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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

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.

CommanderData 10y ago
I saw a demonstration (about 2 years ago) of an mobile ARM powered offline voice recognition platform, faster than Google and more accurate. There was a side by side with Google's online voice recognition and it out performed in speed and accuracy on a mobile GPU/CPU. Complete with an actual learning system. That is truer to an AI for the Raspberry Pi, not to mention addressing privacy concerns. If this is a glorified API / Cloud adapter rather than a true AI, what is it really? edit: found it https://www.youtube.com/watch?v=Fwzs8SvOI3Y https://www.youtube.com/watch?v=Fwzs8SvOI3Y
- synaesthesisx 10y ago
  I like the idea of this - doing all the processing/ML client side. I know Apple has started doing this recently (object/scene recognition & search in Photos app), but appreciate that this process occurs on my device rather than on say, Google's servers... I have a strong feeling that quite a bit of R&D has been going toward Apple's upcoming chip, which will likely have a custom GPU architecture optimized for deep learning (of which Siri will also greatly benefit from) and augmented reality - like the custom HPU in Hololens. Apple's "Lens" wearable will probably pair via W1 with an iPhone which will handle most of the processing. Perhaps they'll even have a custom 3D/depth sensor based on the PrimeSense tech they purchased.... We're on the cusp of consumer AR going mainstream, and it's exciting.
hackcasual 10y ago
Bet you're right. I'm sure there's a big market available though for stuff like speech prompting for home automation and image analysis for robotics. Could also be a blended system where there's local object track with remote object identification.
- general_ai 10y ago
  Could be. But I bet this is just a pet project that a couple of engineers do in their spare time, so I wouldn't expect too much from it. I just don't see this as something Larry would care about one iota. And things that Larry doesn't care about tend to eventually die at Google. Case in point: Social.
weberc2 10y ago
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 10y ago
  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 10y ago
    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?
ppod 10y ago
As far as I know since about 2 years ago translation and speech recognition on google phones are done with deep learning systems built into the phone -- a network connection isn't needed. However, I couldn't immediately find a source to verify. Can anyone confirm?
- general_ai 10y ago
  That's not the case. Today's translation and speech recognition systems are considerably larger than even the beefiest phones can sustain. There are some simple OCR models and word (not phrasal) translation systems that run on the device, but not speech recognition.
  - ppod 10y ago
    What are you basing this on? I have a nexus 5 and I just tested it. I turned on airplane mode, and used google translate with speech recognition. Can't quite tell if the translation is phrase based (looks good) and the speech recognition works well.
feelix 10y ago
A raspberry pi is perfectly capable of running inference at around 10 FPS or more easily. You obviously wont do any training on the pi, but low power devices have been used for inference for years now. For example here it is made to run on a phone: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/ios_examples https://github.com/tensorflow/tensorflow/tree/master/tensorf...
- general_ai 10y ago
  "Inference" of what, exactly? And what do you mean by "easily"? None of this stuff is "easy" at the moment.
  - feelix 10y ago
    Inference as in the opposite of training. An example on inference would be feeding it an image and classifying it with a neural net. The example I linked to above has inception running, which classifies things you point the camera into 1000 different categories. It is very easy to set up (I have done it, and it only took a few minutes)
    - general_ai 10y ago
      :-) I know what inference is. It's just that the speed of inference very much depends on the model you're doing the forward pass on, and the phrase "inference can be run at 10fps" is non-sensical without also specifying the model.
      - deleted 10y ago
        [deleted]
      - feelix 10y ago
        That is false. A raspberry pi is capable of running inference on 90% of the models out there.
        10y ago

CommanderData 10y ago

I saw a demonstration (about 2 years ago) of an mobile ARM powered offline voice recognition platform, faster than Google and more accurate. There was a side by side with Google's online voice recognition and it out performed in speed and accuracy on a mobile GPU/CPU. Complete with an actual learning system. That is truer to an AI for the Raspberry Pi, not to mention addressing privacy concerns. If this is a glorified API / Cloud adapter rather than a true AI, what is it really? edit: found it https://www.youtube.com/watch?v=Fwzs8SvOI3Y https://www.youtube.com/watch?v=Fwzs8SvOI3Y

synaesthesisx 10y ago
I like the idea of this - doing all the processing/ML client side. I know Apple has started doing this recently (object/scene recognition & search in Photos app), but appreciate that this process occurs on my device rather than on say, Google's servers... I have a strong feeling that quite a bit of R&D has been going toward Apple's upcoming chip, which will likely have a custom GPU architecture optimized for deep learning (of which Siri will also greatly benefit from) and augmented reality - like the custom HPU in Hololens. Apple's "Lens" wearable will probably pair via W1 with an iPhone which will handle most of the processing. Perhaps they'll even have a custom 3D/depth sensor based on the PrimeSense tech they purchased.... We're on the cusp of consumer AR going mainstream, and it's exciting.

hackcasual 10y ago

Bet you're right. I'm sure there's a big market available though for stuff like speech prompting for home automation and image analysis for robotics. Could also be a blended system where there's local object track with remote object identification.

general_ai 10y ago
Could be. But I bet this is just a pet project that a couple of engineers do in their spare time, so I wouldn't expect too much from it. I just don't see this as something Larry would care about one iota. And things that Larry doesn't care about tend to eventually die at Google. Case in point: Social.

weberc2 10y ago

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 10y ago
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 10y ago
  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?

ppod 10y ago

As far as I know since about 2 years ago translation and speech recognition on google phones are done with deep learning systems built into the phone -- a network connection isn't needed. However, I couldn't immediately find a source to verify. Can anyone confirm?

general_ai 10y ago
That's not the case. Today's translation and speech recognition systems are considerably larger than even the beefiest phones can sustain. There are some simple OCR models and word (not phrasal) translation systems that run on the device, but not speech recognition.
- ppod 10y ago
  What are you basing this on? I have a nexus 5 and I just tested it. I turned on airplane mode, and used google translate with speech recognition. Can't quite tell if the translation is phrase based (looks good) and the speech recognition works well.

feelix 10y ago

A raspberry pi is perfectly capable of running inference at around 10 FPS or more easily. You obviously wont do any training on the pi, but low power devices have been used for inference for years now. For example here it is made to run on a phone: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/ios_examples https://github.com/tensorflow/tensorflow/tree/master/tensorf...

general_ai 10y ago
"Inference" of what, exactly? And what do you mean by "easily"? None of this stuff is "easy" at the moment.
- feelix 10y ago
  Inference as in the opposite of training. An example on inference would be feeding it an image and classifying it with a neural net. The example I linked to above has inception running, which classifies things you point the camera into 1000 different categories. It is very easy to set up (I have done it, and it only took a few minutes)
  - general_ai 10y ago
    :-) I know what inference is. It's just that the speed of inference very much depends on the model you're doing the forward pass on, and the phrase "inference can be run at 10fps" is non-sensical without also specifying the model.
    - deleted 10y ago
      [deleted]
    - feelix 10y ago
      That is false. A raspberry pi is capable of running inference on 90% of the models out there.
      - 10y ago