IBM's Deborah DiSanzo made the announcement at the 2016 Forbes Healthcare Summit. Immunotherapy is an approach that uses the immune system to fight diseases, unlike chemotherapy, which kills cancer cells. Immunotherapy works on cells in the immune system to combat cancer. Dario Gil, director of symbiotic cognitive systems at IBM Research, holds a remote control wand while giving a demonstration of the IBM Watson immersion room during an event at the company's headquarters in New York Oct. 7, 2014. By partnering with IBM's Watson for Drug Discovery, Pfizer hopes to more quickly analyze and test hypotheses from "massive volumes of disparate data sources" that include more than 30 million sources of laboratory and data reports as well as medical literature.

Immunotherapy is an approach that uses the immune system to fight diseases, unlike chemotherapy, which kills cancer cells. Immunotherapy works on cells in the immune system to combat cancer. Dario Gil, director of symbiotic cognitive systems at IBM Research, holds a remote control wand while giving a demonstration of the IBM Watson immersion room during an event at the company's headquarters in New York Oct. 7, 2014. By partnering with IBM's Watson for Drug Discovery, Pfizer hopes to more quickly analyze and test hypotheses from "massive volumes of disparate data sources" that include more than 30 million sources of laboratory and data reports as well as medical literature. Watson will also be able to combine such a massive database with Pfizer's own proprietary research information.

Most companies know by now that the key to making smart and strategic decisions is to look at both current and past data as a cornerstone for future business. Business intelligence teams and other analysts are brought on to enable more efficient decision making across every department. This can lead to visible changes for customers or viable improvements to process for employees. Advances in computer vision have opened up opportunities to apply data like never before. As artificial intelligence has become an increasingly popular topic of late and corresponding neural networks have improved, it's a great time to revisit how – and when – your company is applying its data.

IBM companies Watson Health and Merge Healthcare unveiled several new machine learning and artificial intelligence technologies for imaging at the RSNA Annual meeting in Chicago this week. Big Blue also showcased new advancements in how Watson technology can learn and gain understanding from image information, which researchers say now accounts for some 90 percent of all medical data. IBM has taken a keen insight in applying Watson's supercomputing capabilities to imaging – especially since its 2015 acquisition of Merge. Big Blue, in fact, is developing numerous tools to help automate analytics, enabling cross-reference X-rays, MRIs and other images against electronic health record data, lab results, genomic tests and more. At RSNA, Watson Health is showcasing: a cognitive peer review tool aimed at reconciling differences between a patient's clinical evidence and data in his or her EHR; a data summarization tool meant to give radiologists, cardiologists and others patient-specific clinical information when they're interpreting imaging studies; a decision support tool to enable physicians to integrate imaging data with other clinical information; the new MedyMatch "Brain Bleed" App, a cognitive image review tool intended to help ER docs diagnose strokes or brain bleed in trauma patients based on evidence in their patient records.

There is plenty of growing evidence that market leaders are making Artificial Intelligence (AI) a top strategic priority and already seeing results. Most business leaders that have rolled our cognitive solutions expect to continue seeing tangible results, and gain a competitive advantage over the next few decades. The five most valuable companies in the United States by market capitalization (Apple, Alphabet/Google, Microsoft, Amazon and Facebook) focus heavily on AI within their research efforts and business models. The five most valuable companies in the United States by market capitalization (Apple, Alphabet/Google, Microsoft, Amazon and Facebook) focus heavily on AI within their research efforts and business models. A newly published IBM study found that the majority (58%) of early adopters of AI (and the cognitive systems that use AI capabilities) believe that these new technologies are "must haves" to remain competitive within the next few years.

The Mill created a massive real-time data art installation built from the computation analysis of pop music, social media and news media by IBM's Watson. Natural language and musical compositions were assigned emotional values by Watson which we then translated into immersive visualizations that could be navigated by time, emotion and genre. Intricate color coding of the visuals was based on a five color palette, one each for joy, anger, disgust, sadness, and fear. Follow @Millchannel on Twitter, Facebook & Instagram for more updates.

WiFi company Zenreach is used to winning at least 60% of the time when it goes head to head with competitors. But when the 150-person startup went back and studied the conversations its sales reps were having with prospects, CEO Jack Abraham was confronted with a challenger beating his team 3 times out of 4. "We hadn't even considered them a competitor," says Abraham. "But when you can scan through all the instances a competitor is mentioned, it's easy to scan through what you're missing." The Zenreach sales team got that wakeup call courtesy of a new technology that launched on Tuesday called TalkIQ. Incubated out of Abraham's venture fund Atomic, TalkIQ is coming out of the gate with $7 million in initial funding from name-brand investors and speech recognition software for sales, customer service and onboarding that the startup claims is 2x better than IBM Watson and 3x better than Google. TalkIQ formed more than a year ago along the premise that if someone (or a machine) were to study every call made in a company, she (or it) could uncover patterns and insights to make the business run better--especially if you accept, as TalkIQ did, research that suggests that as much as 68% of customer interactions with company contact centers still happen by phone.

Last week I attended IBM (IBM) World of Watson as both a speaker and an attendee, and today as I sit in my neighborhood Starbucks (SBUX) thinking about everything, all I can say is WOW! This was one of the most interesting, inspiring and amazing events I have ever attended. And we are still in the very early stages of Watson, Cognitive and AI. I invite you to follow me as I learn more and write more about the wonderful world of Watson, all the companies that work with it and how it will change our industries, our businesses and our lives. As a wireless analyst and columnist, I come at this world of Watson from the wireless, telecom, internet and television angle.

Last week, IBM released a public beta of Watson Analytics, a platform for data exploration, visualization and predictive analytics. This product follows on Microsoft's Azure Machine Learning service, which provides cloud-based machine learning solutions. Interested to see how the offerings compare, I set up accounts with both services and set out to explore several datasets. For fairness, I should note that IBM's Watson analytics is in a public beta, while Microsoft's product is a significantly more mature offering. Besides relative maturity, the more striking difference between the products is the fundamentally different use cases they address.