make this more useful. This
will open up a lot of doors for robot and AI enthusiasts. I'm looking to turn
this into a platform, contact me if this is of interest to you.

~~~
knicholes
I'm extremely interested in using autonomous driving and computer vision for a
lawnmower. I hate mowing my lawn. I hate mowing my lawn enough to program a
robot to mow it for me.

~~~
nitrogen
Since you control the machine and your yard, you can use cameras mounted to
your house for tracking. You don't want smart, you want dumb and predictable.
But good luck making something with a rapidly spinning blade safe while
unsupervised.

It's probably cheaper to hire a landscape maintenance company, or a
neighborhood teenager.

~~~
j_s
_good luck making something with a rapidly spinning blade safe while
unsupervised_

Then don't! If it's autonomous it can be out there all the time rather than
once a week/whatever, no spinning blade needed. Plan B? Buy a goat.

~~~
dualogy
> Buy a goat

Nah. What we _really_ want and need is a robot that while it mows the lawn,
turns it into: its entire energy source, its entire pool of building blocks
for daily (nightly?) self-repairs, for reproduction, for producing oh maybe
fluffy warm wool and delicious milk/cheese/butter as a side product, and
fertilizes the land from the occasional .. discharge resulting from perpetual
energy production-consumption and internal cleanups/repairs, finally as it
still does wear down as all physical assemblages are wont to with time, it
leaves behind highly durable inputs for sturdy clothing and stylish home
decoration (horns, hides, leather etc)!

All from a friggin lawn.

Roboruminant 2.0 baby. Need to reinvent mammalian evolution before we can
_really_ reinvent the wheel!

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madenine
"Google has asked makers to complete a survey about what smart tools would be
"most helpful".

And it suggests tools to aid face and emotion recognition, speech-to-text
translation, natural language processing and sentiment analysis.

Google has previously developed a range of tools for machine learning,
internet of things devices, wearables, robotics and home automation."

That's the meat of it. Google put out a survey - speculation ensues.

~~~
Florin_Andrei
> _Google put out a survey - speculation ensues._

Yes.

This is the actual announcement with the link to the survey at the bottom:

[https://www.raspberrypi.org/blog/google-tools-raspberry-
pi/](https://www.raspberrypi.org/blog/google-tools-raspberry-pi/)

I play with RPis and I make NNs with TensorFlow, so I took the survey. Pretty
standard "tell us what you think" type of thing. If it leads to Google
maintaining an official binary release of TF for the RPi, that would be great.

------
ungzd
The article conveys almost no information. Why speech synthesis, NLP and so on
are called AI? What's special with Raspberry Pi, isn't it a regular general-
purpose computer, just of small size? Will it be run locally or on Google
servers? Why BBC has articles of so poor quality?

~~~
mattoswald
The Pi has exposed IO pins so you can use it to control just about anything
that uses electricity.

There are two basic groups of users. People looking for a cheap small computer
to use for education, gaming, etc. And those who use the Pi as a controller
for other projects.

I'm using one as the controller for an open source coffee maker called Mugsy
as well as another start up in the music education space.

~~~
stickperson
Have the link to Mugsy? Sounds pretty cool.

~~~
mattoswald
Im currently cleaning up the code, models and parts list for public release.
Mailing list subscription is on heymugsy.com. Email is on my profile if you
have specific questions.

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bloaf
Wolfram would probably argue that they've already brought AI to the Raspberry
Pi.

[https://www.wolfram.com/raspberry-pi/](https://www.wolfram.com/raspberry-pi/)

[http://www.wolfram.com/language/11/neural-
networks/](http://www.wolfram.com/language/11/neural-networks/)

------
zython
Kind of an misleading title, nothing is release per se yet.

They've just announced that they might release something ML/AI related in 2017
for the PI.

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reitanqild
Wondering if they just mean providing an api that RPis can use or if they are
somehow going to get meaningful "AI" running on a RPi?

~~~
FilterSweep
Perhaps this is just my overall distrust speaking, but as a RPi hobbyist who
plans to use solid projects such as OpenCV in the near future, I have an
overwhelming fear that Google will release "better" "open-source" projects
that will push out maintainers of the projects we know, all with the intention
of adding their Analytics(TM) in future updates with the stipulation that not
updating your projects introduces you to a Dependency Hell if they work with
other projects you need to add.

~~~
tomcam
...and then drop them silently a few years later? You are such a cynic!

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b1gtuna
Glad I am not the only one who thought the article lacked real info.

