Last month I received a message from Pankaj Maheshwari to join a new meetup group called The Houston Machine Learning Group. I’d been interested in machine learning for quite some time, so I decided to sign up out of curiosity. Within a couple of days, Pankaj was able to gather about 20 of us together, and we all decided to meet up last week at Platform Houston, which is a development space at Rice Village where startups work.
As usual, the Rice Village area was packed full of cars and people, and parking was difficult. After I managed to find a spot, I walked over to Platform Houston and introduced myself to the other members, who represented a wide range of industries like oil & gas, biotech, finance, academia, and software engineering. I found the other members to be very friendly and highly intelligent – after we introduced ourselves, Pankaj told us that he started the group because he noticed that Houston was home to many industries that could benefit from machine learning, but did not have a machine learning community from which to draw talent and share ideas.
The meeting got off to a slow start, but after we got acquainted with each other, we came up with several ideas of projects we could work on, many of which I thought were interesting:
Biotech – Hospitals routinely collect biometric data on their patients, but it wasn’t until recently that they were able to store large quantities of real-time data (one member mentioned that a hospital could store up to a terabyte a day worth of data). The amount of data has gotten so large that it has become difficult to analyze by human means – and machine learning could help discover patterns that we would otherwise miss. For example, imagine a world where each of the nation’s hospitals were linked together via a communications network, and machine learning was able to detect emerging pandemics based on patient data. This would allow governmental organizations such as the CDC to react quickly to such events – which would potentially save millions of lives.
Oil & Gas – Machine learning could optimize the supply chains of oil & gas companies.
Finance & Energy Trading – Machine learning can accurately interpret and place trade orders by analyzing text via natural language processing.
Voting – Machine learning can discover patterns amongst voting populations – this would have a direct impact on political campaigns, and may also keep politicians better informed of their constituents’ interests once they arrive in office.
Traffic – Machine learning could analyze traffic patterns in metropolitan areas to help traffic engineers optimize flow.
Pankaj himself is the founder of two startups, one of which is very close to my workplace called Net Matrix Solutions, which is an IT staffing firm. He expressed an interest in Kurweil, technological singularity, and had the ambitious goal of enabling computers to not only learn from large datasets, but to also be curious about the patterns discovered via learning. He told us that he currently spends 2-3 hours a day looking into machine learning.
Overall, I thought the meetup was very fun, and I really enjoyed meeting people with similar interests. I’m pretty excited to be involved in the group and its projects over the near future.
