The Jeopardy applications requires about three seconds of cluster computer time, but my guess is that financial applications might require slightly more time and retail apps may require less. Also I am sure IBM is working on way to queue up these queries for more efficiency.
This is a great information. One question to be answered at a time is fine. I am just curious to know what is the expected response time for such a response in a single user mode. If it is a matter of seconds or even a minute, still it worth it. Because such high performance machine will be used only to get answers for some critical questions which humans are unable to find in a massive data archive.
By running on a configuration of off-the-shelf cluster computers, IBM will be able to quickly target business applications to solve using the same DeepQA architecture, just with a different knowledge base plugged in. Here are a few applications IBM told me they may target in the future with Watson-like cluster computers:
Healthcare: For medical applications Watson will be able to act as an expert consultant for doctors, simultaneously comparing your symptoms to those of millions of patients worldwide, along with the diagnoses that cured them and all the latest information from medical journals, supplying a ranked list of possible diagnoses.
Retail: Watson can integrate queries from retailers that simultaneously consider past buying patterns, inventory, order management and supply chain issues to supply customer relationship management (CRM) answers that are highly targeted, perhaps offer personalized "sales" while you are still standing at the register.
Financial Services: Watson's realtime analytics will enable financial institutions to what-if scenarios that include market data, current events, the opinion of analysts and a thousand other unstructured information sources that are difficult to encapsulate in to conventional algorithms--plus its machine learning capabilities will enable Watson to hone its predictive abilities even finer over time.
Government: Corporations today must deal with a dizzying array of laws and regulations that could be simultaneously considered by Watson, instead of occupying weeks of a human experts time, allowing businesses to optimize their profits in realtime while still meeting all their regulatory obligations.
What Watson Can't Do: Because the resources of the entire cluster computer are dedicated to answering each question--one at a time--Watson will not be directly amenable to traditional Internet searches, which must serve thousands of amateur users making ad-hoc queries simultaneously.
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.