Jon McAuliffe
The Disruptor
Contrarian and drawn to the edge; challenges the settled answer.
Jon McAuliffe earns The Disruptor not by entering a paradigm but by rebuilding its foundations. In 2005 he committed to a machine-learning-driven investment firm when institutional peers doubted the approach was even viable. His intellectual posture is equally insurgent, dismissing black swan excuses as epistemological laziness and calibrating model complexity solely for predictive accuracy.
“Yeah, that is, you know, if you like the million dollar question in statistical prediction And you might find it surprising that relatively straightforward ideas go a long way here. And so let me just describe a little scenario of how you can deal with this, all right? We agree we have this big historical data set.”
“Well, that's a great question because the two are inextricably linked. The way that you make algorithms great is by making them more powerful, more expressive, able to describe lots of different kinds of patterns and relationships.”
“And you lay all those genomes on top of each other, and then you look for places where all of the genomes agree, right? There hasn't been variation that's happening through mutations. And why hasn't there been? Well, the biggest force that throws out variation is natural selection.”
“And we had met at DE Shaw in the 90s and been less excited about this idea because the methods were pretty immature. There wasn't actually a giant diversity of data back in the 90s in financial markets, not like there was in 2005.”
Masters in Business: “Jon McAuliffe on Innovation and Statistical Methods”
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