Interesting article! I don’t think Amazon Studios should keep the programs for a marketing purpose. Sometimes, if the project or the company does not respond to the idea, ‘Open Innovation’ can be a burden that creates a negative brand image. I don’t know well about how Amazon Studios pick the idea and how many contents they make per year, but if they were more open for trials and errors on trying new and diverse idea, they might keep the channel open and gather more fresh idea to use as the source of gathering another data on consumer’s preference on contents. But without sophisticated algorithm or system to sort the idea to use them as what I mentioned, open innovation platform will have no effect to Amazon. So I support Amazon’s decision in current stage.
I partly agree on your opinion that open innovation can just end as a marketing tool for the city or the companies involved in the project. The beauty of ‘Open Innovation’ or ‘Crowd sourcing’ should be linked with real changes, even with really small changes. What people really want to hear from the project is not only the solutions or the results based on their ideas, but the feedback from experts on them. Quick wins should also follow with the feedback, but Toronto should first build a bond with citizens and people involved in the project as a ‘one’ team.
There were a few projects similar to Toronto’s, but most of them ended with leaving the city as a ‘ghost city.’ (i.e. Songdo city in Korea) The amount of money spent for the project, the number of experts from the government or the level of technologies used for the project… These things cannot guarantee the success of smart project – Bottom-up/Localized initiatives are needed.
Thanks for an interesting article! Different from most of papers or articles are about how to use machine learning as an engineer or the leader of the company, it is really interesting to think about the issue as a sales manager of food delivery services that has valued the insight and knowledge of people on what food/restaurant consumers might love. I don’t think machine learning algorithms would make sales employees demotivated about their roles. Of course, some of AI technologies would replace sales employees, but still, ‘Food’ is strongly linked with each person’s preference. Sales team can use their time on analyzing and finding the opportunities for hidden charms in local area and delivering the best message to its customers. It is up to the company’s decision on how to use just the ‘right’ level of machine learning technology on the context of the business.
As previous comments already pointed out, I think that AECOM needs to take time to test the technology and decide on using 3DP on its products, but overall, I strongly support your idea that 3DP technology would solve many issues that E&C industry has had in decade. The leading player in the industry such as AECOM has to lead the transition of the industry to next phase using 3D Printing technologies.
Autodesk, the leader in construction software field, has also invested in 3DP technology for years and explained on this article (https://connect.bim360.autodesk.com/3d-printing-in-construction) that the technology is truly evolving in these days! Now the use cases will grow, and we would be able to see what this innovation would bring us in next few years. Actually current 3D printing business itself is not profitable. So I think AECOM should keep an eye on the trend happening around them and support the trend, with a long-term view on the technology.
CircleUp’s usage of AI technology on VC investment itself is really interesting, but the most impressive part for me is about how the company collects data about consumer’s reactions and analyze those data into figuring out the success of consumer products. There are a lot of research and articles about using AI technology on investment, but I’ve never thought about focusing on CPG market. I think CircleUp became successful because of its approach to use AI on very narrow and specific topics in the market. To remain competitive, CircleUp should keep focus on building detailed criteria for gathering data about their target companies and consumers and investing on similar sectors to what it has invested so far.
No doubt, 3D printing is the technology that can change the total structure of manufacturing business. However, I’m still skeptical about using 3D printing technologies to Aerospace. Usually 3D printing is mostly effective when the prototyping process is fast and there are a lot of needs on customization, but Airplane is relatively slow industry to develop a new product and also most of products are quite standardized. Moreover, the size of parts is very big and the safety of products (airplanes) is important. Therefore, I think Boeing should take more time to test the technology within its organization, rather than utilizing companies it cannot fully control.
Thank you for interesting opinion on machine learning, especially on gaming industry. To your first question, I think still historical/past data is one of the most important sources for prediction on future. More serious issue is, as you mentioned, lack of valuable primary data to be used as the source of prediction. In most cases, machine learning technology needs something exceptional or failed cases on a certain situation, but most of data are focused on normal cases. Tencent should invest on gathering data with more diverse process and results.