If we think about becoming a quant investor just more on the number side, so structured data and less unstructured data, yes, I'd say everyone can become a bit more quant. There are now platforms that allow, let's say, known data scientists people to actually go and use machine learning. So it's almost like a new field called AutoML. And there will be no reasons to not be B2C eventually in terms of cost and accessibility.
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.
Click here for your copy of 5 Numbers to Determine a Smart Investment, Phil’s guide for discovering and calculating the numbers that matter most in your investments: https://bit.ly/3psMESQ
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