Thank you for this very interesting article! I fully agree with the benefit of building a Reverse Image Search tool for customers but I wonder whether this may not jeopardize the fashion industry’s economy. A key part of this industry relies on continuous innovation, which involved significant costs (designers, prototypes, etc). The only way this process can be economically sustainable is to have a (at least temporary) payback period before this innovation is copied by retailers and the customers informed. By reducing this pay back period, there may be a risk that fashion brands have lower incentive to innovate and that ultimately customers miss future potential innovations. Although this works in terms of shape and colors but another critical aspect may be the comfort and fit and I wonder if Reverse Image search tool can achieve this through AI?
Thank you for this interesting article! I wonder how Am can prove itself cost efficient versus manufacturing process, given the absence of economy of scale? I believe that another limit of this technology may be its durability. As time goes, construction technology becomes more and more advanced but the averaged useful life of houses keep reducing. Therefore one could wonder if this solution is really cost effective once we take into account the duration until experimentation proves that the quality of the construction is guaranteed over a similar length of time. This is obviously all the more crucial than there are significant safety issues at stake.
This is a great essay about one of the most exciting use of AM as of today! However I’m quite surprised about the cost effectiveness of this solution, which plays a key role to give access to accommodation to the homeless. Normally 3D printing simply works best in areas where customization is key. In this case, it seems that the construction would be rather standardized, thus 3D printing would have to compete against scale driven manufacturing process, which benefit from economy of scale. Therefore I believe that this solution could be excellent to fit specific demand but I doubt about his implementation’s success on a larger scale.
It’s interesting in the current context to think about the implementation of machine learning at facebook to identify fake news. However I doubt about the potential success of this application since there is a degree of subjectivity inherent to any media. French news media has already sprung into action by opening a fact checking service to stop fake news items in their tracks and I believe that as of today human control is the only viable solution. Of course as the volume of data grows bigger with time the chance of handling misinformation will become challenging for humans and hopefully machine learning will keep improving and prove itself efficient.
Super interesting article, thank you! Although I never thought about this application before, it seems to be a natural match for the military during operations. Logistics being extremely complex in war times, this solution could help fixing a lot of complicated situation. However, this argument only holds if the replacement parts can be sustainable during at least the entire length of the mission. According to Benjamin Kohlmann’s comment it seems that AM don’t deliver in consistent quality and durability. Given the risk at stake, I don’t think the military can implement AM in the long term as long as this issue is not fixed. Moreover in the cost analysis, I believe that this only make sense if an external logistic is not required anymore to fix the underlying issue. However I would argue that military cannot be assessed the same way as a business operation and that we should value the critical gains in readiness during operations in stressed conditions.
I loved this post! This technology can really change how transportation companies operate. Don’t you think that this technology could also apply to the airline industry? I’m also confused why DB has not internalized AM in house. I would assume that this is a kind of safety net, in case safety issues were to arise. However moving forward this solution would be way more cost effective and would enable a full transparency between DB and the engineering team, which can potentially not be achieved if the third company also collaborate with other rail companies (new developments, etc)