Yesterday, Google said that an unspecified bug was delaying the Android Wear 2.0 rollout yet again. It looks like the delay hasn't been too severe though. The company says that Wear 2.0 is now available for five more watches: the Polar M600, Nixon Mission, Fossil Q Wander, Fossil Q Marshal and Michael Kors Access. That's in addition to the Fossil Q Founder, Casio Smart Outdoor Watch WSD-F10 and TAG Heuer Connected, which Google said were already receiving the update. All told, that's almost half of the 19 older watches that'll get the Wear 2.0 update.
It's a shame the Android Wear 2.0 rollout has been so challenging -- many, many other devices won't ever receive the update. Those that are getting it have had to wait a long time, too, but it seems like it won't be too long until the whole group gets the new software. It makes the platform a lot better, though smartwatches remain a niche. If you really want Wear 2.0, though, your best bet is probably checking out one of LG's newest smartwatches.
Android Wear 2.0 uses offline AI for its smart replies
One of the new features on Android Wear 2.0 is Smart Reply, which suggests responses to messages that you can quickly tap if you're busy doing something else. In its research blog, Google explained that the feature uses on-device machine intelligence, so it works even if you don't have an internet cloud connection. While the researchers initially thought doing that would be impossible, the "Expander" AI team saw it as a unique opportunity.
"[We] returned to the drawing board to design a completely new, lightweight, machine learning architecture -- not only to enable Smart Reply on Android Wear, but also to power a wealth of other on-device mobile applications," the team wrote.
It tried using current neural net tech and so-called graph learning, but the models didn't fit on a smartwatch and attempts to limit the number of replies "did not produce useful results," they wrote. In an attempt to make it more compact, the researchers built a simpler system that groups messages requiring a similar responses, like "Hey, how's it going?" and "How's it going buddy," rapidly and with a low memory hit.
From there, it uses "semi-supervised graph learning" that checks your replies to messages, word and phrase similarity and other factors to predict the best possible replies. The entire model, including the training, resides and performs "completely on device," the team notes. "The model can also be adapted to cater to the user's writing style and individual preferences to provide a personal experience."
The researchers were surprised at how well it works on Android Wear devices, which aren't renowned as computing powerhouses, and plans to use the AI algorithms behind it to "enable completely new applications in the months to come." As with Google's very similar Gmail-based smart replies, however, be sure to only use it when needed -- even with AI smarts, the person on the other end can tell it's not you.