IBM Reinvents Itself By Establishing A Frontier Homestead For Cognitive …

28 Oct 2014 | Author: | No comments yet »

Big Blue Bets Big On IBM Watson Group.

IBM’s Watson computer has amused and surprised humans by beating world class chess champions and Now, one of the world’s smartest machines is taking on chefs. Reacting to 10 quarters in a row of declining revenues and the abandonment of IBM’s profit target for 2015, UBS’s Steve Milunovich asked on the Q3 earnings call last week about IBM’s appeal to Silicon Valley startups.Watson is an artificially intelligent computer system capable of answering questions posed in natural language, originally designed and built to answer questions on the quiz show Jeopardy.The end result will be to transform computers from essentially dumb devices capable only of crunching numbers with extraordinary speed to devices that combine that skill with intuition and common sense.The 400,000-square-foot building at 51 Astor Place in New York’s East Village was once called the Death Star among skeptics, who scoffed at the idea of new development during the recession when demand was nonexistent.

Giving voice to the rising conviction on Wall Street and beyond that the answer to the “disruption” of large companies is to “focus,” Milunovich stated that “they all argue of course they are going to disrupt the large companies, that the large companies basically have to break up.” IBM’s CEO Ginni Rometty had a two-fold answer. IBM says that traditional computing systems, which are only capable of doing what they were originally programmed to do, cannot keep up with Big Data in constant motion. Big Blue’s cognitive computing division — established in January with a $1 billion budget — inked a deal for four floors and officially opened its doors late this month. Watson is being used by chefs to come up with new and exciting recipes in a feat that could turn out to be useful for people with dietary restrictions and for managing food shortages.

IBM’s investments and offerings in these markets appeal to startups, argued Rometty, as evident by the 3,000 applications to join the Watson ecosystem. Jason Leonard, IBM Asia Pacific Watson Business Unit Executive says that unlike Google and Siri, Watson focuses on curated information rather than garbage from the internet.

It was a celebration and media frenzy the day of the headquarter’s grand opening, but that’s since given way to serious work for the more than 700 employees housed in the division’s new home, charged with helping reinvent IBM in what the company’s called the third wave of computing. “The last time IBM stood up a group like the Watson Group was 20 years ago, so it absolutely is of pivotal importance to the business,” said Steve Gold, vice president of the IBM Watson Group. Where Siri waits for a user to ask a question and then searches the internet for an answer, Watson tries to engage in a conversation and interact with the user, instead of searching the internet. The technology, in a nutshell, is a computing system that eats up dark data — that unstructured mass of social media, photos and other information floating out there that’s difficult to capture for analysis — and then learns from it.

Watson can read and understand natural language, which is important in analysing unstructured data that make up as much as 80 percent of the data we see today. Using tools like natural language understanding, search and categorization, visualization, data analysis, psychology, statistics, research in how the brain works and studies in human information interaction, they began to construct a new type of computing system. Instead of customers searching pages and pages of a company’s website, they’ll be able to click on a Watson icon and get the answers they need more quickly. The company has reported revenue declines for 10 straight quarters, with third-quarter revenue down 4 percent to $22.4 billion. “We are extremely bullish on Watson, but more importantly we’re bullish on the business,” Gold said, pointing to the company’s 2015 road map, and the work around big data and mobile among other spaces. “There’s a lot of great innovation.

We also aren’t afraid to divest the businesses that no longer embody the culture and spirit of what we stand for.” That includes IBM’s announcement this month that it plans to rid itself of its semiconductor business by paying GlobalFoundries $1.5 billion to take on the chip business. IBM also announced new customers for Watson in 20 different countries, new partners developing Watson apps, five new Watson client experience centers around the world, and that Watson has started to learn Spanish so it could help Spain’s CaixaBank employees advise the bank’s customers. Last week, Cognitive Scale, which is filled with ex-IBM Watson employees, came out of stealth mode. eWeek says that Cognitive Scale has built a new platform based on IBM Watson. Watson’s technology could be the start of moving away from a keyword-based search to a more conversational, meaningful interaction between humans and computers. It offers applications in four verticals, owns 22 patents, and already has customers and established partnerships with what the story calls “technology titans.” One of these is IBM.

Then, you can make predictions about what’s going to be pleasant, what’s going to be sweet and spicy and salty and savory.” A great chef uses her personal knowledge and intuition to do this, he says. Watson is already being used in a number of industries across the world, including Deacon University in Melbourne, healthcare providers in the U.S, and the Singapore Government recently announced they will make use of Watson’s artificial intelligence to learn from interactions with users, and improve engagement for areas such as income tax, employment and work pass applications. Leonard says telcos, banking and insurance organisations, medical and health providers, and the government sector (including police) are the types of industries we can be expecting to use Watson. Like if she is cooking for someone on a special diet, or if there is a shortage of certain foods. “It might be that you want to improve the fat content or the calorie content,” Abrams says, “and it might be that what you want to do is focus less on certain fishes that may be overfished or may be endangered and instead trade in other fishes.” And it isn’t just engineers like Abrams who are excited about Watson.

These interfaces expose Watson’s core ability to provide credible answers to everyday questions, alongside services ranging from machine translation to user modelling, which categorises people based on their email or public posts. The two key steps are providing IBM Watson with comprehensive information and training it in what seems to be about the same way as one would train an employee. The Austin, Texas-based startup is partners with IBM Watson, SoftLayer and IBM Power, and got its start about a year ago with initial investments form Michael Dell, The Entrepreneurs’ Fund and Tom Boone Pickens III. He writes about wireless technology, disaster recovery/business continuity, cellular services, the Internet of Things, machine-to-machine communications and other emerging technologies and platforms. As IBM learns from its work with customers and partners and overcomes these type of challenges, Rhodin sees Watson’s great promise mainly in its ability to help humans deal with information overload.

