Great work, Yaping — really enjoyed reading your post! In response to your closing question, I think Nestle should lean toward being more proactive, since they can then communicate the key problems they are trying to solve (especially when it has to do with global health/welfare). I wonder whether everything that Nestle incubates has to have the potential to become a for-profit product, or whether they should even try to incubate technologies which are more on the humanitarian/non-profit side.
Great work Ennis — I really enjoyed reading your post on GA! A phrase that I found particularly inspiring is “crowds, research shows, are energized by intrinsic motivations—such as the desire to learn.” I wonder whether there are applications beyond educational platforms where this could be leveraged — either in brainstorming solutions to community health/safety problems, or helping to train machine learning algorithms (e.g., those use in healthcare).
Great work, Jackson — really enjoyed reading your post (especially as a Duolingo user)! It was interesting to learn that most of Duolingo’s machine learning is geared toward optimizing their lessons across all users, rather than tailoring content to individual learning styles — this definitely seems like an improvement opportunity going forward. That should also help with the sentiment that I (and apparently many others) have of the content being a bit disconnected from normal language use.
Great work, Alex — really enjoyed reading your post on Nike! As Nike transitions from creating custom footwear for celebrity athletes to creating similar products for the recreational consumer, it will be interesting to see how they can speed up the fitting/customization process to make it truly scalable.
Great work, Allison — really enjoyed reading your post on UA. It seems like right now, any material-saving benefits of additive manufacturing are unfortunately more than offset by reduced production speed. However, as you mentioned, the ability to personalize products with additive manufacturing is a currently untapped opportunity for UA. Along the lines of automation, it’ll be interesting to see whether UA has fitting appointments for these personalized shoes, or whether they are able to use a more automated option (perhaps a photo/scan/mold of the foot).
Great work, Keith — really enjoyed reading this article, and is definitely one of the most tangibly positive impacts we are seeing from machine learning! In response to your question about leveraging technology to make energy more efficiently, I hate to say it, but I think the blockchain could be helpful here. Specifically, in terms of making local communities of generation and storage, a blockchain accounting structure would allow peer-to-peer transactions of energy to be stored in a trustworthy and easily-audited ledger.