Watson combines a number of cognitive techniques to help you build and train a bot - defining intents and entities and crafting dialog to simulate conversation. The system can then be further refined with supplementary technologies to make the system more human-like or to give it a higher chance of returning the right answer. Watson Conversation allows you to deploy a range of bots via many channels, from simple, narrowly focused Bots to much more sophisticated, full-blown virtual agents across mobile devices, messaging platforms like Slack, or even through a physical robot.

With an eye toward taking the healthcare supply chain to new levels, UPMC on July 8 introduced Pensiamo, a new company whose goal is to help hospitals improve supply chain performance, where costs are high and getting higher, second only to labor costs. Pensiamo is an Italian word. We can provide insights that others cannot," UPMC's James Szilagy told Healthcare IT News. Pensiamo starts up with 150 employees, spinning out certain functions of UPMC's supply chain into the new company. For now, UPMC itself is the sole customer, but Szilagy said there has been strong interest from others.

A couple of months ago we announced IBM Watson AI XPRIZE (AIXP), a competition that challenges teams to attempt their own Moonshot achievements, demonstrating AI-human collaboration to address humanity's Grand Challenges. Now, I'm happy to announce that the competition is open for submissions. What makes IBM's work within the cognitive space so rewarding is the opportunity to engage with our developer community--the professional developers, the hobbyists and the students who believe they can change the world with simple lines of code that build on the extensive capabilities within our platforms. We see it on Twitter, our dev forums and even onsite at hackathons and live events. Some of our greatest advocates are the developers who are constantly experimenting with Watson APIs.

Official IBM Watson Analytics Twitter account managed by @HollyNielsen & @ForsythMAlexand.

Community-based Question Answering (CQA) sites play an important role in addressing health information needs. However, a significant number of posted questions remain unanswered. Automatically answering the posted questions can provide a useful source of information for online health communities. In this study, we developed an algorithm to automatically answer health-related questions based on past questions and answers (QA). We also aimed to understand information embedded within online health content that are good features in identifying valid answers. Our proposed algorithm uses information retrieval techniques to identify candidate answers from resolved QA. In order to rank these candidates, we implemented a semi-supervised leaning algorithm that extracts the best answer to a question. We assessed this approach on a curated corpus from Yahoo! Answers and compared against a rule-based string similarity baseline. On our dataset, the semi-supervised learning algorithm has an accuracy of 86.2%. UMLS-based (health-related) features used in the model enhance the algorithm's performance by proximately 8 %. A reasonably high rate of accuracy is obtained given that the data is considerably noisy. Important features distinguishing a valid answer from an invalid answer include text length, number of stop words contained in a test question, a distance between the test question and other questions in the corpus as well as a number of overlapping health-related terms between questions. Overall, our automated QA system based on historical QA pairs is shown to be effective according to the data set in this case study. It is developed for general use in the health care domain which can also be applied to other CQA sites.

IBM Watson Provides Self-Service AI for Developers By Darryl K. Taft Posted 2016-05-07 Print In what IBM calls "self-service AI," the company enables developers to easily tap into the power of its Watson APIs to build cognitive apps. When IBM initially launched its Watson cognitive computing platform, one of the first questions on a lot folks' minds was, "When can I tap into the power of Watson?" IBM responded by opening up Watson to developers via the Watson Developer Cloud, which offers Watson services and APIs as well as useful documentation and tutorials, starter kits and access to the Watson developer community. IBM started slow and continued to evolve its Watson strategy for developers. The company started with just a few Watson partners and offered just a handful of Watson services.

Many Watson Developer Cloud services and other cognitive software systems provide a numerical score for how confident the system is in some result. For example, the IBM Watson Retrieve and Rank service provides a Ranker confidence score. The IBM Watson Natural Language Classifier also provides a confidence score as do Watson services for language identification, speech processing, entity and relation detection, etc. Some of these confidence scores may have some meaningful interpretation as a probability (e.g., a probability that some result is "correct" or "relevant"). You cannot assume that all results with a very high confidence score are very good and all results with a very low confidence score are very bad.

KPMG will hold a series of workshops over the next few months with IBM Watson staff to work out how to use the artificial intelligence and machine learning capabilities to carry out this new type of audit. "No-one knows exactly what the audit of the future will look like, but you can be sure it will involve two things - bright human beings and cognitive technology," said Duncan McLennan, the firm's national managing partner of audit. "Cognitive enables greater collaboration between humans and systems - so while it's a game-changer for audit in terms of depth of analysis, it will still require insights from talented people. We're being helped, not replaced."

A recent announcement out of the company reports, "XPRIZE, the global leader in incentivized prize competitions, today announced that registration is now open and guidelines are available for the 5 million IBM Watson AI XPRIZE, a four-year global competition challenging teams to develop and demonstrate how humans can collaborate with powerful artificial intelligence (AI) technologies to tackle the world's greatest challenges. The AI competition is XPRIZE's first open challenge where teams will define their own goals and create AI applications that solve some of humanity's most pressing challenges in areas such as healthcare, education, energy & environment, global development and exploration." Marcus Shingles, CEO of XPRIZE, commented, "In the coming decade, as XPRIZE strives to achieve its impact mission through incentive competitions and crowd-sourcing, we see tremendous opportunity in this emerging generation of problem solvers to use AI to solve humanity's grandest challenges… The IBM Watson AI XPRIZE is intended to promote and progress the notion of'AI for impact' among the global bold innovator crowd, both the established community of practitioners, as well as encourage newcomers to experiment and ultimately demonstrate how AI can be used as a tool for good." The article adds, "Teams have until December 1, 2016 to register through the XPRIZE website for the four-year competition, and then will have until March 1, 2017 to submit a detailed development and testing plan for their proposed solution. There will be three subsequent rounds of selection each fall during which a panel of expert judges will choose the top 10 teams that will advance to compete at IBM Watson sponsored events where they can receive Milestone Prizes."