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On November 15, 2018, MM commented on How crowdsourcing is changing the Waze we drive :

When I was commuting daily in the Bay Area, Waze has helped me save countless hours from my commute, so I’m quite invested in this topic! I had no idea that Waze was actually working with local authorities, considering that quite a few people (myself included) use Waze as a way to avoid these local authorities. But I definitely see immense potential in the CCP program, especially in areas where traffic can be a huge source of concern. And like you mentioned, Waze is almost the model platform for demonstrating crowdsourcing innovation. So my question is, where does Waze see itself going from here? It can keep accelerating the speed of its partner signups, but once that is in place, how can they continue to innovate to deliver on their promise of “outsmarting traffic, together?”

On November 15, 2018, MM commented on IBM’s Deja Vu in Disruption :

As someone who knows very little about open innovation, I find your article extremely thought provoking. All the companies that I have worked for have been extremely diligent in protecting their IP, so the thought that IBM should operate “without enforcing patents, intellectual property, and for-profit infrastructure” to be completely terrifying. Although if the upside of doing so is that they get greater innovation than they otherwise would, then maybe then it’s worth it. But in this scenario, I can see how society would benefit, but if they won’t be able to control or monetize it, how can IMB really capture the value?

Fascinating article! I actually worked on a project for an OEM supplier, and the issues that you raise in your article are considerations that they are facing especially as regulations around fuel efficiency are expected to increase over time.

To answer your questions, I think that Ford can definitely take steps to protect its IP. My understanding of 3D printing is that the source code is essentially the formula, which can be extremely difficult to recreate. Ford definitely can sell the code much like software can be sold so that a customer can print a part elsewhere, but unless there is a data breach, I don’t see why they couldn’t profit from their IP. I’m not a huge car person, as in I will drive anything that will take me safely from point A to point B, but I think there are plenty of people who do care deeply about their car’s appearance. It might be a bit niche, but it should provide a somewhat stable revenue stream.

Great article! Appreciate the clarity in how exactly additive manufacturing can help GE reduce cost and complexity while increasing durability for their jet engines. In the paragraph where you bring up fuel nozzles in LEAP engines, you reference the fact that this was the first FAA approved part. So for every part that GE develops to replace a conventionally manufactured alternative, does it need to get FAA approval? And if so, does GE take the cost or timing of that approval process in determining the scale of how they should incorporate additive manufacturing into their business?

I think your final closing question is crucial in determining just how far Walmart’s investment in ML/AI can take it. Having grown up in an area where Walmart is the place to shop, I’m not convinced that the “bells and whistles” would be attractive for that demographic. In fact, your proposition for RFID tags within a household has some elements of Juicero, the Silicon Valley startup that imploded spectacularly. Rather than the traditional way of determining whether the product was fresh or not via touch/smell/expiration dates, customers would scan a QR code. This brought a lot of ridicule to the company, and I worry that at some point, the technology, even if it’s there, is just not necessary. And as for Walmart’s current target demographic, they tend to shop for best prices and value, and Walmart may not be that all the time. So by trying to “lock in” customers to Walmart, I wonder if that will do more harm than good.

On November 14, 2018, MM commented on Machine learning as a tool to predict future earning power :

Such an interesting concept! I think ML can be hugely beneficial for your company, since like you said, the algorithms will become more accurate at predicting income over time. I want to build upon JP’s point about your business plan. There are currently companies out there (Earnest is one that comes to mind) that will give different interest rates to students depending on potential. If I’m understanding your business correctly, however, your point of differentiation is that you’re actually taking a percentage of future income. To me, as a potential client, I’d almost be hedging my bets if I finance with you. So if for some reason I earn less than what I thought I’d be, at least I won’t be paying as much in student loans as I could be. I wonder though if by constructing your business this way, you might inadvertently be cast into the market for lemons, with people who know they’ll earn less than what a model predicts they should being the majority of your customers. I also see a potential problem with future moms who choose to work reduced hours, can / will your ML algorithms account for that?