At the big enterprise we were not unaware of their progress in this area. In the late 1980s we had our own artificial intelligence / expert systems efforts underway. How do we leverage massive enterprise expertise? While Baby boomers retire? Premature, but producing very real value. At that time we talked to IBM and got the impression that they had made good progress. The science was already there, pioneered by academics at MIT, Stanford and Carnegie Mellon. The science was there but the connection to real computing systems and data had just begun to mature. IBM made that happen in the coming years. Watson provided a demonstration. We waited.
So now it seems, based on this investment, that we are ready to proceed. But the midsize company is not an enterprise, and cannot spend millions of dollars promoting these approaches. But these methods, anchored in the cloud, help companies because it can allow access to both the methods and the large and volatile databases required to drive these systems. The systems also need access to unstructured language models (ontologies), volatile big data sets, and publicly available data bases to drive the models that will form the bedrock of any intelligence. Sounds like Big Data. Without this data you cannot leverage intelligence.
IBM is setting the stage with this ecosystem. making the right steps to move forward. I look forward to being involved in making this available to the midsized company. I will follow with more impressions in this space as this work evolves.
More on Watson in this blog.
This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. More here.