The idea of using machine learning in agriculture is really interesting and solves a very critical social challenge in the world today. While I agree that the use of machine learning will fundamentally shift the way we farm; however, to answer your question as to its potential impact, I wonder if there’s a ceiling to the gains to be made. What I mean is that once ideal growing conditions for a particular crop have been found, will there come a point wherein conditions can no longer be optimized? If the world continues to suffer from a hunger crisis, Plenty may have to look at other ways to increase yield beyond growing conditions. Another potential use of this data is to use it as additional input into agricultural genetic modification. Understanding ideal growing conditions can help determine what genes may need to be modified for a crop to grow exponentially. I do not believe that Plenty will solve this problem, but it could expand its revenue stream by selling its data to companies that are tackling these issues on a daily basis. While the ethics of this continue to be debated, in a scenario of world food shortage, this may be an interesting option to explore.
The point that you raise on displacing jobs in the utility industry is an interesting one, and can be generalized to other industries where machine learning is replacing human intervention. This problem is exacerbated by the fact that machine learning will then lead to further automation of grid management, wherein industrial components can conduct maintenance more efficiently. I believe that retraining should be the logical first option: as the business model of the utility changes so should its workforce. In addition to grid software management, workers could also be retrained to work with customers on numerous aspects, including sales and data analytics. As machine learning opens the door toward more decentralized electricity generation, workers will be shifted from working on power plants and grid infrastructure toward the construction of local generation plants.
As you mentioned, the need to secure the internet networks of this essential infrastructure should be the utility’s highest priority. In addition to investing in sophisticated cyber security infrastructure, the utility should also create robust contingent plans in case of an attack. The algorithms need to be built with a road map of how to react in the event of a hack. This may involve rerouting energy supplies, creating back-up components that do not sit on the main network, or decentralizing its technology hubs to mitigate proximity risk.
Thanks for writing about this! I agree with the comment above in that this technology has the ability to affect millions of lives by providing affordable housing. In my specific context in the Philippines, I see this as a game changer for plenty of my countrymen. In fact, when I had visited the World’s Fair Nano in New York, a trade fair on the future state of the world, a 3D construction company specifically pointed out that this technology can help address the homeless in the developing world.
That said, to address your first question, I believe that one way to educate the construction ecosystem is to make headlines through social impact. The reason I say this is twofold. The first is that it gives the company a proof-of-concept in terms of both scale and cost efficiency. By partnering up with a non-profit to provide homes for the poor, it showcases the speed at which it can build homes and the fact that it can be done cheaply. Secondly, it generates buzz for the company and puts it at the forefront of the conversation in how technology can provide a social good.
In terms of your second question, I would stick to staying within the construction industry, but would take a slightly different position than what has already been done. Instead of focusing on building big houses or buildings in its entirety, I would look to creating modules for parts of a building (those that typically take the longest) and sell those parts to a company. This would address the trust issue that you described, and allow the company to get ‘small wins’ in proving the technology to the customer. By manufacturing parts of the value chain, it allows Winsun to get a foothold in the industry without having to wait for the all-in buy in from its customers.
The idea of using a VC to inorganically grow its innovation capabilities is an interesting one, particularly when you’re looking at companies that are as large as Unilever. It seems that even if this is not within their core capability, they will be able to execute on this initiative simply due to their size. The opportunity that they may be missing out on is actually receiving organic innovation suggestions/recommendations. There was a comment above regarding Unilever’s proximity to its customers, and I believe that this is an important dynamic in their business. I see disruption in the space not so much in terms of technical capability, but flexibility and adaptability in reacting to what the customer needs. Unilever can address this by creating open innovation that listens more closely to its customers. Taking this further, I believe that a local approach here is appropriate. As a multinational operating in more than 190 countries, capturing the local perspective in each of its product lines is critical to success. That said, I recommend that the company move toward a more organic and local approach to its open innovation efforts.
An interesting idea on open source innovation! Some of the comments already described the idea of opening up this open innovation platform to more products other than the existing kits. Why not take this notion further and extend the platform to new business models, beyond just the building of toys? As consumers move more and more toward digital entertainment, it might be worthwhile for Lego to explore new ways to monetize its IP beyond its core business. The risk here is that you are likely to receive more ideas that are not viable; however, as is usually the case with innovation, casting a wide net in the hopes of striking gold is never a bad idea.
An interesting topic on the future of the automotive industry. My feeling is that, while this technology is not currently able to scale, there will come a time when all manufacturers will have to incorporate 3D printing in some capacity. The interesting piece here is on the customization of vehicle parts. While I believe there will be some demand for these products, the premium may be high for a long period of time (potentially longer than the 2030 time period you mentioned) due to labor costs and the time associated with single customization. However, I believe that the company can derive significant value from customized auto manufacturing as it relates to autonomous vehicles. Since customer behavior will change in these vehicles (i.e. they will no longer be driving), each one may have different preferences as to what to do during that time. The consumer may decide to watch content, read and relax, have space to eat, etc. This means that demand for a highly customized vehicle, which caters to the customer’s specific need, will therefore increase. Using both 3D printing and driver-less cars will thus look to fundamentally shift the way we know and experience our automotive vehicles.