In an example, let's say that I'm looking at Tyson Foods. And what I have available are these little pods of data that I can sort of order up with a click. Is that something we're talking about here? Yeah, that is quite doable. So you take all the behavioral data you can find about that segment and every other segment that a particular bank is focused on. Then you create a predictive model,. To basically predict what segment are we talking about? Now, it sounds silly because we know which client belongs to which segment, right? But here's what we are doing. We are using a predictive model to isolate which of those behaviors carry the highest discriminatory signal in
The arrival of the AI boom has stirred up a lot of questions, a couple of which seem to define the main concerns with the technology: are machines going to take all of our jobs, and how can I utilize this tech in a way that nobody else has thought of yet?
The first question is answered by the fact that none of this would function without human creativity guiding the process, and the second will be answered in a multitude of ways as this technology continues to be refined and democratized in the coming years..
This week on InvestED, Phil and Danielle are joined once again by AI expert Nuno Neves Cordeiro as they discuss the ways that investment firms are implementing open source machine learning processes to streamline the way they analyze data, as well as how the average investor can take advantage of this technology.
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