I'm often amazed how Google still gives it staff this unique hacker-like approach to their million dollar projects.
For example, the stuff in Google labs (gmail) has had some silly things like don't hit send when you're drunk but sometimes very useful features which may be considered unorthodox like "Gmail telling you when it thinks you wanted to attach a file but forgot".
It's something I wouldn't generally associate with a very corporate design but here they are wanting to add another silly feature and who knows how it will turn out? Maybe it will be super useful and then all the other companies will start to copy it.
But the thing is they're inventing new ways that really don't fit your product development roadmaps. I really like that about them.
I had a similar thought with Apple -- El Cap has a feature where if you shake your mouse around, the cursor will momentarily grow in size so you can find where it is.
That does not feel like a top-down design idea, but a bottom-up feature designed by an engineer who was sick of those moments where he/she had lost the cursor.
While I'm sure some great hackers worked on Smart Reply, I don't think it's the result of the process you imagine. Smart Reply is using really sophisticated machine learning to advance one of Google's core goals, which is the creation of an AI and autonomous agents. A chatbot like the kind that finds a response to email is just the first shoe to drop.
I like the attachment recommendation thing and it can be useful but what I find ridiculous is that they still have yet to recommend that you use the correct from address when sending an email to your work contacts. I have about 15 email address that I can send from. If any recipients are in the x.com domain and I am not sending it from my x.com account it should alert me. Better yet, it should just switch the from address for me. This feature has been requested for years now.
"Gmail telling you when it thinks you wanted to attach a file but forgot" is hardly unorthodox considering Outlook has had it for years. That said, the other experiments do seem very informal and fun.
I appreciate the privacy standards they used (no humans reading your email to develop this), but am concerned that it's not enough. As I understand with language models, overfitting takes the form of returning a sequence of words seen in the training set. If this is overfitting in any part of the response space, this could happen. Out of a million emails, how many suggested responses are going to substantively resemble another response the original author wouldn't want read by others?
Much of this strikes me as a "just because you can, doesn't mean you should" issue. Google clearly loves machine learning and doing cool things but I think lately they've been taking it too far.
For example; after purchasing a book on Amazon recently I happened to do a Google search on that book and the first thing I see is, "Your book is scheduled to be delivered on..." Aside from the creepy factor I'm left wondering what purpose this serves? I just ordered the book. I KNOW it's on its way.
Turns out they just mined my emails from Gmail to provide it in search results.
I'm sure some developer or product manager thought it would be a cool thing to do without giving any consideration to usefulness much less user privacy. I really don't feel like Google needs to know what I'm buying thankyouverymuch. Gmail account: closed.
But you have a lot more to go off here and the number of replies is limited to maybe a few thousand at most. It can quickly determine if it's a scheduling email, check your calendar, and generate responses like "I am available" and "I'm busy". For others it can be as simple as "I'll check it out and get back to you". Finally, if you are expected to review the automatically composed response or choose from several options it's actually not that bad at all. This actually seems a lot like the iOS feature where if you miss hang up on an incoming call you can send a quick SMS reply back saying things like "I'll call you back" or automatically adding a reminder to call back in an hour.
Overfitting requires "memorizing" the dataset, instead of generalizing it. I think that's very very unlikely. The neural network parameters can only store so many bits of information. But the dataset is millions of times bigger.
This kind of stuff is really cool. I imagine the future of Google being the same old search box, but instead of entering a search query, you engage in a conversation with Google so you can delve deeply into a narrow topic and get back tailored responses to your question (as opposed to opening 10 tabs of Stack Overflow links that are maybe related to your question).
I worry a bit about the long-term risks of this kind of training (query / reply). While this is obviously very far from being "high resolution" enough to single out very specific information, at some point these kinds of tools (and assistant AIs that can answer questions) will out of necessity be able to converse around very domain specific topics. At this point, how do they know what data is private and what is not? It could be tempting to train these AIs on chat logs or e-mail conversations, but that'd give them knowledge of very private information which they might leak to others. Even if they're limited to data that is accessible anonymously, they'd be extremely good at picking up information that wasn't intended for the public. For example, if you could describe a person called /u/andreasblixt on reddit, and leave it up to the bot to put the pieces together that this person is also on Facebook, Twitter, etc... and that obscure forum from 10 years ago. Food for thought.
A final thought on this... When these assistant AIs will inevitably have to know something about you. For example, your preferred schedule, food restrictions, preferred airlines, name, family, friends, phone numbers, where you were last night, who you've talked to, etc. Even if we all get our own namespaced AI assistant (i.e., the trained neural network that contains private information is stored and encrypted for your access only), that assistant's "brain" may very well become a prized target because if you get access to it you can interrogate it for information (you most likely can't just access the information in any meaningful way – you'd literally have to give it queries to make it return semantic output with the information you're trying to access).
