To your first question, profits from a profitable innovation should be shared among contributors. As I understand, whole point of this open innovation initiative is to foster collaboration among health researchers. Like in any other industry, there are people whose main motivation was to make money, and whose main motivation was to help people. If some researchers start making money on the foundations of other researchers, I do not think this initiative will be sustainable. Similarly, in healthcare industry, some developers are paid royalty fees even if they do not hold a patent. For manufacturer, the reason behind that is to pay costly development effort to developer and fasten the money making process. If profits are fully allocated the one who did the final touch, there is no incentive left for initial research efforts.
This interesting article represented me 2 challenges about open innovation of commercialization of Hyperloop. First, commercialization of an innovative project might require significant experience in this area. This made me think that whether VHO would be able to get any great ideas. With this hackathon, VHO might not source the right crowd. Second, commercial plans are generally long term plans that should be executed step by step. However, in the case that VHO get the commercialization idea through crowd sourcing, business plans might not be implementable by working executives. Thus, in the short team, I would narrow down the crowd that VHO want to source (we can make it limited to Tesla, SpaceX and Virgin Group maybe). Then, I would also require teams to have some executive experience so that if their business plan is selected for implementation, these employees can quit their current jobs and would join as an executive team to VHO.
I have two different perspectives this interesting article. First, 3D printing might be great for innovation, as it fastens the process of prototyping. However, for mass production, I do not think it should be widely used. Copying has been a big problem for apparel industry as mentioned by Adidas CEO . With improving reverse engineering capabilities and 3D production capabilities, Adidas can be perfectly copied by low cost producers in the markets and with new capabilities, these low cost producers would be able to hit even the quality level of Adidas. Second, even if Adidas wants to invest in 3D printing, cyber security should be their number one priority. Would you imagine that designs of Adidas shoes are stolen and go public? For an sports apparel company, I am not sure whether it makes sense to invest significant amount of money to cyber security.
To your questions, construction can become a consumer DIY market. In many developing countries such as Mexico, Brazil and Turkey, construction is done by families. For example, in Turkey, by 2011, there were around 4 million DIY houses out of 20 million total . Contour should not worry about employment in construction industry at this point. First, set up effort required for the equipment that would be used for a home would create new jobs. Second, construction is one of the most hazardous industry for workers. As reported by occupational safety and health administration, 991 out of 4693 workers killed on job were working in construction industry. That being said, safety benefits of such a development would likely to outweigh unemployment costs. Third, currently job openings outnumbered unemployment . In such an environment, releasing construction workers to do other jobs would even boost the economy.
Based on Huffington Post’s article named “10 Powerful Responses To The Question ‘What is Art'” , art has two distinct pieces: tangible and intangible. Intangible piece reflects personality, imagination and emotions . These characteristics prevent art to get commoditized. To your question about use of machine learning in creating art, as long as algorithms do not develop emotions, only tangible part of art can be drawn from algorithmic composition. Without emotions, personality and imagination, this tangible piece will be a commodity -no different than a barrel of oil- that can be produced by anyone who has access to specific algorithms. Thus, human composers will still be there in future as they need to input their emotions into the tangible piece to create “real art”. My imagination for copyright would be very similar to current world. As long as something can be publicly accessed (such as songs created by algorithms), there will not be any copyright. At the same time, modifications and additions may make this commodity tangible pieces properties of individuals who contributed their personality, imagination and emotions.
I agree that through predictive maintenance, oil companies can generate vast value. However, I would like to bring new perspectives on use of machine learning (ML) at Shell on three dimensions. First, I do not think 100%, as stated by RDS, plant availability is achievable. Platforms have to go through annual or at least bi-annual maintenance and there are some parts that we cannot replace without stopping whole platform. Second, I do not think it is necessarily true that feeding ML algorithm with useful data requires technician training or equipping technicians with ERP linked mobile devices. Even printers at our houses currently can alert us about why it stopped working. I think instead of making the whole algorithm people dependent, I would explore automatic failure reporting systems through sensors. Third, impact of predictive maintenance would be even multiplied if Shell can successfully deploy predictive maintenance to its other assets such as pipelines, refineries and petrochemical plants.