Jake Chouinard

  • Student

Activity Feed

Mark, great example of an area where the data input to Watson might not be able to pick up on the intangibles of players. I would go further and think that Watson will miss a lot of players who are not the “stars” in college with the highest stats, due to the lack of data input to predict potential. I foresee Watson as being a tool to add one more data point in a decision, versus the machine that will make the decisions. It will be interesting to see how the NBA and other professional sports continue to incorporate data and machine learning into their strategy.

Thanks for the article Jake! I love that LEGO is continuing to leverage open innovation in unique complementary ways. I think it is a way to really drive brand loyalty for the customers, as they will feel that they had a say in developing the project. I do agree with any of the other comments though, and I personally find it hard to imagine that physical LEGOs will be a large part of the business in the future. LEGO will have to continue to find new ways, such as VR like others mentioned, to attract a younger population that is more engaged with technology.

On November 14, 2018, Jake Chouinard commented on Organovo: bioprinting tissue to speed up drug development :

Interesting to hear about Organovo using bioprinting with a unique commercial strategy of partnering with pharma companies who will benefit in the drug development cycle. I would imagine that 3D printing the liver will have high upfront costs, but the experience and technology has the potential to be transferable to other organs. I have heard of other companies working on using 3D printing to create scaffolding tissue used in the heart. Perhaps Organovo’s approach will be less of an upfront challenge and lead to the company’s eventually ability to accomplish such a feat. I hope that Organovo can deal with the public pressure and maintain a long term view to accomplish this!

On November 14, 2018, Jake Chouinard commented on Closed Innovation at Facebook :

Great article comparing open and closed innovation. Alexander mentioned Apple as an example of open innovation, but I’d like to dive deeper into the Apple Watch in comparison with its current competitors. I believe the Apple Store will enable Apple Watch to dominate the tech wearables industry in the future as Apple will be able to crowd source new innovations and act as a platform to deliver content to its users. Compare this to Fitbit or Garmin, who operate in a closed innovation system, and it is difficult to envision these individual companies being able to compete on innovation.

It will be interesting to see how much data sharing will occur within open innovation in the future, and how that data can be then used in artificial intelligence and machine learning.

On November 14, 2018, Jake Chouinard commented on Printing: Speed :

I tend to agree with John Doe that it seems the current market potential for 3D printing shoes is in the niche consumer space. However, I disagree with questioning the value. Much like automotive companies create high performance vehicles to drive and showcase their innovation, Adidas has the potential to prove this technology with partnerships with, for example, high performance athletes who are willing to pay an extremely high premium for percentage gains in performance. I think it will be crucial for Adidas to be a first mover in the space and use 3D as the opportunity to drive new innovation, with the aim of eventually improving the technology to economically replace current production processes.

On November 13, 2018, Jake Chouinard commented on Machine Learning in the Shale Patch: A Look at the “Mother Fracker” :

This article provides a thoughtful examination of an industry that is ripe with recent technological advances. Making money in the oil industry was a heck of a lot easier when oil prices are $100/barrel. These prices led enough new players into the space to create a surplus of production. With the drastic price drop in 2014, oil producers were forced to focus on efficiency improvements and cost cutting. As horizontal drilling and fracking technologies continue to improve, the lowest cost provider will have a serious competitive advantage.
It will be interesting to see just how big of a role machine learning can play in this lower priced environment. As Mark suggested, perhaps the larger players with the most data will be the companies that have the most to gain from machine learning. Pioneer seems to be one such company that could see large benefits from the technology.