Turning Back the Clock: Symbolic Processing or Machine Learning
Aside from unlimited cold brew, one of the great perks of my job is the opportunity to make Dave tell me stories about the “old days” of machine intelligence. At that time, (believe it or not) MIT students were not encouraged (financially or academically) to study machine learning (ML). Marvin Minsky was running MIT’s artificial intelligence lab and researchers were focused on a top down approach to called “Symbolic Processing.” The fact that you are looking it up on Wikipedia (as I did), illustrates how successful that technology has been.
Less aesthetically enticing, ML required a vast amount of computing power and since it was out of favor, Dave had free rein to use the connection machine after 10pm. Walking the well trod path of other MIT probabilists like Claude Shannon and Ed Thorpe, Dave achieved technical breakthroughs in the middle of the night in an MIT “computer” room.
It was clear to Dave that computing power was reaching a point that enabled ML applications to dominate in a business that could scale relatively narrow human tasks. The actual task or industry was less important than having a well-defined problem. His team could therefore create software for digitizing handwriting, reading mammograms, and demand forecasting at Walmart before ultimately building the first predictive algorithms for Amazon.
It is in this field of so-called “narrow AI” that methods from data science continue to generate the greatest commercial value. This is the same approach we used to develop XPLR, which enhances our ability to find early-stage FinTechs. The majority of our portfolio companies use supervised learning in one form or another; Dave’s perspective is invaluable in both due-diligence and aiding our founders in their efforts to leverage their own proprietary data.
AI shows no sign of relinquishing its position as the most investable technology in FinTech today. As a true pioneer of commercial AI, having Dave’s network and expertise helps us intelligently invest in its continued proliferation.
—Frazer Anderson, Investment Analyst