Agriculture is the industry that accompanied the evolution of humanity from pre-historic times to modern days and fulfilled faithfully one of its most basic needs: food supply. Today this still remains its core mission, but it's integrated in a more complex than ever mechanism driven by multiple sociological, economic and environmental forces. This $5 trillion industry representing 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse gas emissions continues to keep pace with world's evolution, changing tremendously over the past years. Digital and technological advancements are taking over the industry, enhancing food production while adding value to the entire farm-to-fork supply chain and helping it make use of natural resources more efficiently. Data generated by sensors or agricultural drones collected at farms, on the field or during transportation offer a wealth of information about soil, seeds, livestock, crops, costs, farm equipment or the use of water and fertilizer.

IBM Watson and pharmaceutical company Teva will expand their existing global eHealth alliance to focus on two key healthcare challenges: The discovery of new treatment options and improving chronic disease management. Both projects will run on the IBM Watson Health Cloud. The partners jointly announced their expanded plans on October 26 at the World of Watson conference in Las Vegas. The partnership features a new, three-year research collaboration to develop cognitive technologies that enable a systematic approach to the emerging field of drug repurposing and deliver unprecedented scale in the discovery of new uses for existing drugs. The companies also announced that respiratory and central nervous system diseases would be the first targets for their chronic disease management initiative, which will be the first project to integrate data from The Weather Company - an IBM Business - into the analysis.

Though artificial intelligence experts may cringe at the portrayals of humanlike AI in science fiction, some researchers are nudging us closer to those visions. "I think it's useful that your user interface not only understand your emotions, your personality, your tone, your motivations, but that it also have a set of emotions, personality, motivations," says Rob High, the CTO of IBM Watson. "I think that makes it more natural for us." Last month, High's company unveiled Project Intu, an experimental platform that allows developers the ability to build internet of things devices using its artificial intelligence services, like Conversation, Language and Visual Recognition. Someday, the system promises to let programmers create a staple character of sci-fi: the gregarious, hyper-connected AI like J.A.R.V.I.S. of Iron Man, KITT of Knight Rider, or Star Wars' C3PO.

IBM Watson wowed the tech industry and a corner of U.S. pop culture with its 2011 win against two of Jeopardy's greatest champions. Here's how IBM pulled it off and a look at what Watson's real career is going to be. Between them, they'd racked up over $5 million in winnings on the television quiz show Jeopardy. They were the best players the show had produced over its decades-long lifetime: Ken Jennings had the longest unbeaten run at 74 winning appearances, while Brad Rutter had earned the biggest prize pot with a total of $3.25 million. Rutter and Jennings were Jeopardy-winning machines. And in early 2011, they agreed to an exhibition match against an opponent who'd never even stood behind a Jeopardy podium before. But this Jeopardy unknown had spent years preparing to take on the two giants in the $1m match, playing 100 games against past winners in an effort to improve his chances of winning. That opponent didn't smile, offered all his answers in the same emotionless tone, and wouldn't sit in the same room as his fellow contestants.

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.