Certainly it would be wonderful, if Watson could start formulating and answering useful hypotheses that we've not already thought of. As it is, I assumed that "guidance" was provided. For example, in the medical environment, we're interested having Watson focus on identifying which treatment plans produce the best results for specific cancers. We're not interested in the most likely time of day for journal articles on cancer to be published nor the historical trends in colors of respiratory medicine journal covers.
Re: " Obviously you can't just hand it the "Encyclopedia Britannica" (or "Wikipedia") and have it "know everything". "
That is not obvious to me. Depends what they mean by "unstructured data". The ability to hand it unstructured data and have it integrate it into whatever structures it creates is advertised as one of Watson's greatest strengths.
@DrQuine Somehow structures must be created that organize patterns of information and build relevant "expertise"
For the Jeopardy contest there was a lot of preprocessing, because the format of the show made it easy to anticipate what might be important--people, places, things, etc. However, there was also a lot of unstructured data to scan too. Probably will be similar for the domains of knowledge IBM is amassing in its Watson Content Store--some structure for obviously important items plus high-speed scanning and pattern matching for content that is stored unstructured.
BTW Watson was was preceeded by the Open Advancement of Question Answering (OAQA) initiative at Carnegie Mellon University which IBM participated in then developed into what it calls DeepQA--the basic engine for Watson.
I look ahead to hearing more about how information is fed into Watson. Obviously you can't just hand it the "Encyclopedia Britannica" (or "Wikipedia") and have it "know everything". Somehow structures must be created that organize patterns of information and build relevant "expertise" in areas of domain interest.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.