I just started reading Avogadro Corp (http://www.amazon.com/Avogadro-Corp-Singularity-Closer-Appea...) this weekend, and this reminds me quite a lot of the emergent AI that figures heavily in the story (ELOPe). A quick synopsis: developers build a system to "improve" responses from emails. The system at some point is given the ability to send emails on its own, and a poorly issued directive. It's been an engaging read so far, and fairly hilarious since the corporation in the book is very obviously based on Google.
Hey, remember that one time when this feature was Gmail's April Fools Day joke[1]? Kind of funny how it's now a serious and actually useful-looking product.
Gmail itself was a sort of a serious April Fools joke. It was launched on April 1st, 2004 and because it offered 1GB of free storage when other providers were offering ~5MB, a lot of people assumed it was a hoax.
While the technology is very cool, this pushes me that much closer to a "dumber" email service. It's always a conflict for me as I love shiny new things, but I'd rather we let AI loose on someone else's email, especially when the AI's revenue stream is advertising (a business predicated on knowing as much as possible about your audience).
I don't think I understand your reasoning. You're already tolerating an AI processing your email to produce the ads, so assuming that, why does a cool new feature push you closer towards a "dumber" service?
advertising becomes scary when this service tries to suggest responses like "Yes, let's have a meeting tomorrow and why not enjoy a refreshing glass of ice-cold Dr.Pepper together!". But if not, I'm not that worried about the ad revenue aspect.
You can make gmail "dumber" by using the IMAP api and then encrypt your email? Unless you use google apps for work since you aren't paying for the service you are the product.
I kept imagining it would generate responses based on MY past emails until the end of the article. Example "When does your flight leave for Paris?", I was imagining it would pull the info from Google Now to reply "Friday at 9am", but I don't think it is built for this type of specific question.
> The solution was provided by Sujith Ravi, whose team developed a great machine learning system for mapping natural language responses to semantic intents. This was instrumental in several phases of the project, and was critical to solving the "response diversity problem": by knowing how semantically similar two responses are, we can suggest responses that are different not only in wording, but in their underlying meaning.
Does anyone know where I can find out more about this? A paper or something maybe?
This looks more powerful than iOS's context sensitive keyboard, but that also looked impressive when demoed. It will be interesting to try this out with real-world emails and see how well it works in practice.
This gets really exciting when implemented on a smartwatch. Single tap responses that are actually useful would make smartwatches significantly more powerful. Speech recognition is great but it's not always appropriate for social environments.
I have a concern that is somewhat related to this issue. I've been wanting to play around with doing NLP in the client using the SpeechRecognition API available in Chrome. It typically gives pretty good results for simple recognition purposes, but there is not yet any way to specify an arbitrary grammar for the backend service to use. This is a big deal when someone wants to be able to recognize a name spelled like "Bobbie" rather than "Bobby". The W3C Web Speech spec currently allows for setting arbitrary grammars, but it isn't implemented. I'm just saying it would be cool if some of you AI geniuses at Google could help me out on that front.
You can play around with the dumb little AI app that I've been working on that does a little bit of NLP in the browser. Check out this site with Chrome: https://yc-prototype.appspot.com. His name is Bertie. You should see his face on the bottom of the page. The site works like an OS in your browser.
Interesting. I used a sequence to sequence methodology about 10 years ago in a chatbot that won in a self-learning competition ... of course never had the data available that google has.
A bot like that is a great tool to experiment with NLP and ML ideas. This is really an intriguing area of research.
When you receive a call today, you are already prompted with auto response messages such as 'I'm busy, I'll call you back.' This seems like the natural next step.
> But replying to email on mobile is a real pain, even for short replies.
Imo, this has already been solved. I just whisper replies into my watch for both email and SMS. Google's voice recognition is finally good enough for this. I can't think of anything more convenient.
I'm not sure if AI-ish replies are something I'm interested in. Throwing complex fuzzy logic at what should be a hardware/interface problem seems shortsighted. I prefer a much higher level of granular control, especially if these messages are work related.
[+] [-] supersan|10 years ago|reply
For example, the stuff in Google labs (gmail) has had some silly things like don't hit send when you're drunk but sometimes very useful features which may be considered unorthodox like "Gmail telling you when it thinks you wanted to attach a file but forgot".
It's something I wouldn't generally associate with a very corporate design but here they are wanting to add another silly feature and who knows how it will turn out? Maybe it will be super useful and then all the other companies will start to copy it.
But the thing is they're inventing new ways that really don't fit your product development roadmaps. I really like that about them.
[+] [-] mmanfrin|10 years ago|reply
That does not feel like a top-down design idea, but a bottom-up feature designed by an engineer who was sick of those moments where he/she had lost the cursor.
