He's a lightning-fast learner, he speaks eight languages and he's considered an expert in multiple fields. He's got an exemplary work ethic, is a speed reader and finds insights no one else can. On a personal note, he's a mean chef and even offers good dating advice. Named after IBM's first CEO, Watson was born back in 2007 as part of an effort by IBM Research to develop a question-answering system that could compete on the American quiz show "Jeopardy." Since trouncing its human opponents on the show in 2011, it has expanded considerably.

IBM Watson is known for its work in identifying cancer treatments and beating contestants on Jeopardy! But now the computing system has expertise in a new area of research: neuroscience. Watson discovered five genes linked to ALS, sometimes called Lou Gehrig's disease, IBM announced on Wednesday. The tech company worked with researchers at the Barrow Neurological Institute in Phoenix, Arizona. The discovery is Watson's first in any type of neuroscience, and suggests that Watson could make discoveries in research of other neurological diseases.

The holiday season is upon us and, for many, this represents the most hectic shopping period of the year. Whether you're navigating crowded shopping centers or debating what gifts to buy, the in-store experience can be particularly overwhelming. To help shoppers better manage their holiday shopping needs, we've teamed up with IBM to pilot Watson-enabled mobile concierges at both Mall of America, the largest commercial shopping center in the US, and Fashion Island, a coastal shopping destination in southern California. Mall of America's "E.L.F." and Fashion Island's "At Your Service" tap into the IBM Watson Conversation API to analyze shoppers' inquiries and help them plan more personalized in-store shopping visits right from their fingertips. These solutions follow the success of our first pilot with Macy's called "Macy's On Call and illustrate how the simplicity of building with Watson's language APIs, particularly Watson Conversation, has enabled us to expand our technology in more meaningful ways to more shoppers.

Artificial intelligence is getting a kickstart for the holiday season with an elf-themed chatbot launching at Mall of America. E.L.F, or Experiential List Formulator, is an IBM Watson-enabled platform, created in collaboration with Watson developer partner Satisfi, which helps visitors plan a more personalized shopping experience. It understands and interprets their queries using the Watson Conversation API and AlchemyLanguage API, both through Facebook Messenger or online on mobile and desktop via elf.mallofamerica.com. Visitors to the shopping center in Bloomington, MN, are guided through a series of questions from E.L.F to understand things like how much time they have and what activities they prefer. The service then presents them a series of suggestions, including ideal stores, theme park rides and shows.

The year 2017 is predicted to be that of Artificial Intelligence (AI) and machine learning -- redefining the way humans communicate with devices to not only improve daily life but also boost businesses, even in India. To make this happen, here comes IBM Watson -- a cognitive system enabling a new partnership between people and computers. Named after IBM founder Thomas J. Watson, the supercomputer combines AI and analytical software for optimal performance as a "question answering" machine that thinks like a human. For IBM, cognitive is digital business plus digital intelligence. With Watson, people can analyse and interpret all of their data, including unstructured text, images, audio and video.

Disruption ahead: Deloitte's point of view on IBM Watson8 9. What makes Watson unique In technical terms, IBM Watson is an advanced open-domain question answering (QA) system with deep natural language processing (NLP) capabilities. At this point, the Watson Software as a Service (SaaS) platform is most effectively used to sift through massive amounts of text--documents, emails, social posts, and more--to answer questions in real time. Watson accepts questions posed by the user in natural language and provides the user with a response (or a set of responses) by generating and evaluating various hypotheses around different interpretations of the question and possible answers to it. Unlike keyword-based search engines, which simply retrieve relevant documents, Watson gleans context from the question to provide the user with precise and relevant answers, along with confidence ratings and supporting evidence. Its learning capabilities allow Watson to adapt and improve hypothesis generation and evaluation processes over time through interactions with users. Developers and other users can improve the accuracy of responses by "training" Watson. IBM is also continuing to expand Watson's capabilities to incorporate visualization, reasoning, ability to relate to users, and deeper exploration to gain a broader understanding of the information content. Watson recently launched a new platform service that has the ability to ingest and interpret still and video images, which is another significant type of unstructured data.

IBM has launched the Watson for Cyber Security beta program to encourage companies to include Watson in their current security environments. Starting off with such organizations as California Polytechnic State University, Sumitomo Mitsui Banking Corporation, and University of Rochester Medical Center, the program will grow over the next few weeks to encompass 40 companies spanning industries like banking, travel, energy, automotive, health care, insurance, and education. For the past few months, IBM Security has been working with eight universities -- California State Polytechnic University at Pomona, Penn State, MIT, New York University, University of Maryland at Baltimore County, and Canada's universities of New Brunswick, Ottawa, and Waterloo -- to help teach Watson the "language of cybersecurity." The research project involved feeding Watson's AI brain thousands of documents annotated to help the system understand what a threat is, what it does, and what indicators are related. Watson for Cyber Security combines machine learning and natural language processing to make associations in unstructured data like blogs, research reports, and documentation that security analysts can then use to make better, faster decisions.

You may know Watson as IBM's Jeopardy-winning, cookbook-writing, dress-designing, weather-predicting supercomputer-of-all trades. Starting today, 40 organizations will rely upon the clever computers cognitive power to help spot cybercrime. The Watson for Cybersecurity beta program helps IBM too, because Watson's real-world experience will help it hone its skills and work within specific industries. After all, the threats that keep security experts at Sun Life Financial up at night differ from those that spook the cybersleuths at University of New Brunswick. IBM researchers started training Watson in the fundamentals of cybersecurity last spring so the computer could begin to analysize and prevent threats.

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For this tutorial, we're going to power TJBot with APIs from Watson Developer Cloud. We'll start by putting a voice interface onto TJBot, then give it the ability to converse and understand your emotional tones. In part 2 of the tutorial, we'll transfer the code onto a Raspberry Pi and put the whole thing into the physical TJBot itself. For the sake of simplicity, we'll keep the conversation simple.