Alejandro Martinez's Profile
Very interesting article. I agree that this is very scary and frankly terrifying in todays world, yet I do disagree with N. in the sense that creating a blue print for a gun does not differ from creating a blue print for a potato cannon or a sling shot. I disagree with Defense Distributed and their cause, yet we cannot treat DD different that we would for any other prototype. I believe though that the government should intervene in the 3D printer to introduce a red flag or even prevent the user of the printer to print gun relating materials, in the same way that current scanners and printers prevent users from copying treasury notes. I think gun printing is scary and dangerous, but I do not think that DD should be judged for placing blue prints of how a gun work.
I think this is a fantastic article that highlights the multiple opportunities that exist within the DoD to improve its current operating procedures. The article shows how the existing process is flawed and can lead to potential issues given that the members are not aware of exiting issues, and how IA will really improve the process, my concern with moving to IA to help with the maintenance of these expeditionary weapon systems is that in a deployed location the use of cyber capabilities is becoming more dependent than ever, thus if all maintenance of expeditionary weapon systems is conducted by a cloud on IA what will happen when the connectivity in the battle field is limited? Could enemies eliminate an entire tank formation by blocking their access to internet?
The article is great at bringing to light the vast amount of opportunities that the DoD has to improve its logistics, and at the same time improve the Just In Time supply of necessary equipment. My question with the availability to utilize 3D printing as a method to circumvent the current supply process has to do with the multiple iron clad contracts that the DoD has in place with suppliers to issue parts. In many cases the suppliers that the DoD utilizes have patents over some of the necessary equipment that must be supplied for specific weapon systems, thus if the DoD begins printing parts for those weapon systems the suppliers might consider the DoD breaching exclusivity contracts. My question would push forward the argument by asking if the DoD with 3D printing can negotiate better terms from their suppliers, and if they can also utilize this new technology as a cost saving strategy for future weapon system negotiations.
I think this is an amazing investment by the DoD not only to take care of the wounded members but also to help drive the medical technology forward. By being able to 3D print organs many service members lives will be saved not only in garrison, but hopefully, in the far future, in remote field hospitals where access to a larger hospital is not possible. My only hesitation with the new technology would be the willingness of the service member to adopt the new technology and be willing to accept a 3D printed organ. History has proved, time and time again, that the DoD tests multiple drugs with service members placing them in many times in harms way, thus many service members might be hesitant to accept this new technology as they might see it as another gimmick by the DoD to test new technology that might back fire on them in the near future.
I think this is a great article that shows the predicament of many nations as they seek ways to improve their military with limited funds. Additionally, I strongly agree that as time progresses the talent of individuals seeking to join the military is diminishing, thus the governments need to find ways to improve their armed forces when a big portion of the capable population is not interested in joining its ranks. My question with developing machine learning for this situation is that if the UK modifies their force due to inaccurate machine learning conclusions, the results of this will be not only very long lasting, but can also place their current military force in mortal danger, thus it is of vital national security to ensure that the machine learning results are accurate before any action is taken.