To build on a challenge you bring up, working with the FAA, airplane manufacturers are notorious for how expensive their code is, given the intense regulatory environment. It seems that code has to be written, rewritten, checked, and re-checked so many times that it becomes almost prohibitively expensive to add significant amounts of new programming. Are those costs simply an inevitable part of doing business? If the requisite ML algorithms take a significant amount of time and resources to write, will Boeing be willing to make the investment? Can one of the startups you mentioned do this at lower cost than a bureaucratic juggernaut like Boeing?
PG&E is facing a lot of pressure this year after the ferocious wildfire season in California, some of which may have started at utility facilities. Perhaps a machine learning algorithm that looks at factors that could cause wildfires would be helpful. I imagine they could use that information to make targeted improvements to facilities that reduce the likelihood of a substation sparking a fire, though finding appropriate data to feed the algorithm may be a challenge, and it may simply be too random and hard to predict.
To Ratnika’s point about engaging other stakeholders in the firearm industry in this discussion, I wonder what the NRA’s take on the issue would be. While they’re certainly not advocates of gun control, their corporate members are companies that profit off of selling guns, not 3D printer manufacturers. Would they have a vested interest in preventing the spread of 3D-printed guns, and might they be willing to come to the table on that premise? They’re an unlikely ally, but competitive pressures may make for strange alliances.
This is really fascinating! I’m curious about the process DB uses to print the parts themselves. Do they have to get CAD drawings from the original manufacturer? Are parts manufacturers willing to hand over or sell those files? Or does DB create the files themselves? What would be the safety implications of “reverse engineering” parts in that way?
I have to imagine that some parts are pretty complex, too. Does it seem like this technology could work for the majority of frequently used replacement parts, or will it really only apply to a few?
Interesting approach for addressing the opioid epidemic–at this point, I think any thought applied to the problem is helpful. But I always wonder, how often do solutions developed during a hack-a-thon actually come to fruition / market? I have a hard time believing that solutions developed over such a short time span can really address the complexity of such a tough issue. Is the HHS just paying lip service here, or do they really expect to make a dent in public health outcomes?
I’m curious how for-profit entities providing library IT services (Ex Libris, Innovative Interfaces, etc.) will be able to compete with an open-source technology like FOLIO. It’s interesting to see how, in the world of web browsers, there’s a mix of open-source tech (e.g., Firefox) and closed (e.g., Microsoft Edge) in use. The common factor there, however, is that all of the options are free. If Ex Libris currently charges for its technology but FOLIO decides not to, will anyone pay a premium for the non-open source solution?