John Doe

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GE Digital: Can Machine Learning Be the Key to Turning GE Around?
John Doe
Posted on November 13, 2018 at 10:11 pm
In 2011, General Electric (GE) made a big bet on machine learning and AI with the creation of what would become GE Digital. In a time of great flux at GE, will Digital survive? What will be its role be [...]

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On November 14, 2018, John Doe commented on Printing: Speed :

I completely agree with your skepticism regarding the need to have fully customizable shoes for the mass market and using 3D printing to accomplish this. I believe that while this may be an excellent solution for extremely niche consumers (ex. high performance athlete), it may not be feasible or even necessary for the average user. Along those lines, I question the true value addition to Adidas’ product using this technology and whether it is worth the large investment versus, as you rightly point out, continuing to invest in existing production processes.

On November 14, 2018, John Doe commented on The Road to Autonomous Driving at Fiat Chrysler Automobiles :

I think the commoditization of the automobile is already underway and it will be difficult for OEMs to avoid. FCA’s positioning in the market and brand strategy may help them stave off this trend better than some of it’s competitors, but the risk is a real one.
While FCA’s strategy of relying on partners to help develop AV technologies in this time when its competitors are spending billions of dollars (on technologies that may be fruitless) may be considered a smart one, I believe that they absolutely risk being left behind. In an automotive industry which is changing more quickly than it has since its inception a century ago, by not building internal know-how in these technologies and best practices, you risk becoming obsolete.

On November 14, 2018, John Doe commented on The Additive Artisan: Richemont’s Use of 3D Printing in Mechanical Watchmaking :

Very interesting take on the watch industry. I think that your concern of whether AM would diminish the prestige and allure of the luxury watch is a very fair one. I believe that manufacturers would be taking a significant risk moving in this direction and performance differences (ex. weight) would need to be sufficiently large enough to outweigh any of the perceptions of having created a “cheaper’ watch.

On November 14, 2018, John Doe commented on 3D Printing Toyota’s Headlights: The Sourcing Decision :

I really appreciated the problem of having to maintain tooling for components over extremely long periods, the difficulty of changing tooling in the auto industry and the costs this create for suppliers and OEMs alike. The idea of using AM to help address some of these issues is quite intriguing. In addition to some of the issues you mentioned, I believe another topic that would interesting to delve more deeply into with AM is the quality/durability of the parts per unit cost added to the piece price.
Hopefully OEMs like Toyota can continue to invest in these technologies to help bring them mainstream and make them more cost efficient solutions!

On November 14, 2018, John Doe commented on Toronto Raptors: Machine Learning as a Method for Improving the Roster Decision Process :

Super insightful article! It’s fascinating to see machine learning applied in sports. I do, however, agree with your comment that the results of the analysis are inherently subject to human biases in the decision making process. There is a tremendous amount of subjextivity in player evaluation, however it can clearly be used as a tool to help influence one’s decisions.Great job!
#wethenorth

On November 14, 2018, John Doe commented on Machine Learning in Caterpillar :

Great discussion! Its interesting to see how a company like Cat is looking to improve it’s processes using new tools like machine learning. I think your point on safety is a very pertinent one where machine learning could definitely play a role. I definitely see connectivity being a key issue (specially on remote work sites).