If you think chatbots are hot right now -- being used in psychotherapy, turning into racist trolls, and presenting an existential threat to Apple -- just wait until they turn into full-fledged personal assistants. In five years time, digital personal assistants will even more important than your smartphone, says University of Washington computer scientist Pedro Domingos, author of "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World." "What you have right now on your smartphone is dozens of apps," Domingos tells Tech Insider, "with each app doing it's own thing." On any given Friday night, you use one app to find a restaurant, another to buy a movie ticket, another to figure out how to get to where you're going, and another to find a date to take out with you. "It's incredibly annoying," he says, since the apps "don't talk to each other and you have to learn all these different interfaces."

We hear about AI taking over our jobs. We hear about AI listening in on our conversations. We hear about AI becoming a substitute for our romantic partners. Here's what the real AI experts Guru Banavar, (IBM), Toby Walsh, (The University of New South Wales), and Roman Yampolskiy (University of Louisville), say about the subject, and why a lot of what you think you know is probably wrong. In 2015, GE inaugurated a new, Multi-Modal manufacturing facility in Chakan, India.

For artificial intelligence, 2016 has been called "like 2015 on steroids." Want to learn more about what that really means? Follow these 10 twitter users for an insider's take on the latest developments in AI. The brains behind Google's AI platform DeepMind, Hassabis is arguably one of the most important voices in the AI world today. AlphaGo, created by DeepMind, has surpassed expectations, winning in the game of Go ten years before experts predicted.

Advertising and media are often at the forefront of new technology, and we have already seen augmented reality platforms showing content in the real world and a virtual reality advertising network for brands. Now an artificial intelligence robot, AI-CD?, developed by Japanese advertising and marketing agency McCann Japan, is set to work on providing new creative direction for commercials. The AI will give input on projects, mining and analyzing creative databases of adverts to find the best commercials for products and messages. But the robot is also being treated as somewhat part of the team at McCann, taking the title of "creative director" and attending the opening ceremony for new company employees. McCann Japan CEO Yasuyuki Katagi said: "Artificial intelligence is already being used to create a wide variety of entertainment, including music, movies, and TV drama, so we're very enthusiastic about the potential of AI-CD? The whole company is 100 percent on board to support the development of our AI employee."

Mauro Maggioni has been named the Bloomberg Distinguished Professor of Data Intensive Computation at Johns Hopkins in the Krieger School of Arts and Sciences' Department of Mathematics and the Whiting School of Engineering's Department of Applied Mathematics and Statistics. He will join Johns Hopkins from Duke University, where in 2012 he was promoted from assistant professor to full professor of mathematics, electrical and computer engineering, and computer science. Maggioni is the 20th Bloomberg Distinguished Professor appointed across Johns Hopkins. The professorships are supported by a 350 million gift to the university by Johns Hopkins alumnus, philanthropist, and three-term New York City Mayor Michael R. Bloomberg. The majority of this gift is dedicated to creating 50 new interdisciplinary professorships, galvanizing people, resources, research, and educational opportunities to address major world problems.

I deal with machine learning and web graphs analysis (mostly in theory). I also work on the development of Big Data products for one of the mobile operators in Russia. It's the first time I write a post, so please, don't judge me too harshly. Nowadays, a lot of people want to develop efficient algorithms and take part in machine learning competitions. So they come to me and ask: "Where to start?".

Last episode, we treated our Decision Tree as a blackbox. In this episode, we'll build one on a real dataset, add code to visualize it, and practice reading it - so you can see how it works under the hood. And hey -- I may have gone a little fast through some parts. Just let me know, I'll slow down. Also: we'll do a Q&A episode down the road, so if anything is unclear, just ask! Subscribe to the Google Developers: http://goo.gl/mQyv5L

Google announced an update to its open-source framework TensorFlow that will now run training process for creating machine learning models over hundreds of machines aligned. According to The Verge, Google opened up its TensorFlow last year for companies that wants to build their own artificial intelligence application using the same open-source library the search engine applies to power everything from photo analytics and automated email replies. Google tried extending its platform to other computer servers by publicly releasing a version that could only run a single machine. Now, Google has updated a new version of TensorFlow with a feature that will enable to run distributed computing across multiple machines at the same time. Engineering leader of TensorFlow Rajat Monga said the reason why TensorFlow's multi-server version was delayed for release because they found it difficult to adapt the open-source software to be usable outside of the highly customized data centers of Google.

Today, there are 4.4 million taxis globally. In 2020 this number is expected to reach 5.5 million. Once the commercialization of autonomous driving kicks in, the taxi market has the potential to double. This would allow for mobility to become a commodity or a service, which could compete with public transport. Similarly, commercial transport will be affected by AI.

E-Commerce has exploded in recent years, with consumers choosing to make many of their purchases online in favor of traveling to brick-and-mortar locations. However, there are many retail sectors where consumers still prefer to buy in-person, even if their pre-purchase research is largely aided by online channels. Apparel is one area that fits this pattern, with consumers wanting to try on sizes, see how the products actually look, and wear them to ensure an adequate level of comfort. In addition, consumers of specialty retailers enjoy the in-store experience due to the knowledgeable sales associates who are able to educate them and guide them towards relevant products and services. For this reason, many retailers have struggled to match the online shopping experience with the traditional brick-and-mortar shopping experience.