To gauge the future of IBM (NYSE: IBM) one needs to understand its cognitive computing platform, Watson.

This episode of Fast Forward was recorded in the IBM Watson Experience Center here in New York City. My guest was Rob High, the Vice President and Chief Technology Officer of IBM Watson. High works across multiple teams within IBM, including engineering, development, and strategy. He is one of the most lucid thinkers in the space of artificial intelligence, and our conversation covered many of the way that technology is reshaping our jobs, our society and our lives. Read and watch our conversation below. Dan Costa: What is the dominant misconception that people have about artificial intelligence? Rob High: I think the most common problem that we're running into with people talking about AI is they still live in the world where I think Hollywood has amplified this idea that cognitive computing, AI, is about replicating the human mind, and it's really not. Things like the Turing test tend to reinforce that what we're measuring is the idea of AI being able to compete with fooling people into believing that what you're dealing with is another human being, but that's really not been where we have found the greatest utility. This even goes back to, if you look at almost every other tool that has ever been created, our tools tend to be most valuable when they're amplifying us, when they're extending our reach, when they're increasing our strength, when they're allowing us to do things that we can't do by ourselves as human beings. That's really the way that we need to be thinking about AI as well, and to the extent that we actually call it augmented intelligence, not artificial intelligence.

Try Watson's AI-powered APIs for free For many people, the first time they ever heard about artificial intelligence and IBM Watson was when it played Jeopardy! While Watson made a few mistakes on its way to victory, it cemented its reputation well enough that many articles about Watson still describe it as the artificial intelligence system that played Jeopardy! But even before Watson competed on Jeopardy!, AI systems also learned games, ranging from tic-tac-toe to chess. You may recall that in 1997, IBM's Deep Blue beat the world's chess champion Garry Kasparov. And since Jeopardy!, AI systems like Watson have continued to learn to play other games, ranging from the ancient game of Go to Texas Hold'em poker.

When people in an emergency situation call into their local 911 operations center, there might be another "brain" listening in on the call. The Association of Public-Safety Communications Officials (APCO) International, which has more than 29,000 members, tapped IBM to bring Watson into their software. APCO recently announced that APCO International's new guide card software called APCO IntelliCommä will use IBM Watson Speech-to-Text and Watson Analytics to improve the scripts used by 911 operators. The guide card system provides guidance to 911 operators on what to ask and say to gather needed information to access specific emergency call types. Essentially, the software helps operators "provide rapid and customized instructions so callers get the fast, consistent, and appropriate information they need and expect in an emergency," according to a press release.

July 11, 2017 Written by: Chris O'Connor An IoT platform must connect devices, must collect data, must handle thousands of vendors, dozens of standards and must be able to scale to millions of devices sending billions of messages. To deliver true value beyond the basics, it must add cognitive, security, privacy, insight generation and close loop automation. With these capabilities and the supporting technology advancements, the IoT platform becomes an agent of transformation for a business. Organizations in the midst of, or planning for, an IoT deployment understand the complexity of finding a solution that is holistic yet customizable to their own unique requirements. A solid platform is the linchpin in connecting endpoints, capturing meaningful data, and pulling all together into a central dashboard that allows you to glean actionable insights.

In treating brain cancer, time is of the essence. A new study, in which IBM Watson took just 10 minutes to analyze a brain cancer patient's genome and suggest a treatment plan, demonstrates the potential of artificially intelligent medicine to improve patient care. But although human experts took 160 hours to make a comparable plan, the study's results weren't a total victory of machine over humans. The patient in question was a 76-year-old man who went to his doctor complaining of a headache and difficulty walking. A brain scan revealed a nasty glioblastoma tumor, which surgeons quickly operated on; the man then got three weeks of radiation therapy and started on a long course of chemotherapy.

You've probably seen the Watson commercials, where what looks like a sentient box interacts with celebrities like Bob Dylan, Carrie Fisher, and Serena Williams; or doctors; or a young cancer survivor. Maybe you caught the IBM artificial intelligence technology's appearance in H&R Block's Super Bowl commercial starring Jon Hamm. "It is one of the most powerful tools our species has created. It helps doctors fight disease," Hamm says. "It can predict global weather patterns. It improves education for children everywhere. And now we unleash it on your taxes."

Deliver lightening fast customer support at scale requires a lot of resources and this is why you want your end users or employee to be able to self serve as much as possible. Bots have been around for a long time, but recent advances in natural language processing drove huge adoption over the last year. They are now being used to enhance a broad set of experiences with customer service being one of the most relevant. In this article we're going to learn what does it take to save time to our customer support team. To do this we'll build a chatbot to automate answers to frequently asked questions, eventually saving precious time to your customer support operators so they can focus on more complex requests.

Machine learning is everywhere these days. Whether it's recommending your next movie on Netflix or beating Ken Jennings at Jeopardy, ML is here to stay. But how do you get in on this wave? IBM has just made their new Watson Machine Learning (WML) service generally available this week. I do have to point out that you will need to create an account with Bluemix to start playing around with the service, but there's a 30 day free trial and it's pretty fun.

Causality has been recently introduced in databases, to model, characterize, and possibly compute causes for query answers. Connections between QA-causality and consistency-based diagnosis and database repairs (wrt. integrity constraint violations) have already been established. In this work we establish precise connections between QA-causality and both abductive diagnosis and the view-update problem in databases, allowing us to obtain new algorithmic and complexity results for QA-causality. We also obtain new results on the complexity of view-conditioned causality, and investigate the notion of QA-causality in the presence of integrity constraints, obtaining complexity results from a connection with view-conditioned causality. The abduction connection under integrity constraints allows us to obtain algorithmic tools for QA-causality.