Among the many companies relying on Watson for their own AI operations is Equals 3, which uses Watson to power Lucy—its cognitive companion for marketing professionals. Lucy uses several IBM Watson services, including Retrieve and Rank, Natural Language Classifier, Personality Insights and Tradeoff Analytics. Lucy can comprehend vast amounts of structured and unstructured marketing data and provide detailed answers in seconds.
"Lucy solves the data-overload problem marketers and agencies have been grappling with for years: accessing the appropriate data at the right time," said Scott Litman, co-founder of Equals 3, in a statement.
"The fact that Lucy can accomplish in one day what has previously taken months to do is a complete paradigm shift, and her ability to enhance what marketers can do is really made possible thanks to the cognitive computing capabilities of IBM Watson," Litman said.
Watson Not for Everybody
However, despite there being more than 80,000 developers using the Watson Developer Cloud, IBM's cognitive system is not a match for everybody.
Rob May, CEO of Talla, which markets an AI-powered virtual assistant akin to Apple's Siri, but aimed at business professionals, said Watson was simply not a fit for Talla.
"We do a lot of natural language processing and we have a cognitive computing approach to a lot of what we're doing," May said. "We tried Watson in the beginning and it really just wasn't a very good fit for us."
May said there are a lot of pros and cons to Watson. Among the pros are that IBM is clearly committed to it, the Watson resources will be available long term and they offer a lot of different functionality.
But on the down side, said May, a lot of Watson "is maybe more marketing hype than substance in some ways. It definitely does some stuff, but some of the functionality is pretty limited and it's really not set up well for small companies to build products on top of. It seemed like a lot of the Watson functionalities that are set up are targeted at larger IBM customers, which would make sense."
In particular, he believes Watson seems targeted at existing customers that have large data stores that are appropriate for cognitive computing, or some kind of analysis that can't be readily performed with common, existing algorithms.
Rather than use Watson, Talla used a series of open-source components and wrote a lot of its own cognitive code.
"IBM has tried to get companies like us to build on top of their platform, but I just don't think it's ready yet," May said. "It's not flexible enough; it's not easy enough to get started."
Yet, IBM has sponsored a number of Watson-related hackathons and developer competitions where small startups have successfully used the services to launch new apps.
Moreover, IBM's recent deal with Twilio to integrate Watson services with the Twilio communications platform not only opens Watson up to the more than one million developers in Twilio's developer community, but it only takes two minutes to integrate the cognitive services with Twilio, said Patrick Malatack, vice president of product management at Twilio.
Right now, IBM is doing more than its competitors to encourage developers to learn how to create cognitive applications, Pund-IT's King said.
"I can't think of another vendor among IBM's direct competitors that is supporting similar developer-oriented efforts to anything like the same degree," said King.
"That said, companies including Apple, Google and Microsoft have created powerful solutions supporting natural speech and machine learning functions. Google and Microsoft also have proactive, innovative efforts aimed at increasing developer activities around those platforms."