Thanks for sharing a very interesting use case for machine learning that is actually being applied in real life today compared to so many of the machine learning stories we read about that are more “marketing fairytales” of benefits to come in the future. It is easy to see how machine learning can significantly improve maintenance schedules, and I wonder if machine learning can’t also be used to identify real time flight conditions and over time analyse how weather or other aspects could be analysed to even more precisely predict/model maintenance schedules.
I believe the biggest challenge for RR to reap the benefits of machine learning lies in your question reagirding RR’s actual ability to adapt, develop and apply new cutting age software and data analytics innovations. Having seen first hand the challenge of attempting to transition a hardware based company to a software driven approach (although admittedly from an investor perspective rather than engineer…), I believe RR would be well served to start this journey in partnership with an external party experienced in machine learning technology and application. Done correctly, I wonder if such a partner could potentially significantly speed up the adoption curve for RR in machine learning while they develop their own internal systems and teams to spread the learning across the organisation. Regardless of the approach RR chooses to take going forward, I have no doubt that effectively adopting machine learning in their jetty engine development and maintenance process will be crucial for RR to remain at the cutting edge of jet engine development.
The topic you address might be the most challenging and important of our age of digitalisation and you do make a good point, with an ever increasing and fast moving landscape of potential cyber threats open innovation and sharing of threat intelligence will likely be an important source of knowledge and increased security. There is no doubt that the DoD could benefit from improving their bounty programs to access the same level of innovation as other private sector technology enabled organisations use to expose vulnerabilities.
However, I do believe there is one critical element missing that is relevant to the DoD. As an important organisation for the worlds largest military power, the threats the DoD face in cyber security will likely be the most sophisticated in the world and therefore their defence and response system will need to be even more sophisticated. This level of sophisticated cyber security knowledge is highly limited and highly sought after in today’s environment and I would question whether a model based on crowdsourcing can really the solution rather than just a part of the solution that helps with the low hanging fruit (patching etc.).
Personally I believe crowdsourcing needs to be a part of the solution to the DoD’s cyber security defence, but that it will likely remain a small part as the DoD will need to continue to rely on training and retaining a staff of highly skilled cyber security staff, contracting highly skilled security services firms and buying/trading threat intelligence with other government agencies and private organisations to keep the organisation safe from cyber war and crime.
Thanks for opening my eyes to how shell is already utilising additive manufacturing!
It’s fascinating to me to understand how they are using 3D printing to make prototypes to make it easier for the engineers to understand how what they are working on fits with other parts of the project and see the model of their project in real life. I have heard from many of my friends who are O&G engineerers how frustrating and difficult it can be to work on a very small part of a larger product and not be able to see how it actually fits in with the larger project. However, I can’t help to question how helpful it actually is for the overall process to have a miniature model of construction projects that will ultimately turn into some of the worlds most massive and impressive construction and drilling equipment. Will the miniature models really help the engineers understand the load balancing, structural stability and unforeseen issues for the real construction in a completely different material? I am not an engineer and admit that I am really not qualified to comment, but I would love to hear your view on whether this is really a “nice to have” for the engineers or something that makes a substantial impact on their large scale projects.
Thanks again for the interesting paper!
As others have mentioned I really appreciated reading about this application of additive manufacturing, definitely one of the most interesting application methods I have come across. That said, as you allude to in your final queastions, I am inclined to think that their technology and production process might not be a large competitive advantage. As soon as competitors are able to use the technology after the patents expire and/or competitors develop similar or better technology, the only competitive advantage of Align will be that they were the first movers. Therefore I believe they need to use their first mover advantage to solidify their market position through developing better customer acquisition and distribution channels than their competitors, something that might actually create a lasting competitive advantage.
Additionally, I believe you are onto an even more interesting topic with your question related to their data. The major competitive benefit they currently have is to be able to produce faster and at a lower cost than competitors, significantly increasing adoption potential. If they can use the data to develop a better approach to treatment that can be proven to achieve results faster than competitors I believe they could have a major sustainable competitive advantage.
Although I do see your concern related to Alibaba’s market power and the potential impact they have on consumer choice, I personally believe what Alibaba does actually significantly increases consumer’s utility. The middle age man buying cycling gear will for instance not have to spend hours searching for the right new cycling gear, he will see relevant ads when he is browsing the app and can chose for himself whether it is something he wants to buy or not. I believe the only real alternative is for the same user to be shown a large number of ads that are not targeted to the user, leading to a high number of ads that will be viewed as interruptive to the user.
I do agree that we should proceed with caution with the tech titans that have become so dominant at an unprecedented pace, but as long as personal information is kept safe from cyber criminals, are collected willingly by an informed consumer and are used in places where the consumer clearly views them as ads, artificial intelligence in personalisation is in my eyes simply an improved version of advertising that leads to higher consumer utility. It is then up to regulators to ensure that no one player in the economy gets too much market power or misuses the personalised information by mislabelling ads, steal information from consumers or sell/lose user information against user’s will.
Amazing to discover that there are others in our section that have realised that it is the food supply chain and what we eat that is the largest contributor to climate change and actually not the more widely assumed transportation/energy sectors. Although I do think Clover is using open innovation in an interesting way, I side with you in that it will be hard to scale a model that is based on consumers participating in weekly tasting sessions before a product is launched. I wonder if making it more of a digital voting process might be more scalable. Clover could for example open for customers to send in menus suggestions and open up for a voting contest for a sub set of the submitted suggestions each quarter, awarding the winner of the contest free Clover food for a year. In my view, that might be a more scalable model for engaging customers in open innovation once the chain goes national.
If Clover were to stick with the current appraoach to open innovation, I believe they would need to run a more decentralised version of it as they scale with potentially different menues in each region. While this might work for Clover from a marketing, customer and business perspective, I wonder if they would still be able to achieve their goal of having an impact on the climate impact of the fast food industry as it might lead to high levels of food waste and a less climate friendly supply chain at scale.