Ian Hossfeld's Profile
I think that content can be successfully created by “crowds”, but it will still require a writer and a director to tie the concepts all together into a coherent vision. One way this could be implemented would be to run a competition to solicit ideas for the general overview of the plot. By providing the public with some basic information about the plot, the writer could then reach out to the public at various points to receive feedback about potential plot twists as well as provide opportunities for new ideas to be submitted. After the script is completed the director could then publish storyboards for various scenes to see which ones the public liked better. By taking this approach the public wouldn’t have perfect information about what the final product will look like. Therefore, they will still be excited to see the production and, if anything, their interest would be further piqued because they played a part in the production.
I like that San Jose is empowering its constituents to be part of the solution to address city needs. This gives everyday people a greater sense in ownership and provides the city with ideas that they were unlikely to come up with on their own. While the manager-council form of city government may take longer for concepts to scale, I think San Jose is well positioned to implement these changes. I believe this to be true because the city manager is not an elected official and therefore generally speaking has greater longevity. So while the concept of open innovation is being driven by the mayor, if the city manager believes in the system they will continue to implement the practices even if a new mayor is elected.
I think GE is smart to commercialize its expertise in additive manufacturing. As an industrial conglomerate, these machines and services are a growing market that the company is well suited to serve since all of their business lines will benefit from any R&D used to develop new products. I agree with your assertion that it is risky for GE to focus solely on the largest most technologically advanced. The pursuit of the “high and right” customer leaves the company vulnerable to disruption as new players enter the field with smaller less costly designs that technological advances then enable them to compete against the large capital-intensive project created by GE. Because of this I think that GE would benefit by also being dominate in the mid-size company market as well as large scale manufactures.
I think one way that New Story could address the fit-out issue is combining 3D printing with modular building. A module that was one-part bathroom and the other part kitchen would contain all the water and sewer hookups required for a basic home. Modules can be pre-built in a factory, to include appliances and fixtures installed, and shipped to the construction site where the house can be built around them, preventing the need for a crane to lift them in place. By using a pre-built modules the entire house can still be completed within a day and be entirely fitted out.
I agree with you that farming will drastically change during our lifetime. While I was on active duty, we used Persistent Systems Wave Relay radios which are also used by farmers experimenting with autonomous and remote-controlled farming equipment. I am unsure of when vertical greenhouses will become economically viable. In general, the cost of land and building costs have grown a lot over the last real estate cycle making even traditional multifamily and office development challenging. Secondly the rise of e-commerce has made industrial buildings, which had traditionally been the cheapest property type both by land value and building cost, much more sought after for last mile distribution warehouses. This being said I do see small scale vertical greenhouses growing in popularity as the farm to table and locally sourced movement grow in popularity.
I enjoyed reading this article because the idea of bias in machine learning is very thought provoking. Just as in any industry, it makes sense for law enforcement to utilize big data and machine learning to better utilize their resources to keep the public safe. While removing prejudice and bias from data sounds on some levels easier then removing bias in real life, it obviously is quite difficult to do in reality. Moving forward I think it is very important that organizations work hand in hand with the partner entities identified in paragraph two. This is important not only to provide a comprehensive approach to solving the issue of crime, but also working with them to quickly identify when the machine learning algorithm may be displaying biases. Having partner entities work with police departments and PredPol engineers to identify potential police interactions that then become data points affecting bias in the learning algorithm, there is a higher likelihood that the PrePol engineers can correct the effect these instances have on the AI.