[+] [-] vonnik|10 years ago|reply
[+] [-] MichaelGG|10 years ago|reply
Sure, if you use the word thinks. If you instead say "if msg.Contains "attach" then warn" it's not that impressive.
The feature in the article is a bit more than a single if.
[+] [-] davidw|10 years ago|reply
That one's not that hard.
http://marc.info/?l=mutt-dev&m=95685122323646&w=2
[+] [-] dexterdog|10 years ago|reply
[+] [-] dingo_bat|10 years ago|reply
[+] [-] ikeboy|10 years ago|reply
[+] [-] imh|10 years ago|reply
[+] [-] Zelphyr|10 years ago|reply
For example; after purchasing a book on Amazon recently I happened to do a Google search on that book and the first thing I see is, "Your book is scheduled to be delivered on..." Aside from the creepy factor I'm left wondering what purpose this serves? I just ordered the book. I KNOW it's on its way.
Turns out they just mined my emails from Gmail to provide it in search results.
I'm sure some developer or product manager thought it would be a cool thing to do without giving any consideration to usefulness much less user privacy. I really don't feel like Google needs to know what I'm buying thankyouverymuch. Gmail account: closed.
[+] [-] IgorPartola|10 years ago|reply
[+] [-] Houshalter|10 years ago|reply
[+] [-] andrewtbham|10 years ago|reply
[+] [-] blixt|10 years ago|reply
I worry a bit about the long-term risks of this kind of training (query / reply). While this is obviously very far from being "high resolution" enough to single out very specific information, at some point these kinds of tools (and assistant AIs that can answer questions) will out of necessity be able to converse around very domain specific topics. At this point, how do they know what data is private and what is not? It could be tempting to train these AIs on chat logs or e-mail conversations, but that'd give them knowledge of very private information which they might leak to others. Even if they're limited to data that is accessible anonymously, they'd be extremely good at picking up information that wasn't intended for the public. For example, if you could describe a person called /u/andreasblixt on reddit, and leave it up to the bot to put the pieces together that this person is also on Facebook, Twitter, etc... and that obscure forum from 10 years ago. Food for thought.
A final thought on this... When these assistant AIs will inevitably have to know something about you. For example, your preferred schedule, food restrictions, preferred airlines, name, family, friends, phone numbers, where you were last night, who you've talked to, etc. Even if we all get our own namespaced AI assistant (i.e., the trained neural network that contains private information is stored and encrypted for your access only), that assistant's "brain" may very well become a prized target because if you get access to it you can interrogate it for information (you most likely can't just access the information in any meaningful way – you'd literally have to give it queries to make it return semantic output with the information you're trying to access).
Anyway, automatic e-mail responses, yay!
[+] [-] Natanael_L|10 years ago|reply
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[+] [-] rcthompson|10 years ago|reply
[1] https://www.gmail.com/mail/help/autopilot/
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[+] [-] mattgmg|10 years ago|reply
* This is an automated response
[+] [-] hokkos|10 years ago|reply
[+] [-] keshav57|10 years ago|reply
Does anyone know where I can find out more about this? A paper or something maybe?
[+] [-] OkGoDoIt|10 years ago|reply
This gets really exciting when implemented on a smartwatch. Single tap responses that are actually useful would make smartwatches significantly more powerful. Speech recognition is great but it's not always appropriate for social environments.
[+] [-] alphydan|10 years ago|reply
Is it trained mostly on personal gmail accounts?
[+] [-] denniskane|10 years ago|reply
You can play around with the dumb little AI app that I've been working on that does a little bit of NLP in the browser. Check out this site with Chrome: https://yc-prototype.appspot.com. His name is Bertie. You should see his face on the bottom of the page. The site works like an OS in your browser.
[+] [-] novalis78|10 years ago|reply
A bot like that is a great tool to experiment with NLP and ML ideas. This is really an intriguing area of research.
https://thinkingai.wordpress.com/
[+] [-] julianozen|10 years ago|reply
[+] [-] tabrischen|10 years ago|reply
[+] [-] alttab|10 years ago|reply
[+] [-] drzaiusapelord|10 years ago|reply
Imo, this has already been solved. I just whisper replies into my watch for both email and SMS. Google's voice recognition is finally good enough for this. I can't think of anything more convenient.
I'm not sure if AI-ish replies are something I'm interested in. Throwing complex fuzzy logic at what should be a hardware/interface problem seems shortsighted. I prefer a much higher level of granular control, especially if these messages are work related.
[+] [-] jes5199|10 years ago|reply
[+] [-] gosub|10 years ago|reply
[+] [-] lwf|10 years ago|reply
[+] [-] jasonmorton|10 years ago|reply