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I like the idea but I call foul at generalizing this result. > Google's artificial intelligence technology has a considerably higher I.Q. than Apple's Siri vir

I like the idea but I call foul at generalizing this result. > Google's artificial intelligence technology has a considerably higher I.Q. than Apple's Siri virtual assistant, This is device specific, and was done with phones, not home assistants. The google home device might be less intelligent, if it has lower local compute. This is also highly dependent on the quality of the microphone. Finally, I suspect both companies are re-training the 'nets often, so these results are in flux.

neuronexmachina 9y ago
> The google home device might be less intelligent, if it has lower local compute. Other than some minor sound processing, does any of the assistant behavior on either Google Home or phones actually happen locally?
- deleted 9y ago
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- Klathmon 9y ago
  I have no idea about the home, but Google has been "pioneering" (I don't actually know if they are a first here) "federated machine learning". This lets them use a model trained on their systems, but improve it with real usage on the device without needing to send the data back to google. Essentially it's a private version of machine learning that doesn't need to send anything back to the server to still get most of the benefits. I know Google is using it for their "smart replies" and I think in their keyboard app already on phones, so there is a chance they could be applying it more widely to some responses locally on the Home devices.
  - tyingq 9y ago
    I'm curious when this starts to matter. I would guess most normal, non tech, people just don't ask much of these voice devices now. Mostly asking them for countdown timers, weather, playing a song, and maybe a few other things. Not because the devices can't do more, but because the customer isn't expecting them to.
    - Klathmon 9y ago
      Well even for the more "simple" things federated learning can improve the experience. Lower power usage, less latency, and in some cases improved privacy. And some kind of "smart" parsing of voice is still required. I don't like having to say things a specific way to get the machine to understand them, and as the "smart" stuff gets smarter, it gets easier to use even for simple tasks. Before I could ask "whats the weather" and get a generic answer, now I can ask "what's the weather tonight", "what time will it rain", "will it be really cold tomorrow morning", or even "what temperature is it in here" (asking specifically what temperature my indoor temperature is). There is a TON of work that goes into getting all of that to work, but it's not really a "feature" you can point to easily, even though it makes the product significantly better than alternatives. And being able to do all of that without needing the extra latency of a round trip to a google server would be an improvement.
hammock 9y ago
All requests are sent to the cloud for both services, there is no relevant local compute

neuronexmachina 9y ago

> The google home device might be less intelligent, if it has lower local compute. Other than some minor sound processing, does any of the assistant behavior on either Google Home or phones actually happen locally?

deleted 9y ago
[deleted]
Klathmon 9y ago
I have no idea about the home, but Google has been "pioneering" (I don't actually know if they are a first here) "federated machine learning". This lets them use a model trained on their systems, but improve it with real usage on the device without needing to send the data back to google. Essentially it's a private version of machine learning that doesn't need to send anything back to the server to still get most of the benefits. I know Google is using it for their "smart replies" and I think in their keyboard app already on phones, so there is a chance they could be applying it more widely to some responses locally on the Home devices.
- tyingq 9y ago
  I'm curious when this starts to matter. I would guess most normal, non tech, people just don't ask much of these voice devices now. Mostly asking them for countdown timers, weather, playing a song, and maybe a few other things. Not because the devices can't do more, but because the customer isn't expecting them to.
  - Klathmon 9y ago
    Well even for the more "simple" things federated learning can improve the experience. Lower power usage, less latency, and in some cases improved privacy. And some kind of "smart" parsing of voice is still required. I don't like having to say things a specific way to get the machine to understand them, and as the "smart" stuff gets smarter, it gets easier to use even for simple tasks. Before I could ask "whats the weather" and get a generic answer, now I can ask "what's the weather tonight", "what time will it rain", "will it be really cold tomorrow morning", or even "what temperature is it in here" (asking specifically what temperature my indoor temperature is). There is a TON of work that goes into getting all of that to work, but it's not really a "feature" you can point to easily, even though it makes the product significantly better than alternatives. And being able to do all of that without needing the extra latency of a round trip to a google server would be an improvement.

hammock 9y ago

All requests are sent to the cloud for both services, there is no relevant local compute