Weinschenk has written about the phone companies, cable operators and related companies for decades and is senior editor of Broadband Technology Report. The group began with three partner companies using Watson to develop apps, and that has since grown to more than 100 with another 3,300 that have applied for the program. Let me create a new combination of foods that will be novel and tasty.’ ” “We’ve only been kind of at this whole agricultural cooking game for, you know, a few thousand years, right?” Gourley says. “And we’ve only explored a small piece of it.

To respond to the fluid nature of users’ understanding of their problems, the cognitive computing system offers a synthesis not just of information sources but also of influences, contexts and insights. Investments have gone to health-care optimization platform maker Welltok and e-commerce company Fluid, among others, some of which have not been made public.

Watson can help a highly specialized physician—or just about any other professional—see the bigger picture but it can also help newcomers to the profession learn best practices and get answers to their questions. They identify and extract context features such as hour, location, task, history or profile to present an information set that is appropriate for an individual or for a dependent application engaged in a specific process at a specific time and place. Eventually, Gold said, it will serve as a place for startups to actually incubate — much like a traditional incubator program — where company founders can set up shop, while being mentored and tapping into Watson resources. The company recently raised $25 million as part of its $37 million Series C funding round. “The ability to continue to get smarter and learn from what people are asking and what consumers are doing is really key, and it’s not something we’ve done a lot in health care,” he said.

It was the clearest testament of how machines can truly be partners with humans rather than try to replace them.” In addition to age-old fears about automation and loss of jobs, there are other potential societal challenges to Watson and cognitive computing. That’s why Watson officials reached out about a year-and-a-half ago to Terry Jones, founder of Travelocity and Kayak founding chairman, to have him visit IBM headquarters in Armonk, N.Y., to take a closer look at Watson. Watson is giving you hypotheses with a confidence factor and these help you explore other avenues.” Indeed, explaining to the public and to Watson’s users, how it works and what to expect from it, would require a concerted educational effort by IBM.

People, including educated professionals, demand answers and certainty, not hypotheses, especially when they interact with technology and engage with science. Watson represents what Gold called a “shining beacon” for the company, albeit still part of a much larger firing on all cylinders across the business to push IBM into its next act as a company. “IBM has a great history of reinventing itself and change is not unique. … You have to constantly push the envelope and reinvent,” he said. “You don’t get to be a 100-year-old company and $100 billion business and not continue to have to be pushed for change, for the next big thing.” Priyamvada Natarajan sums up this educational challenge in The New York Review of Books, questioning the degree to which people understand the scientific method and “whether they have an adequate sense of what a scientific theory is, how evidence for it is collected and evaluated, how uncertainty (which is inevitable) is measured, and how one theory can displace another, either by offering a more economical, elegant, honed, and general explanation of phenomena or, in the rare event, by clearly falsifying it….

Kelly III (head of IBM’s research organization) and Steve Hamm state this position clearly: “The goal isn’t to replicate human brains… This isn’t about replacing human thinking with machine thinking. Rather, in the era of cognitive systems, humans and machines will collaborate to produce better results, each bringing their own superior skills to the partnership.” Still, while the goal “isn’t to replicate the human brain,” Kelly and Hamm devote an entire chapter to IBM’s TrueNorth chip. They must “remember” previous interactions in a process and return information that is suitable for the specific application at that point in time. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory or sensor-provided).

Cognitive scientist and machine learning expert Michael Jordan: “We have no idea how neurons are storing information, how they are computing, what the rules are, what the algorithms are, what the representations are, and the like. Many of today’s applications (e.g., search, e-commerce, e-discovery) exhibit some of those features, but it is rare to find all of them fully integrated and interactive. Oren Etzioni, CEO of the Allen Institute for Artificial Intelligence, writes: “Watson was an impressive demonstration but it was narrowly targeted at Jeopardy and exhibited very little semantic understanding. The intelligence is largely in their PR department.” It well may be that the IBM DNA, while providing it with a great blueprint for getting a message out and getting people excited about what it does, could also be the wrong path to follow today. In late 1947, Thomas Watson Sr., IBM’s CEO at the time, “made a decision that forever altered the public perception of computers and linked IBM to the new generation of information machines,” writes Kevin Maney in The Maverick and his Machine.

Maney: “He told the engineers to disassemble the SSEC [IBM’s Selective Sequence Electronic Calculator] and set it up in the ground floor lobby of IBM’s 590 Madison Avenue headquarters. Undoubtedly we will see smarter Siris, a conversational, self-controlled transport vehicle from Google, a Watson-powered medical diagnostics advisor from IBM.

As the future uses of these systems come to light, we hope to help ground the discussion of cognitive computing in a verifiable framework of capabilities and technologies. IBM should extend and expand the brilliant Jeopardy! public relations coup, maybe even provide the public with free access to some of Watson’s capabilities (IBM already provides a cloud-based version of Watson to 10 universities in North America for their students to use in cognitive computing classes). Note: This definition was developed by representatives from BA Insight, Babson College, Basis Technology, Cognitive Scale, CustomerMatrix, Decision Resources, Ektron, Google, Hewlett-Packard, IBM, Microsoft/Bing, Next Era Research, Oracle, Pivotal, SAS, Saxena Foundation, Synthexis and Textwise /

At the same time, it’s probably best not to generate unnecessary hype and speculation, and not indulge in grand visions of where computing may be going. After all, we’ve gotten used to surprising and useful new technologies coming from unexpected corners that succeed or fail based on the benefits they provide us. Isn’t Watson Oncology, providing medical diagnostics to parts of the world where access to modern medicine is limited, an impressive achievement all on its own?

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