It will definitely be interesting to see whether JP Morgan extends their coding training in the coming years. The trend of increasing analytics training for more ‘traditional’ hires is something we see in the consulting industry as well, so it’s not surprising that it’s happening in banking as well. Yet I do wonder what the benefits are of providing traditional banking hires with coding training, as opposed to hiring data scientists specifically. I imagine that it would be very difficult to train a banker up to the level of a data scientist and vice versa, so I’m curious as to whether they continue to cross-train both, or if they find a more synergistic way to have those two different functions work more collaboratively together.
It is interesting to think about 3D printing as cutting down R&D costs for a company like Chanel by reducing incremental dollars spent on prototyping mascara, since I suspected their runway collection 3D printed garments were more for show than for cost efficiencies. Along those lines, I wonder if they are looking into whether 3D printed components could be used for any of their garment production. That being said, they are likely to get more press for customer-facing 3D printed products than they would for back end improvements, so it all depends on whether their motivations are more focused on cost reduction vs. upside
The machine learning initiatives they have implemented to date are very interesting, and seem quite innovative for a brick and mortar grocery store. From what I understand, Kroger is fairly mission-driven and people-focused, especially with their front line employees, to a greater extent than some other grocery retailers. Given that, I do wonder what the effects of expanding machine learning into things such as auto-pick in distribution centers would be in terms of morale (though I do understand the need for cutting costs if they want to exist in the long term).
I like the question you pose about whether we will continue to rely on physical documents such as IDs and passports in the future. When it comes to sensitive processes (such as airport security or even local voting), it seems as though physical documents and human interactions are valued to try and reduce risks of hacking / digital alteration. Yet that’s also subject to human error. It seems as though Jumio’s deep learning approach will serve them well for pioneering this work, and I’m curious to see how they are able to form partnerships over the next few years in order to help train the systems to an even better degree.
Agree with the response above–losing connections with customers could be a risk as these types of companies increase their use of machine learning and big data analytics. That being said, there are opportunities to leverage machine learning even further with unstructured data sources such as social media to further enhance customer understanding.