Alex, thanks for the thought-provoking piece. We’ve seen Watson in the context of Jeopardy, an inherently backwards looking application that relies on finding connections between historical data points. Though a more fine-tuned understanding of current and historical weather patterns would certainly be useful, to what extent do you think machine learning will improve the accuracy of our weather forecasting? Also, I wonder if there are diminishing returns to integrating such granular data into a business. The more granular you get, the harder it may be to be flexible and adapt when the data leads you astray.
Lisa – I’ve never seen a twofer business model like this before, so thanks for the interesting read. Much has been made of “the wisdom of the crowds,” and Duolingo is capitalizing on this idea. Even if one language beginner’s translation isn’t quite right, aggregating thousands of them and picking out the overlap should in theory give you a good answer. How does the theory match up to the reality, though? Is there any benchmarking for how Duolingo actually stacks up to professional translation services or other technological solutions like Google Translate in terms of accuracy? I would imagine the app is effective for simple word translation, but may miss idioms and other nuances that require a native or very well-trained speaker. Who is the typical customer for this low-grade translation service?
Michael – thanks for the look at a fascinating business. A few questions came to mind as I read this. First, to what extent does Uptake depend on data not only from its client, but from downstream distributors, customers, etc.? As we’ve seen in class, data sharing is the exception, not the rule, and is typically limited to the bare minimum. Second, you mentioned Uptake has turned profitable due to the massive savings they have identified for their clients. Are they actually paid on a savings commission basis? That would be quite a unique business model, but one I’ve seen work incredibly well in professional services as it increases trialability and customer loyalty. Finally, from a fundamental business model perspective, what exactly is Uptake’s “special sauce?” A lot of businesses are getting into the machine learning game, so I wonder how Uptake will maintain an edge across a disparate set of end-markets. Does the company’s experience advising CAT, for example, improve its ability to advise Aerospace businesses, or are they essentially starting from scratch (and thus have lower barriers to entry) with each new industry?
Shezaad – the disruptive power of entirely self-driving trucks is apparent, but how will the business model work given the software is only designed for highway use? Doesn’t this mean that a paid driver will still need to sit in the front seat to monitor the truck while it’s on autopilot, and to take over when it gets to the off-ramp? Is the bet here that these drivers will not be subject to the same hours regulations as those of fully manual trucks, given their dramatically decreased workload? Otherwise, it seems to me that the only thing Otto achieves is potentially safer and more gas-efficient highway driving, but without really cutting out the real bottleneck – the driver.
On a totally separate note, it sounds to me that Otto’s AI set-up is very similar to what Google is doing as part of their self-driving car initiative. Isn’t it inefficient for multiple companies to come up with their own machine-learning AI systems based on their own data, when just one system leveraging all existing data would arguably be best? Do you think this market could go open-source in due time? Finally, I wonder if by acquiring Otto Uber actually seeks to get into trucking, or if it will just re-purpose the software to enable their own self-driving cars (or both!).
Brad, I’ve spent some time looking at aero-engine manufactures, but have never encountered the RDE – thanks for bringing it to light! One question that occurs to me: the end-consumers for airframes and aeroengines, operators like Delta or United, are interested in energy efficiency only to the extent that energy prices are high. With crude in the $40 per barrel range, a historic low, is there any incentive for P&W to spend tremendous resources developing an even more efficient engine? When gas prices are high, new, more efficient planes and engines are in high demand, but given the current state of the energy market, operators are holding onto their less efficient planes for longer, because they can afford to. I wonder if there’s a cross-over oil price at which greenlighting the RDE would make sense – unfortunately, given how long it will take to develop the engine, it’s impossible to tell!
Alexandra, I agree it’s somewhat shocking that Chipotle would be willing to suspend core menu items (no salsa or guac??) due to pricing fluctuations in their supply chain. One thing that really surprised me about your piece is Chipotle’s apparently limited power with their suppliers. If it’s true that they are using relatively small-scale, concentrated suppliers, I would think that Chipotle, with it’s ~2,000+ locations, would be a critical customer, and they’d have significant negotiating power. Do you know why it is that Chipotle’s suppliers are able to get away with saying no to long-term contracts?
Barbara, thank you for the informative article. Another aspect of banana production that I think is troubling from a sustainability perspective is the proliferation of the Cavendish banana varietal. Although there are hundreds of naturally occurring varieties of bananas, commercial production is dominated specifically by the Cavendish , which comprises something like 99% of the global export market (and 47% of total bananas eaten, which includes cooking bananas like plantains). Monoculture is often problematic, but particularly in this case because the latest strain of the Panama fungus specifically affects Cavendishes. The fungus hasn’t hit Central America yet, but if it does, there will be little the growers can do to stop it from wiping out most of their production.
Steve, thank you for a very interesting look at the potential future of food. Having just lived in New York for the last four years, I noticed a handful of new restaurants popping up that were vegan, but “un-apologetically” so. The food blog “The Infatuation” put it better than I could when discussing one of these restaurants: “rather than serve vegetables that taste like meat, Avant Garden serves vegetables that taste like vegetables.” I’m completely on board with reducing our reliance on inefficient food sources (and wow, I did not realize quite how inefficient beef was), but is the “meat substitute” route really the way to go? Like Andrew said above, if you’re comparing a veggie burger to a meat burger, the meat burger has a natural advantage. Why not create something that isn’t a burger at all, but that is unambiguously more desirable? In a future where we simply don’t have the planetary resources to support cows, why eat something modeled on an anachronism?
Spencer, thank you for the illuminating post on a topic I haven’t heard much about before. ACM’s business model brought to mind the Eco Securities case in Finance a few weeks ago – as you’ll recall, Eco served as an intermediary to develop projects that would produce carbon credits that could be used to offset a company’s carbon footprint, or be sold in the open market. Is there a comparable policy or economic framework when it comes to water rights? I could see tremendous potential value in, for example, a tribe with water rights far in excess of what they need partially monetizing those rights in an efficient, open market to the highest bidder. This would both generate much needed cash flow for the tribes, and incentivize net water consumers to lower their usage, or to invest in projects that offset their water footprint. I think one issue would be that water rights are inherently localized, so it wouldn’t make sense to have a broad global mandate for water usage reduction similar to what the Kyoto protocol did for carbon emissions.