Ladies and gentlemen of the analytics community, we have a platform war on our hands.
That’s not to say a platform war wasn’t already underway. In one corner there’s SAP, which has spent the past several quarters touting its HANA in-memory technology (which is baked into an ever-increasing number of products in its software portfolio). In another stands Oracle, which is updating its current software (including its Big Data Appliance) to better meet the needs of companies with massive amounts of data to crunch. In December, Amazon announced Kinesis, a software platform capable of capturing huge datasets and analyzing them in “real time” for insight. And let’s not forget open-source solutions such as Hadoop, which dominate many a company’s analytics stack.
But IBM’s Watson could accelerate the competition between all the major players in the analytics space.
At a high-profile Jan. 9 event in New York City’s newly opened World Trade Center 4, IBM announced that it would upgrade its Watson supercomputing platform into a full-fledged business unit, backed by a billion dollars in funding and thousands of researchers and scientists. IBM CEO Ginni Rometty framed the move in grandiose terms, suggesting that Watson would kick off a “cognitive” era of computing in which software becomes almost human-like in its ability to intuit connections and solve some very complex questions.
Watson is reportedly adept with unstructured data such as images and unfiltered Web content; developers and end-users can interact with it using natural language. “It understands the implications of your language,” Rometty told reporters and IBM customers gathered for the event, “and will ask you clarification questions back.”
In limited ways, Watson is already hard at work. In the beginning of 2013, IBM joined with WellPoint and Memorial Sloan-Kettering Cancer Center in New York City to train Watson in processing and interpreting oncology data; as a part of that effort, clinicians and other human trainers spent nearly 15,000 hours “teaching” Watson how to interpret clinical information. But IBM sees Watson’s functionality as extending far beyond health-care (or competing on “Jeopardy,” which was the software’s first public appearance); it wants the platform to become a transformational agent for many industries, with its analytical abilities tackling some truly intractable problems.
As part of making Watson more versatile, IBM has introduced the Watson Developers Cloud, which features tools for building Watson-powered apps. There’s also the Watson Discovery Advisor, a new tool for digesting and analyzing data in rapid time.
The extent of Watson’s powers remain somewhat nebulous—every time Rometty used the word “cognitive,” you could practically see the IBM executives in the room twitch as they contemplated having philosophical discussions about the definition of artificial intelligence with potential clients. But in devoting such a huge monetary commitment to Watson (with the accompanying hype), IBM has made it clear to competitors in the space that it intends to dominate Big Data. In turn, that could force SAP and Oracle to commit more resources to not only building out their platforms, but convincing the world that those platforms are truly the most adept at chewing through epic datasets in order to deliver piercing insight.
There’s also the question of financial returns. Although IBM has assigned considerable resources to this effort, it remains to be seen whether Watson can generate equally impressive revenues; according to The Wall Street Journal, the platform earned $100 million over the past three years, which is impressive but not enough to justify a full-fledged business unit: Watson will need to earn far more in coming years if it wants to earn its keep. If other companies pursue Big Blue down the road of “cognitive computing,” they face similar bottom-line risks. Too bad Watson’s highly touted abilities don’t include predicting the future.