It gives suggestion on reply message. I use it a lot.
NLP can be use in informational retrieval such as organizing things into cluster of topics via LDA.
I've met someone with the mindset that AI is a fad and that what have it done so far? I disagree, it may be over hype but I see that person using Siri. I use Hello Google and I consider that to be NLP not the traditional statistic NLP but the deep learning NLP kind.
Also those website translator such as google translator and old school babel translate helped me a lot when I was trying to search for things that were in Japanese. There were a few famous Korean and Chinese novels that are machine translated and it's decent enough to read if you're really into that novel and willing to ignore the quality.
https://www.blog.google/products/gmail/subject-write-emails-...
I really need to poke around the settings and see if it can be disabled...
Keep in mind features like this are built around the needs of the people who make it. Outlook is sort of a snapshot of the needs of a Microsoft employee circa 1996. GMail is a little better, but is still of reflection of the company.
https://hnprofile.com/author_profiles?utf8=&search=julienres...
This can be used to great effect in companies. Essentially, we deploy a search engine for tribal knowledge in a company. Overall, we see significant improvements company wide. Reduced turnover and in turn improved knowledge retention
So have you already started analyzing word patterns and finding different accounts people have on the same service and also correlating them between multiple services?
People do leave much more information about themselves on the internet than they realize.
https://twitter.com/austingwalters/status/104189476543920128...
I don’t make that available and personally think that’s a bit too intrusive
And got back
“My name is Proposal”
Theoretical research of these subjects it's not like an open-source project used in industry: "who's using this tool to do x, y and z?". The output of NLP research is the combination of thousands of various papers that, all combined, makes something like a siri search possible.
Alexa and particularly Google Assistant are much better, the latter retaining context between questions e.g: "who is the 44th president of the US" followed by "who is his wife?" is a neat trick.
https://developer.amazon.com/blogs/alexa/post/15bf7d2a-5e5c-...
But Apple just took 2 famous Google AI researcher. So it seems that Apple is trying to catch up.
https://last10k.com/sec-filings/vnce/0001564590-19-011520.ht...
It works fairly well, albeit not perfectly at this point.
[1] - https://deepmode.app
Sentiment Analysis (get the tonality from the entire text or the tonality from specific parts of the text)
Disclaimer I work at a web application / API text analytics company: https://gavagai.io/
Here are a Quora post my CTO speaks more about our tool and analyzing survey text data.
https://www.quora.com/Whats-an-automatic-efficient-way-to-an...
https://www.quora.com/What-is-the-best-approach-to-quantify-...
* https://www.grammarly.com/ is pretty interesting. Corrects your grammar and not just your syntax
* Swype keyboard which uses your spelling corrections as a way to better figure out how you use a swype keyboard
* https://flexibits.com/fantastical and many other calendar apps do NLP stuff to pull out meeting info. Microsoft, Google and Facebook do this kind of stuff pretty well (Disclosure: I worked on such features at Microsoft)
Happy to give more examples if people are interested in working in this space.
The Chatbot stuff is more questionable, especially the ones based on deep neural nets ( again I've published in this domain so I looked at it pretty closely ).
Twitter/FB/Douyin/Google all use NLP to tune their feed or give you search results.
Just to give you some examples...
As @anthony_doan mentioned, this is something that is actively being used by consumers and companies.
(Disclaimer: I work on DeepL translator)
Though I'm not personally a regular user, from what I've observed, the AI is able to very, very efficiently resolve a significant number of requests because a lot of the messaging is the same: "what's the wifi?" "bring me towels" "can i get my car?" etc.
The application of NLP for a niche industry has felt particularly appropriate for a small startup where in contrast, doing generic NLP really feels like a boil the ocean type strategy that makes more sense to those who have the resources (google/apple).
Photo Recall is an Amazon Alexa and Google Assistant app that lets you retrieve Unsplash photos by voice plus photo slideshows created with Custom Voice Commands can be viewed from your Amazon Echo Show or Google Home Hub (or via the Google Assistant app).
All voice recognition and text prediction is a result of nlp. Every time you search on google, or say “hey Siri/Alexa”. Every time you call an automated service and it asks you why you’re calling and connects you to the right department. When you type a text message and it completes a word and predicts the next one. It affects what ads you get shown. It lets companies automatically block negative reviews with sentiment analysis (not always used for good). Or to quickly find where supplies are needed in emergencies by parsing twitter feeds in all languages. Etc.
If you own a smartphone, you interact with nlp technologies dozens of times per day. So yeah, it’s good and useful.
Our website: https://landria.io
https://chrome.google.com/webstore/detail/emma-by-bunchai-ne...
They are a great service to restaurants and use NLP to automate a lot of service integration such as between the embedded POS system and delivery companies.
In that same vein, I've seen companies that have "chat support" use NLP bots to get a feel for the type of question a person is looking for before handing off to a human support person.
I've also seen AI personal assistants that handle meeting schedules etc like https://x.ai/