Now you can use Chatbots to get news and information in a personalized pattern. Famous media companies like CNN and Fox news have already launched their News Chatbot on platforms like Facebook Messenger, Line and Kik as well as on voice-activated devices like Amazon's Alexa. Facebook has unveiled new capabilities for businesses and publishers on Messenger, enabling users to chat with CNN to get breaking news and personalized stories. People will now be able to chat with the companies and publishers like they would do with their friends. CNN is using chatterbots for Facebook Messenger to interact with users in a natural and human-like way.
Google Home may have only been living with us for a short time, but it's quickly becoming our favorite thing in the house. And now it's starting to play a little nicer with the other things we love, with Netflix and Google Photos support beginning to roll out to users. First spotted by Android Police, the update brings a new Videos and Photos tab to the Google Home app's Assistant settings, inside which you will see options for linking your Netflix account and enabling Google Photos. As described in the app, the new features, which require a separate Chromecast and Netflix subscription, will allow users to stream photos to their TV and "play shows and movies by asking your Assistant." Last week, Google announced it was opening its Actions on Google platform, allowing developers to tap directly into the digital assistant to bring voice commands for things like food ordering, news, and shopping, as well as enabling two-way conversations with the device.
During SXSW 2015, many Tinder users matched with a woman they assumed was real. They had conversations her, which seemed to flow naturally. But she was a chatbot, promoting the Alex Garland film Ex Machina. Some who fell for it called it deceptive, but it also opened up what movie promotion could be, and how deeply bots could engage with fans. Chatbots have already infiltrated social media, shopping, small business, advertising, music festivals, and Werner Herzog.
The company is opening its voice-enabled Assistant to developers who can start creating "actions" for the device. Early partners will include media companies like NBC News, Buzzfeed and NPR, as well as consumer apps like Quora, Genius and Todoist. SEE ALSO: Google's data centers, offices will use 100% renewable energy in 2017 The idea is similar to the "skills" developers create for Amazon's Echo line: companies can create "Conversation Actions" that link their services to Google Assistant on Home. Using the actions created by Domino's, for example, you can ask Google Assistant to order you a pizza, or ask for the latest CNN headlines. Unlike Alexa's skills that have to be manually enabled, Google notes that once developers create a conversation action, they're automatically available.
Data scientists are always stressing over the "best" approach to variable selection, particularly when faced with massive amounts of information -- a frequent occurrence these days. "Massive" by today's standards means terabytes of data and tens, if not hundreds, of millions of features or predictors. There are many reasons for this "stress" but the reality is that a single, canonical solution does not exist. There are as many approaches to selecting features as there are statisticians since every statistician and their sibling has a POV or a paper on the subject. For years, there have been rumors that Google uses all available features in building its predictive algorithms.
"The aim of marketing is to know and understand the customer so well the product or service fits him and sells itself." Anyone who shops online or uses a music streaming service will have experienced recommendations. Their accuracy can be surprising at first glance, but these recommendations aren't made by accident. They are based on sophisticated machine learning techniques, pattern analysis and automated decision making. Systems like these rely on a technology infrastructure that can import, analyse and interpret huge volumes of data and take appropriate action without the need for human intervention.
Reviewing a product designed to learn over time is like reviewing a newborn baby. So much functionality is dependent on artificial intelligence and machine learning, the only certainty is that it'll get smarter over time. Who knows what it'll end up being: A jack-of-all-trades? Or maybe just a creeper that records everything you say? At birth, it didn't have the ability to order you Domino's, play Spotify playlists, or get things from Amazon Prime.
The companies have integrated the automation technology into Watchwith's data-driven advanced advertising products. "What used to potentially require thousands of man-hours is now an automated process within the Watchwith platform," Watchwith says in a statement. By embedding artificial intelligence into the video advertising inventory creation process, Watchwith MAF gives TV networks and premium video publishers the power to create, manage and sell contextually relevant native video advertising at scale. "And the result is the highly scalable, native digital video advertising solution the TV industry needs to compete with Facebook, YouTube, Snapchat and other native digital video distribution platforms."