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On November 15, 2018, live4ever commented on Ambulnz, Inc. :

Great article and loved reading about your startup! In terms of adaptability of the UI, is there a training process for the EMT’s? Do you foresee Uber or Lyft entering and overtaking this space and what will be Ambulnz inc. relative advantage other than having a first-mover advantage?

On November 15, 2018, live4ever commented on Using Open Innovation to Solve the Ocean Plastics Problem :

Loved the article and the social entrepreneurial angle that fits with Plastic Bank’s mission and the very relevant target countries. My concern is around tokenizing the incentive compensation system for the waste collector. First of all these waste collectors are not technologically educated or equipped to make or receive such transaction, the article doesn’t address how Plastic bank is addressing the physical aspect of the transaction. Secondly, I can understand the reason behind using blockchain for tracking the transactions but we know every crypto token these days gets traded and this might create huge volatility and inconsistency in the cost of services that Plastic Bank wants to provide to the low-income people for whom this might be a single source of income. Maybe I am interpreting the blockchain innovation mechanism incorrectly but to me, this tokenization might adversely affect one of the goals of the company that is to provide a fair wage to collectors.

This is an interesting read and raises some valid questions, but the author is right in that he falls for the common myths and hype of the industry. Healthcare companies- Medtronic included use 3D printing as a tech in R&D and few direct personalized healthcare applications. The idea and the tech behind it are quite common, and the best example of this is in dentistry – where doctors have been filling cavities and applying tooth caps with personalized 3D printed inserts for years now. Additive manufacturing as a tool is still evolving and right now cannot provide the economic advantages of traditional mass manufacturing, and Medtronic is right in its decision of not using it where it doesn’t make economic sense. Also, additive manufacturing is just a tool and should not be considered as the great leveler in R&D competencies. Real innovation doesn’t come from just having access to a tool.

Interesting article! Coming from the same industry, I had exposure to BHGE’s Predix platform when they presented to my previous company and back then we had various concerns on the same. Some of it like ensuring continuous feed and the quality of the data that you have picked in the article to more intrinsic ones like transmission rate from offshore to an onshore server given the extensive dataset to concerns that whether they understand the data being fed. GE is a major supplier and OEM for offshore equipment but from the moment they sell their equipment to 5 or 10 yrs later when they might see it in their shop for bigger overhaul or repair work, they lose the insight on how their equipment is used on the field between this timeline, and what sort of maintenance philosophy is applied. To teach the ML algorithm to better predict the maintenance requirement, they not only need their own design parameters but more functional knowledge of the equipment. They not only have to extensively work on gaining this confidential data from the partners but also develop either in-house expertise or long-term partnership with users to bridge this gap. Secondly, they also need to have a strong business case on how the use of ML will gain them a competitive or commercial advantage for eg, if you go down the route of predictive maintenance, it will reduce their revenue forecast (less use of parts, services etc) so what will drive GE to use Predix to change the traditional ways of this industry?

On November 15, 2018, live4ever commented on D.E. Shaw: Double Down or Diversify? :

This really is an interesting read, and firms like D.E Shaw are on the right track with investing in research in this new field. As for the question of diversifying into other types of trading strategies, that depends on how well they test and simulate their AI models before deployment. Machine learning algorithms are expanding the scope of their Quant models and are rapidly approaching scenarios where AI generates its own algorithms and strategies – one day even generating a hedging strategy against its own durability.

On November 15, 2018, live4ever commented on Boeing: Additive Manufacturing Adding Enough? :

Very interesting article and coming from a similar capital expenditure intensive industry going through a turbulent market shift, I can fully relate to the author’s frustration on only looking at a smaller dimension of cost reduction vs. realizing bigger potential with 3d printing. However, sometimes taking incremental steps to first realize the roadblocks and challenges before going full swing in implementing change processes can be beneficial. For the airline industry that has a strict regulation for safety factor consideration in material selection, safety parameters, and design choices, maybe there are limiting factors with the 3d printing that are yet to be uncovered or factored in. I was also looking into Boeing’s 3d printing strategy from a different perspective of vendor selection that Boeing is working with. Generally, Scandinavian countries are more expensive to do business in terms of labor or other service costs so I feel it is an interesting choice of partnership especially when the focus in on cost reduction. There are other competitors in the titanium 3d printing marketplace such as Timet or lmiaerospace that can possibly provide higher cost saving synergies considering a majority of Boeing manufacturing facilities are in US. Enjoyed your post! Great work!