David St. Geme

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Machine learning as a tool to predict future earning power
David St. Geme
Last modified on November 12, 2018 at 6:03 pm
This post discussed how a machine learning algorithm can be applied to predict student earnings post-graduation.

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On November 13, 2018, David St. Geme commented on Is the Future of Food Blockchain? :

Do you think this same technology could be leveraged to do better inventory management, particularly around perishable goods? Understanding the entire supply chain seems very promising, and I think grocers could also use this data, in addition to consumer consumption data, to better understand consumer consumption patterns and more effectively manage their inventory, reducing waste and maximizing profit.

On November 13, 2018, David St. Geme commented on Printing the Future: Ford Motor Company’s New Production Process :

One potential area of growth that I think is really interesting is making cars “customizable” by their individual owners. For example, for customers who have access to 3D printing devices at home or at work, they may be able to modify certain components of the car in a lego-like fashion. In a world where a one-size-fits-all mentality seems to be falling by the wayside, I think this additional element of additive manufacturing could be really interesting for automobile manufacturers.

On November 13, 2018, David St. Geme commented on An A.I. Odyssey: How Fox is Using Machine Learning to Market Movies :

Very interesting article! One thought that immediately came to mind was if machine learning may be able to play a larger role in the future in the script-writing process. You mentioned the script analyzer that exists, and it seems like there may be some promise at the very top of the funnel at the conception and script-writing phase, instead of only focusing this technology on the marketing phase.

On November 13, 2018, David St. Geme commented on Skolkovo, Russian Silicon Valley vs. Corruption: how innovation can thrive? :

It’s not entirely clear to me how open innovation was applied successfully, or at all in this case. What is the goal of creating an open environment at Skolkovo and what is the main hypothesis around what open innovation will contribute. Are there any examples in other countries or economies where open innovation has worked well?

On November 13, 2018, David St. Geme commented on Disruption in the automotive business: how distributed innovation can change a 100-year-old industry? :

Very cool post! Do you think that more manufacturers will shift to an open innovation process? What do you see as being the biggest barrier to widespread adoption? My guess is that companies are attracted to the open innovation model because of how much more rapidly they could conceive of and develop product, but does this get in the way of competitive advantage and profitability?

On November 13, 2018, David St. Geme commented on 3D Printing & The Future of Army Resupply in Remote Areas :

Really cool post! Are the 3-D printing machines the military is using able to build any number of parts/components, or are specific machines required based on the type of part? My guess is the former, but if the latter that could pose a significant barrier to adoption of this technology.

On November 13, 2018, David St. Geme commented on Mickey Mouse in the 21st Century: How machine learning is making Disney World the happiest, and most efficient, place on Earth :

Great post! I especially like the potential of the shoe recognition tool to better understand visitor patterns and common walking routes. One really cool potential application here could be to identify the most commonly-walked routes, and then actively push visitors to other pre-determined walk routes to control site congestion. Disney could also prescribe a series of routes that the visitors should take once entering the park so that they could completely optimize for traffic at various sites.