Awesome post! Great analysis of how the vast numbers of SKUs may provide a unique benefit of implementing AM. One concern i have is that my experience with 3d printers is that the resolution of the finished good is not good enough to ship directly to consumer. I would expect Nike would need to add finishing processes to refine parts made with AM before they were acceptable to ship out. An alternative might be using 3d printers to create the molds for the many different SKUs. This might also save time as the 3d printer could create a mold that is close to the required near-net shape, and then traditional machining could finish the mold, instead of having to make the mold from a standard billet and machine away the entire cavity.
As an avid Mercedes-AMG fan (another great year), for Ferrari’s sake I’m afraid this may be too little too late. Engine and car development in F1 can be very difficult as there are heavy restrictions on testing, so even if Ferrari can design new systems built upon the benefits provided by AM, I’m not sure they will be able to test them adequately to make a difference in the next couple of seasons. Adding to my concerns is that there may be material property differences between parts made with AM and with traditional machining methods, ie the grain structure of metal processed in the two methods are radically different and likely behave differently under the extreme stresses of an F1 race. Do you think Ferrari will be able to close the gap to Mercedes now that they are investing in AM?
Nice insights! I agree Valve really needs open source content creation at this point in its life, but I fear they are setting themselves up for failure unless they partner with an existing widespread console manufacturer. I’m worried that Microsoft or Sony may simply be letting HTC spearhead the move towards VR platforms, and will jump into the market once critical mass of content and consumers is generated. At that point, I don’t know that HTC can compete with the momentum that already exists on the mainstream platforms – what do you think?
Interesting post! I had no idea such a company was putting on productions like this! It does seem like it’d be a good candidate to benefit from crowdsourcing of ideas. Operationally, do you think crowdsourcing might cause problems for the development of new shows? I fear a little bit that an abundance of ideas might be difficult to filter and clearly identify the best themes from. One idea might be to use machine learning or some data analytics in combination with crowdsourcing of ideas to more quickly filter and tag the most popular or common suggestions.
Nice post! Very interesting to read about the depths on which Netflix is built today on top of machine learning and data analytics. One fear, or perhaps only question, I have is how Netflix views creativity in light of machine-driven content creation. I am a little concerned that machine learnings may capture consistent themes and over time drive creation of content that will no longer be viewed as fresh, but as a repackaging of thematic elements known to work. We’ve seen some of this in Hollywood in particular, with large studios relying more on sequels and remakes than ever before. Do you think Netflix analytics can benefit creativity or does it limit it?
Interesting blog topic! You do a nice job of highlighting where a data-driven platform may provide benefits over human doctors. Reading through, I really like the point you made on how data should really be used at this point in time to augment current practitioners. One worry I have in moving to machine diagnostics is that people care about human interaction, and may be turned off by the lack of human contact if we shift fully to a data driven tool. Rather, I see the benefit here as creating a mechanism against which human doctors can compare their assessments, and both correct incorrect assessments, and over time learn from mistakes that were prevented. A second question I had was whether you think even though the Babylon platform outscored humans, is the perceived barrier for a robot higher than for a human? We expect humans to make mistakes, and I suspect that humans may hesitate to implement robotic platforms until they demonstrate an even larger benefit over human performance.