With much fanfare and a rarely seen introduction by CEO Ginni Rometty, IBM launched IBM Watson as a new business unit focused on cognitive computing technology and solutions, now being led by Senior Vice President Mike Rhodin. The announcement is summarized here. Until now IBM Watson was important but had neither this stature in IBM’s organizational structure nor enough investment to support what the company proclaims is the third phase of computing.
With much fanfare and a rarely seen introduction by CEO Ginni Rometty, IBM launched IBM Watson as a new business unit focused on cognitive computing technology and solutions, now being led by Senior Vice President Mike Rhodin. The announcement is summarized here. Until now IBM Watson was important but had neither this stature in IBM’s organizational structure nor enough investment to support what the company proclaims is the third phase of computing. As IBM tells it, computing paradigms began with the century-old tabular computing, followed by the age of programmatic computing, in which IBM developed many products and advancements. The third phase is cognitive computing, an area in which the company has invested significantly to advance its technology. IBM has been on this journey for some time, long before the IBM Watson system beat humans on Jeopardy!. Its machine-learning efforts started with the IBM 704 and computer checkers in the 1950s, followed by decades of utilizing the computing power of the IBM 360 mainframe, the IBM AS/400, the IBM RS/6000 and even IBM XT computers in the 1980s. Now IBM Watson is focused on reaching the full potential of cognitive computing.
If IBM is right that cognitive computing will be the next wave
These recent actions build on IBM’s announcement last fall that it is commercializing IBM Watson to enable developers and partners to innovate on the platform. Its launch of the IBM Watson Developers Cloud marketplace introduces new offerings and content essential to building its ecosystem of resources to meet existing and future demand for applications of cognitive computing. The step is essential in that it will maximize the number of products using IBM Watson and provide IBM with a springboard to exponentially grow its efforts. At the same time, IBM is working with academic institutions
IBM’s announcements included new products to complement the IBM Watson portfolio and give it a broader footprint and value to customers. The first new product announced is IBM Watson Discovery Advisor, a tool that helps pharmaceutical companies plow through massive volumes of big data. This is a good place to start, as harvesting the right information for specific roles and purposes is the foundation of cognitive computing, enabling organizations not just to access information but to synthesize it.
The next announcement was IBM Watson Analytics, a product previously known as Project Neo and introduced to the market last fall, which my colleague Tony Cosentino covered. Incubated in IBM’s business analytics group and using a spectrum of analytic and discovery technology, the product and people who worked on it and other efforts are being transferred to the IBM Watson business unit. Though it was not initially built for IBM Watson today, the discovery and exploratory technology integrates the pillars of analytics, helping facilitate a knowledge discovery process whereby you can explore data through natural language and discover new insights. The move to shift IBM Watson Analytics was unexpected and introduces new pressure to market and sell the product. It has growing potential for line-of-business analysts, who will want to examine this and other tools from IBM’s business analytics group. Only time will tell if IBM will be able to fully monetize the product’s potential through its IBM Watson effort, but the move could be its short-term method to gain customers and revenue. It definitely will be a complement when it interfaces to IBM Watson and utilizes the knowledge that Watson creates.
The next major product announcement was IBM Watson Explorer, a big data analytics tool that enables collaborative discovery, navigation and search across information in applications. Both analytics tools advance the science of big data technologies but focus on more than just the mechanics of what big data does, as described by the “four V’s”: volume, variety, velocity and veracity. Rather, they address the value of what is possible through the so-called W’s, focusing on the who, what, where, when and why. This is what we call information optimization, facilitating the business potential of not just big data but of cognitive computing. For its part, IBM is applying its big data and information management efforts to IBM Watson, categorizing them as IBM Watson foundations. This is critical as our information optimization research finds that organizations do not have enough capabilities to integrate and normalize information from disparate sources as the largest shortcoming of technology in 45 percent of organizations. By integrating and utilizing these big data and business analytics tools as part of IBM Watson, cognitive computing will from a competency perspective be more advanced even if these products are not directly needed for enabling IBM Watson.
With this much at stake IBM was not going to leave customer endorsements to chance, and while it has taken some criticism that customer commitment might not be as high as it has claimed, that question was answered at the IBM Watson event. For one, the medical and healthcare industry was front and center to validate its commitment to IBM, represented by organizations such as the Cleveland Clinic and Memorial Sloan-Kettering Cancer Center. Most interesting was an early peek at the potential of mass consumerization of IBM Watson. The first example was presented by e-commerce facilitator Fluid: Its Fluid XPS is focused on changing the digital experience of consumers by gaining access to information about their needs for products and services in a holistic manner. The example it promoted cold weather gear for camping by asking a question as a front end to the North Face website. A second example was the potential to have IBM Watson be the natural language interface for finding a vacation destination, specifying certain criteria like class, price, type and climate of location; today this requires repetitive tasks such as filling out forms and making your own comparisons to determine where you want to go and for what price. The concept was presented by Terry Jones, the former CEO of Sabre and Travelocity and chairman of Kayak. He has more than 40 years of experience in the travel industry and now consults about business innovation through his company, called Essential Ideas. IBM also demonstrated how cognitive computing can provide the next generation of marketing can synthesize the interactions and psychology of individuals to more effectively market to them. These examples point to the potential of enabling natural-language recognition technology to discover relevant responses that guide users’ actions and decisions.
As part of my analysis over the past couple of years, I’ve been following this step forward and wrote about the new category of cognitive computing. In 2013, IBM brought forward IBM Watson Engagement Advisor and focused on smarter customer service through a simpler engagement approach to improving the customer
As it begins to scale its offering, part of IBM’s challenge is to manage the continuous information feeds that effectively make IBM Watson smarter. While IBM does not talk much about the content aspects of what is required, it is clearly more than just loading files, and these efforts are just as important as librarians are to libraries, whereby they are not just stewards to a collection of books but ensure the value and improvement of the library. There is still a level of mystery on the technical mechanics and readiness of the platform that the company needs to address before the natural-language interface is ready to work its magic. In addition, IBM is still using a natural-language form of text and working through how it can make voice mainstream with IBM Watson, as Apple and Google and others have done. IBM has been working on speech in research for some time and more recently with Nuance, who IBM announced a partnership with back in 2011, but it has yet to demonstrate this capability to the mainstream public, which indicates hesitation on how fast it plans to use voice and speech as the interface. While IBM was not able to fully monetize its early efforts in speech technology, it is now becoming mainstream in the consumer market but has yet to evolve significantly in the business markets as part of enterprise software. I am looking forward to seeing more of what it can do in terms of voice and speech input and Watson talking iteratively to help expedite what is truly natural language for humans.
IBM does not often create new business units and elevate them to this level of commitment and investment for the future. While the business goals for IBM Watson are lofty from both revenue and computing perspectives, no other company – not even Microsoft, Oracle or SAP – has both the established technology foundation and the people and financial resources that IBM has to make this a reality. IBM should be congratulated for making the investment in cognitive computing and helping create new jobs and opportunity that will incubate not just in Silicon Alley but across the globe as others realize the full potential. Our technology innovation research finds that increasing the value of an organization is very important to over half (56%) of organizations which is exactly what IBM is hoping will increase its business opportunity. If you want to catch up on the dialogue and resources related to this topic, you can search #IBMWatson on Twitter and follow @IBMWatson. If you want to learn more about IBM Watson and cognitive computing, go to www.ibm.com/watson and you will find more information about the technology, our research on the topic and the value of this new computing paradigm.