The research name is System S.
The article is about researchers monitoring large streams of data and using machine learning to help in detecting whether an infant in the ICU has an infection. The data streaming tech is from IBM though and based on what was used in Watson, so there is that link.
Interesting work nonetheless and hopefully an echo of things to come. Perhaps those working in the analysis and prediction on massive streams of data part of HFT could reapply their skills here in a way that could literally save lives.
It's actually not. There really is no connection between the two other than being from the same research lab.
"Artemis is built on an analytics platform called InfoSphere Streams that, like Watson, emerged from IBM research into ways that software can make decisions on the spot using data arriving at a high speed from many different sources".
I thought they started from the same origin and then split focuses. Thanks for the correction.
What we'll end up with is increasingly powerful expert systems, and the human strategists behind the scenes will operate at a higher and higher level.
I suppose I do feel comfortable giving my personal take on it, and why I find working on Streams exciting: we're designing a language and runtime system for a new programming model. Not just a new language (which we do have), but a new programming model. The way you write programs changes when you have essentially infinite streams of data coming through your system - you have to think in terms of operators that transform or filter individual pieces, and you have to keep in mind its inherent distributed nature. That is, you may write a chain of operators to process your data, but each operator can run in parallel with the others, even though you will probably design your application thinking of one particular piece of data marching through the system. The runtime system itself is, of course, distributed and fast.
To get an overview of this programming model, take a look at this paper: "SPADE: The System S Declarative Stream Processing Engine": http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.160...
Just keep in mind two things: the newest iteration of the language is called Streams Processing Language (SPL), and that it is a complete rewrite of Spade.
I suppose I should put in the disclaimer that these are my views, and I do not represent IBM.
Your post got me even more confused: what exactly new programming models? I understand there may be an influx of sensor data coming in and your apps have to be able to cope with them --- do specific data analysis, maybe some kinds of expert systems, and generate possible suggestions. But how is that different from existing systems, say, nuclear station operation system, high-frequency trading systems, to name a few.
Infections and acute illnesses in infants in general are scary for a number of reasons. These guys can go bad very quickly. They can't tell you if and where they hurt, so it's a little like veterinary medicine.
In training, very subtle clues like a slightly elevated heart rate or (in particular) respiratory rate didn't initially alarm me because in adults these kinds of isolated findings mean practically nothing. Very experienced peds nurses would occasionally take a look at a baby I'd just examined and wasn't worried about...and would worry. I learned quickly to trust what seemed like intuition. We'd start the wheels in motion for more vigorous intervention.
These nurses (and the docs who then benefit from their experience) were applying a lot of (sometimes unwritten, if not unconscious) heuristics in these evaluations. A system doing this rigorously, objectively, and routinely is a good application of such software.