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On November 15, 2018, MM commented on Machine Learning in Credit Assessment at Capital One :

I agree that the financial services industry is ripe for innovation driven by machine learning. I agree that the most obvious solution in personal banking is in analyzing customer creditworthiness, but I think there are other applications as well. For instance, machine learning can be used for things such as monitoring for and identifying fraudulent activity by being able to analyze immense amounts of data and uncovering patterns and trends that humans would not be able to. From a customer perspective, machine learning using natural language processing can be used to identify intent in some data sources such as emails. For example, if a customer emails their bank, a machine learning algorithm could derive the intent of the email and then direct it to the most appropriate person or department within the organization to handle it. These are just a couple of other exciting examples where machine learning can be applied to consumer banking.

This piece raises the really interesting question of whether machines will be able to become better than humans at something that is intensely personal. This reminds me of an episode of Black Mirror from the most recent season. If you’re unaware, Black Mirror is an eye-opening, thought-provoking series currently produced on Netflix which examines modern society and in particular, unintended consequences and impacts of new technologies. In the episode “Hang the DJ”, it follows two people in a dating simulation. A virtual simulation runs a 1,000 times to see if two people are compatible, which then shows up on their dating app in the real world. In the show, it follows two people who in the simulation match 998 times, providing their real world selves a probability of 99.8% that they are meant to be together. While an extreme extension of this, it raises the question of how machine learning and computer simulations can impact this area. What works well about the simulation model is it overcomes the challenge of determining what variables to analyze. By effectively being able to analyze “everything” they free themselves of the challenge of only analyzing swipes and likes.

On November 15, 2018, MM commented on Xiaomi: Fueled by Open Innovation :

The use of open source is quite interesting here and I wonder where the main benefit comes from. Is it from the companies ability to build better products based on input from their following? Or is it based on the open source nature encouraging and building up a large “fan base” which has translated to a large customer base?

On the IP point, it’s concerning to see they are facing lawsuits in many geographies. Given its rapid diversification and expansion into industries beyond smart phones, it is not surprising that they have been challenged to adequately monitor and control that products coming through their platform are not built on protected IP. I imagine that in the search for rapid growth, they’re okay with taking on these lawsuits, believing that slower growth with tighter controls would ultimately be more costly for them.

On November 15, 2018, MM commented on GE Additive: Additive Manufacturing and Aerospace :

Given the lower waste, higher flexibility and higher efficiency of 3D printing, it makes sense that aerospace suppliers like GE are turning to 3D printing to build low quantity pieces. Going forward, I wonder about the overall role of 3D printing in the industry. Will it be primarily utilized as a way to more efficiently produce current products that are produced in standard ways? Or instead, will it primarily be used to potentially create new, innovative products that previously were inconceivable based on old manufacturing capabilities? It will be interesting to see how the industry evolves as these capabilities expand to enable completely new products to be produced.

The use of open innovation at LEGO was surprising, particular as it is a product company rather than a technology company. To tie it to another key theme, it will be interesting to see how they deal with additive manufacturing / 3D printing. If they are already outsourcing innovation and enabling their customers to develop their own product sets, how can they defend themselves from those customers just printing the components themselves rather than purchasing them from LEGO? Presumably, customers can completely cut LEGO out of the equation, both designing and producing the toys themselves. It will be interesting to see how they address this dynamic and if it affects how they manage open innovation currently.

This is certainly an interesting topic with relevant implications for the US military. However, I think it is also relevant to think about the potential implications for other militaries and perhaps more importantly, militant groups that are not as well organized. It appears that additive manufacturing could level the playing field for these groups against more organized, established militaries. Currently the US military benefits from a really strong logistical and supply network, whereas the ability of less organized groups to print weapons themselves can provide them a better opportunity to be competitive, overcoming their current weaknesses. When less organized militant groups can manufacture their own weapons, built from open source directions available online, instead of going through the complex challenges to source them in other ways, they are better positioned to be competitive in the battlefield.