Thanks! I think education is the front where LEGO could potentially succeed in terms of open innovation and commercial success. While LEGO seems to expand into various kids-related categories, I feel have tremendous potential to leverage on new technologies and their adoption by youth. Firstly, while 3D printing is a hot topic among adults, LEGO could easily mimic the learning potential through its existing products. By structuring the construction experience around designing and “printing” new structures with bricks, they can convey complex concepts at entry level. Secondly, LEGO has incredible resources and storytelling capabilities to move older kids into a VR-like experience where they could build larger structures and learn how things work in real life. Based on what kids end up building and learning most efficiently, LEGO can repackage this information into new products and services that tie customers closer to the brand.
Thank you for your contribution. Pinterest seems like a leading innovator in visual deep learning. It has cash, resources, and a high-potential business model to push new innovations. I would go a step further – what if Pinterest could morph relevant pins into new content? Just like a designer pulling together several client ideas? Intellectual Property rights would not be breached since the algorithm is simply getting inspiration to create a work of “art”. The customer on the other hand could have a more meaningful and value additive interaction with the service and stay locked in for a longer time. Moreover, what if you could morph some Amazon products into the picture, e.g. room design with Amazon basics bed frame? We are still debating the visual recognition potential of algorithms, but how about we make a leap towards visual creation?
Thank you for the article. It was really insightful to provide an overview of the Uber-driver partner relationship. I think the growing complexity and capability of ML algorithms poses as a huge temptation to overexploit the less powerful – the driver. Gaining perfect information on an individual driver’s patters (and therefore ex-ante motivations) is very valuable for Uber and puts the driver at a loss. Proving a dynamically evolving incentive algorithm targeted individually at each driver can easily squeeze all possible efforts out of every driver at the lowest cost possible – just like you pointed in your example. I think the only ethically acceptable solution here is to hold every driver to the same incentive scheme, so that the hard workers earn their fair share. Moreover, since I am learning about these mechanisms from an Uber expert and not my own Uber app (which I use frequently), makes me worry about the transparency of ML applications at the firm. I feel every time news like this break out, I seem to trust Uber less and less. Due to their size and impact on urban ecosystems, they should be held to highest standards of public service and do more than currently with respect to how their new technologies are affecting both sides of the market they co-create.
Interesting article! I agree with Mr Daniel Knight from the comment above. While the technology is emerging and adidas is already managing to produce, market and sell limited batches, I would look into the long-run evolution of the footwear industry. I have confidence that skilled engineers will in the end create a time/cost efficient solution to print shoes or soles with additive manufacturing technology. However, I would reframe the question – it’s not “how can we print (fast)?”, but rather “what should we print (that will add value)?” I think adidas has to fundamentally rethink purchasing experience for customised shoes. It’s not just about adding colourful stitches or my dog’s portrait on the sole, but ultimately it’s about this perfect fit for my foot shape, gait, weight, etc. To be able to print the perfect shoe, you need more than just a top printer. You need to measure the customer’s unique profile, process it and come up with a perfect solution. Only then print. I see a huge potential on the market – once you measure the customer, you have a high chance to retain her for long. But you need the right store format, qualified staff, flawless measuring experience, and talented engineers and designers to create perfect CAD algorithm for printing.
Thank you for the article. It sounds like we are observing dawn of mass 3D printing applications to real life! That being said I think we cannot really *yet* determine whether 3D printing is just another marketing gimmick that serves to just stand out from the crowd, or is it really a new long-term approach towards manufacturing? More specifically, I would like to learn about the empirical user experience of how it actually feels to use a shaving handle that was designed by a user with presumably no prior experience. While I acknowledge it may sound quirky and fun, I would be sceptical of the practicality of such invention – e.g. maybe it turns out you need a specific curve and weight balance to be able to shave quickly and safely? Giving full decision power to an end-user sounds exciting when it comes to the looks of a product, but I would hypothesise a customer would benefit from human expert guidance? I think additive manufacturing is a low-hanging fruit for large companies to demonstrate innovation mindset, but it is a massive challenge to design an offering and experience that would truly augment usability for the end customer outside of the marketing sphere.