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Will Craig
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Terrific topic and I absolutely believe additive manufacturing has the potential to truly transform a variety of industries. That said, given the current state of the technology, I don’t think ISRO should go all in on its own captive manufacturing capabilities. The risks at this time are just too large given the government, safety regulations, and idiosyncratic risk of a rocket launch. As you correctly stated, additive manufacturing still has difficulties producing uniform parts with the same molecular composition. ISRO should begin to incorporate to proven parts and process from 3rd party partners and allow them to shoulder that risk but wait until the process is at a more established state to build out proprietary capabilities.
With an eye towards the future, the most impressive value of additive manufacturing is to source local materials to build structures and components. In this way, ISRO need not ship a colony of structures to the moon – only the additive manufacturing machines to produce those structures. It also has tremendous value in providing emergency just in time repairs for critical components in austere locations – such as a space station.
Great article! Moneyball started this all, but improvements in data collection, analytics, and machine learning have taken that concept to incredible levels. With the tremendous amount of data available, a decision maker can become easily overloaded and lost in the noise. Therefore, the competitive edge does not lie with data or analytics, but with the human component that decides what data is relevant and what is not. It is here where a Baseball team can gain an edge over opponents with same analytic capabilities. It is not about selecting a player with good stats, but a player with the right stats. Though these analytical capabilities are important; as we saw with Oakland during the Moneyball era or Boston in 2015, analytics can’t solve everything. Money matters and the best players go for a premium. Analytics allow you to help find undiscovered players to fill holes in the salary puzzle.
I’m a firm believer that the most talented and advanced programmers and hackers will never work for the U.S Government due to wages, bureaucracy, and stigma. I do believe, however, that ethical hackers are interested in helping the government improve its systems. The government may not be able to employ them full time, but they can use them in a manner befitting a consulting to test for weakness and advise on improvement. As technological advances continue, this form of testing is not so much an option but a necessity. The scope of such work is rightfully a tricky debate. At the very least, it should include any gateway or protocol that can be reasonably accessed from public servers for these servers are likely already under some form of attack. Closed networks and other compartmentalized systems would require a higher detail of control and vetting in order to employee a private hacker for testing purposes. The government cannot afford to ignore potential weaknesses in such a critical infrastructure node.Ultimately, it is much better that the government discovers its own weaknesses before its enemies do.
WHOOP has some very interesting potential. I’m skeptical of the healthcare benefits but extremely intrigued by the commercialization potential of the data and the associated analytics. Imagine a world where athletes could commercialize their performance data. Concerned about your Fantasy Lineup for the weekend? What does WHOOP say about the recovery rate of each of your players. Want to bet on a team to make a deep run into the playoffs? What does the WHOOP data say about their endurance level and recovery programs. With this in mind, I think WHOOP should be very careful about outsourcing its innovation and data. Instead, it should look to partner with major athletics leagues, star athletes, and other professional sports to keep both its data collection and analytics proprietary – those two facets provide tremendous value to the company.
Given the recent success of SpaceX and Blue Origin, NASA’s hold on the imagination of young scientists and aspiring astronauts is rapidly deteriorating. Why deal with a bureaucratic government agency that is burdened by politics and a lack of funding when talented people are paid more to do more at private organizations? Space is truly becoming more accessible, and NASA is handling its needs in a very intriguing way. I love the idea of appealing to the general public’s passion for space and using that to source open innovation. NASA is uniquely positioned to accomplish this because of the humanitarian nature of its mission. I have concerns, however, with longevity of this “open innovation” relationship. As this “final frontier” becomes contested and militarized, what will happen to NASA’s access to this open innovation? From previous experience, I can say that open innovation does not work in an environment where state secrets, technology, and tactics are closely guarded. It is a very real possibility that as Space becomes privatized and more accessible, NASA is forced to become less about exploration and more entrenched in U.S policy interests. If this were to unfold, it will likely be less able/willing to engage in open innovation and once again more reliant on the government. It is important, therefore, that as NASA takes advantage of its “open innovation” relations it does not lose track of its traditional government funded R&D programs.
Great article with some solid points about the benefits of Machine Learning in Aviation. While one could spend a significant amount of time addressing all the potential benefits, I’ll focus my comment on the potential to improve maintenance. Reducing maintenance down time is a massive component of maximizing revenue an airline receives from asset turnover. Current maintenance inspection and servicing methodology, both in civilian and military application, is generally based on engine operating time, flight time, or calendar days. While these metrics are based on safety and a general assumption of service life, they fail to take into account dynamic stress on components such as positive or negative g, severe turbulence and loading on wing spars, material contraction and expansion due to extreme temperatures, and the effects of corrosion from salt water or sand in drier climates. If Emirates were able to collect all this information, appropriately apply this information to events experienced by the individual airplane, and create a customized maintenance cycle – it could have a significant impact on asset optimization by addressing service concerns only when needed. To your point, the capabilities and data are becoming widely available. What matters are the metrics a company decides to focus on, those it chooses to ignore, and how it goes about implementing those insights.
Mike – great paper on a topic of increasing importance. The Department of Defense has numerous resources at its disposal, but technological innovation and the associated manpower requirements are far from the top of that list. Rather than invest in collection AND analysis capabilities on-board surface ship combatants that have both limited manpower and internet band-with, the Navy should use its deployed assets (both sea going and airborne) as information collecting nodes that feed data to a centralized shore location for analysis. This would allow the Navy to focus its scarce intellectual and technological resources in one location. In all likelihood this data is not capable of immediately changing the course of a dynamic battle. It, however, may be able to influence the tide of a longer war. With that in mind, the analytic capabilities belong at a strategic level, with information collection at the tactical level. As to private sector aid in combating this problem, given Google’s reluctance to support similar objectives with machine learning regarding reducing collateral damage with drone strikes – I am not optimistic.