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thetrevdev
Tired of seeing this article when the word AI doesn't appear once in the
article and its just an announcement for untold mysteries sometime in the
future....

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mercwear
Off topic but I find it strange that Google is not using it's own survey tool
for the survey link the article (they are using Qualtrics)

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zwieback
Here's another thing in that same vein: [https://www.oreilly.com/learning/how-
to-build-a-robot-that-s...](https://www.oreilly.com/learning/how-to-build-a-
robot-that-sees-with-100-and-tensorflow)

I've been thinking about building a few of these as a class/group project at
work.

~~~
lukas
Hi - I wrote that article - let me know if you build some, I would be excited!

~~~
zwieback
Just saw this - I'm working on getting some internal funding for this idea. We
have some robotics and deep learning SIGs in our company so it might just work
out.

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anfractuosity
Sounds cool! I wonder if this will be with TensorFlow. If so, does the RPis
videocore have any capability to accelerate such things or not out of
interest.

~~~
khedoros1
I know from a few years ago that there was some work at doing GPGPU-type work
on the Raspberry Pi's video hardware. This is a project that I remember
reading about, but didn't look into deeply:
[https://www.raspberrypi.org/blog/accelerating-fourier-
transf...](https://www.raspberrypi.org/blog/accelerating-fourier-transforms-
using-the-gpu/)

There's another one that goes into more detail on the "how" of running other
algorithms: [https://rpiplayground.wordpress.com/tag/raspberry-pi-
gpu/](https://rpiplayground.wordpress.com/tag/raspberry-pi-gpu/)

I'm not sure if there are limitations that would keep it from being
interesting for TF or not; I don't know enough about it.

~~~
anfractuosity
Cheers, the FFT example is especially interesting.

------
awqrre
I don't want Android on my RaspberryPi...

~~~
khedoros1
A lot of people _do_ , though. I don't understand why; there are a _ton_ of
other Android-capable devices already out there to choose from at similar
price and performance levels.

There are a few "Android on the Pi" projects around. They all need work before
they're remotely useable. Frankly, I wish there was at least one high-quality
project to point people to.

~~~
awqrre
> there are a ton of other Android-capable devices

are you talking about the tons of cheap Android phones?

~~~
khedoros1
No, I'm talking about other Pi-like single-board computers and Chromecast-like
"Mini-PCs" and "HDMI-sticks".

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shahbaby
thank you commentators for saving me before I wasted my time reading the
article, this is why I love hacker news

------
general_ai
Since the article doesn't have any information whatsoever, here's my
prediction: by "bringing AI to Raspberry Pi" they mean being able to call
their cloud APIs from there.

TensorFlow is not suitable for anything practical on the Pi. You can certainly
get it to run there, but CPU vector math on resource constrained devices is
not going to be a forte for a framework designed primarily for quickly
iterating over models on a GPU workstation or a multi-GPU server. TF very much
likes to have a very beefy GPU.

~~~
weberc2
You can already call whichever APIs you like from a Raspberry Pi. This
announcement must be about doing something new on the Raspberry Pi (for
instance, compiling TensorFlow to ARM if that isn't already supported).
Perhaps the use-case is a fleet of Raspberry Pis?

~~~
intoverflow2
Like a lot of things on the Pi this might just be a PR stunt and be about as
exciting as a sanctioned way to call APIs.

Remember when Wolfram came to the Pi? Runs too slow to be of use for anyone
but it ships with every copy of raspbian.

>Perhaps the use-case is a fleet of Raspberry Pis?

This would be a waste of money, I know they're cheap but for a space that is
working on GPU power anything CPU based isn't cost effective at all.

~~~
ben_w
This may be a dumb question, but…

The Pi does have a GPU. Nothing amazing, but better than the CPU. Given this
is public knowledge, why is the GPU being ignored in comments like yours?

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Abishek_Muthian
Misleading title, Google hasn't brought AI tools for RPI; they are taking a
survey on what they should bring to the community. Those who are yet to take
survey, be informed it's a long survey. A coffee would be helpful.

~~~
glup
Ya this is a very aggressive use of the present tense.

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g123g
More fake news from BBC.

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fenollp
It'll probably just be a cloud API "look, we can collect more data".

Hopefully it will be an efficient implementation of 1bit-weight NNs like
XNOR.ai (which has been pushing on the research on 8bit & 3bit nets).

ARM SIMD (NEON) is not as great as x86's but this can turn out to work & be
very cache-efficient!

EDIT: for CPUs, at least.

