What's The Future Of Cognitive Computing? IBM Watson

By Jay Bellisimo, IBM Watson Group

We are entering a new period of computing history — the cognitive computing era.

Cognitive computing offers fundamental differences in how systems are built and interact with humans. Cognitive-based systems, such as IBM Watson, are able to build knowledge and learn, understand natural language, and reason and interact more naturally with human beings than traditional systems.

They are also able to put content into context with confidence-weighted responses and supporting evidence. Cognitive systems can quickly identify new patterns and insights. Over time, they will simulate even more closely how the brain actually works. In doing so, they could help us solve the world’s most complex problems by penetrating the complexity of big dataand exploiting the power of natural language processing and machine learning.

IBM is working to expand the adoption of systems, such as Watson, to enable global innovation and collaboration. This month, we announced anew alliance with SoftBank to bring Watson to Japan. The collaboration will include further expansion of Watson’s ability to communicate and “think” in Japanese, as well as establishment of a local ecosystem of partners, developers, entrepreneurs, students and other enthusiasts to create new apps and services powered by Watson. This is a critical step that will allow us to bring cognitive computing to every corner of the globe, starting with one of the world’s largest economies and technology markets.

In a new study from the IBM Institute for Business Value, “Your Cognitive Future,” we identify three types of capabilities for cognitive systems. They are not mutually exclusive, but can take advantage of more than one. The three areas are:

1. Engagement: These systems fundamentally change the way humans and systems interact and significantly extend the capabilities of humans by taking advantage of peoples’ ability to provide expert assistance and to understand. These systems provide expert assistance by developing deep domain insights and presenting the information in a timely, natural and usable way. Here, cognitive systems play the role of an assistant, although one who is tireless, can consume vast amounts of structured and unstructured information, can reconcile ambiguous and even self-contradictory data, and can learn. Humans and Watson working together are more effective than either one alone.

USAA, a financial services provider for the military community, last year announced that it’s offering IBM’s Watson Engagement Advisor in a pilot to help serve military men and women as they transition from military to civilian life. Watson analyzed and understands more than 3,000 documents on topics exclusive to military transitions. By accessing Watson, USAA members are able to ask questions related to the transition experience from military to civilian life.

2.Decision: These systems have decision-making capabilities. Decisions made by cognitive systems are evidence-based and continually evolve based on new information, outcomes and actions. Currently, cognitive computing systems perform more as advisors by suggesting a set of options to human users, who ultimately make the final decisions. To do so, the systems rely on confidence scores — a quantitative value that represents the merit of a decision after evaluating multiple options — to help users make the best possible choice, including why a particular recommendation was made.

3. Discovery: These systems can discover insights that perhaps could not be discovered by even the most brilliant human beings. Discovery involves finding insights and connections and understanding the vast amounts of information available around the world. With ever-increasing volumes of data, there is a clear need for systems that help exploit information more effectively than humans could on their own. While still in the early stages, some discovery capabilities have already emerged, and the value propositions for future applications are compelling. Advances in this capability area have been made in specific domains, such as medical research, where robust amounts of information exist.

Baylor College of Medicine, a leading health sciences university, is constantly looking for innovative approaches to advance and accelerate medical research. The time needed for research professionals to test hypotheses and formulate conclusions currently ranges from days to years. A typical researcher reads about 23 scientific papers per month, making it humanly impossible to keep up with the ever-growing body of scientific material available. Biologists and data scientists at Baylor are using a cognitive computing system powered by Watson in their Baylor Knowledge Integration Toolkit to accelerate cancer research, unlock patterns and make discoveries with greater precision to improve diagnosis and treatment plans.

We see an amazing opportunity ahead for Watson to transform many industries and professions. Another interesting example is “Chef Watson,” which is working with world-class chefs from the Institute of Culinary Education (ICE) to discover entirely new flavor combinations. The result has been a set of new creative recipes and flavorful dishes, helping demonstrate the nearly infinite possibilities of human and machine collaboration. In fact, IBM and ICE will launch a new cookbook in April featuring more 60 recipes inspired by Chef Watson.

Jay Bellisimo is General Manager of Watson Transformation, IBM Watson Group.

Learn more at ibm.com/madewithibm or join the conversation at #NewWayToWork.