>> My name is Tyson Thomas, and I'm the chief scientist and the director of product science
for a small software company called Neural ID.
So Neural ID is a software company that analyzes data for pharmaceutical companies,
using machine learning pattern recognition.
So it came out of technology that was geared towards analyzing patterns and has been applied
to images in manufacturing, retail, a variety of different application areas,
and we've evolved the product into processing waveforms
and geared our software product towards the pharmaceutical and health sciences,
where they generate a lot of data.
And it takes a lot of time for humans to go through that data.
So our motto is that the machines work and the humans think.
So, my role is to try to bridge the gap between the scientists that are our customers
and what they want to do with their data,
and our core technology, which is pattern recognition.
So typically what that involves is understanding how the experts--
the domain experts look at their data, and then trying to use that insight
to formulate how we approach their problem in the same way that they do,
so that we can essentially capture their expertise and knowledge in the machine.
So what that means is we do things like feature extraction.
So how do we go from the raw data waveform into what's salient about that data.
So ignore the things that aren't important and emphasize the things that are important.
So my role has been in that aspect of future extraction, designing the product
from how one interacts with it, how one points it towards data, how one trains it,
and then how one uses it to automate the process of analyzing the data.