AM is the future of manufacturing. This technology needs players like Boeing to heavily invest upfront to drive costs down in the future. What concerns me is the quality control processes that need to be implemented to usher this new age of manufacturing. The future of manufacturing unions need also be considered. How will the human element drive or inhibit the acceleration of AM? Aviation may also pose safety concerns that would change the credibility of AM for years to come. Perhaps big industry can instead build AM’s capability my investing in printed unmanned rockets to secure public confidence?
I think Eli Lilly should branch this OIDD program into its own business. Pairing OIDD with the Eli Lilly name may deter OI innovators who may be weary of big pharma. The key element in fostering the relationship between the program and researchers is the trust and security of information. Having stipulations that Eli Lilly must be the first to enter negotiations for commercialization may draw the appearance of inhibiting social good for the purpose of securing revenue. Although Eli Lilly is allowing the use of it own proprietary R&D capabilities, I feel as though moving to no stipulations would improve the company’s image even more. When considering the program’s expansion, this action may be necessary to garner that additional periphery support.
Fortunately Toy R’Us will still be in business (for the time being at least)! LEGO has often dazzled us with its innovative creations and themes but a move into open innovation is truly key to remain dynamic in the toy industry. I think what is also essential is how to expand their open innovation ideas to other platforms like technology or media. The LEGO brand has evolved into one that moves across different mediums and its OI campaign should allow consumers to reflect that. As the company moves forward, I think the sources in which they collect inputs will be critical to their future strategy. Should LEGO look into surveying customers at the movie theater about toy designs? These questions will expand the “talent pool” and draw more consumers into the innovation process.
Often when scrolling through Netflix, I am disappointed by the recommended movies that usually populate for me. Although the films are usually within my desired genre, I never have felt that the algorithm has read my preferences as well I would have liked. Perhaps Netflix should consider letting users add input to refine their algorithm. I’ve seen similar examples where users can search for music genres and artists and from that listing, playlists are formulated that do a better job of pinpointing a relevant starting point. Film preference however, may have a higher standard deviation from a user’s “medium” genre choice. Allowing for input would decrease variation and allow machine learning to begin at a more accurate starting point.
Great article. I think AM is the future of manufacturing. What concerns me is the substitution of automation for construction workers. In developing countries like the Philippines, construction provides a crucial outlet for many citizens to make a living. I’d like to see how the human element plays in the construction of these printed homes. Are people serving merely as a quality control supervisor or does the equipment require multiple operators. I think the challenge with technology is not only making things easier for society, but also creating value by diverting the work force to larger issues in need. Perhaps the adoption of AM can push more employees into the related fields of architecture or city planning?
Often ignored for more “popular” industries, the benefits to improving agriculture could not be more understated. An almost perfectly competitive industry, every move to conserve resources or increase crop yields will pay dividends to the future of the human species. The US military has similarly used machine learning to predict maintenance schedules on its vehicles, so I see no issue in believing that JD can produce the same result. I hope to one day see the agricultural industry be fully automated. Machine learning may also allow farmers to rent equipment at a low cost, rather than owning and paying high up front capital costs.
As technology improves, I wonder if we could also use the MagicBands to gather bio-metric data from consumers. Obviously the collection of this data would require Disney to jump through massive legal hoops, but if we could capture heart rate or temperature we may be able to predict a customer’s emotional response as they interact with the park. Disney is all about creating a “magical moments” – if we could define what makes a moment special by observing bio-metric data we may be able to design a more emotional experience for park goers.