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Thanks for the post, Pasha. I think you touched on an important point that has been at the heart of our discussions all semester: what won’t tech and AI be very effective at? The human, emotional element, here in the form of a trainer, is one of them. I agree with many of the comments above that tech is a great tool to complement a trainer. For example, and humor me for a second, it is not a stretch to someday soon be able to log on to Shad’s app and know how many people are at the gym based on the number of IDs scanned in, which treadmills are currently available based on which ones are spinning, whether the squash court lights are on because the motion detector’s sense people are on the court, etc. These data points are not challenging to incorporate — it won’t be long. Next, for fitness specifically, I think you’ll see a move towards passive sensors for weights training, so you no longer need to enter how many reps at which weight you accomplished. A combination of sensors and your phone/watch should be able to recognize this movement, reducing a friction point for the user. Lastly, as you mentioned, a passive way to track what you eat would be ideal. Once you purchase your food at Spangler, the nutritional content of your meal should be uploaded (wherever you want, if you’re interested) and available to you. What you chose to do with this data is up to you. What this does not capture, however, is the human element of your trainer recognizing you worked extra hard, or you’re struggling a bit, or as you mentioned, you could use extra motivation for the last rep. That emotional, judgement based piece cannot yet be outsourced to AI, and I don’t see that trend changing anytime soon.

Great post Jesse! Two thoughts struck me while reading. First regarding the Fender Play, I wonder if Fender could work with some of the artists who created the original songs to actually instruct the video. I am picturing Eric Clapton in HD walking a beginner through “Layla” for example. There are certainly thousands of covers on Youtube for these classic guitar songs, but Fender has the strength (and to a degree the budget) to contract with the artists to populate the Fender Play platform. We may need to run the numbers and see whether this is feasible!

Second, I wonder when a musician decides to stop playing, whether Fender should also be there to buy back their guitars for pennies on the dollar and refurbish them, and then sell them again. I would be interested to see how big the market is for second hard guitars vs new guitars, and I suspect with the churn rate you’ve described, the second hand market would be quite high. If this is the case, Fender could investigate this business too (I am picturing the DeBeers diamonds case from last year, a bit here), and make a fine, data driven model to get the best buy back price and resale value.

Great post, RPark, thanks! I am a big fan of the Nespresso offerings, and I find the battle for market share between single serve providers very interesting. I wonder whether there is a play for Nespresso in creating a subscription offerings of cups, using data from the Prodigio? I like the bluetooth connected functionality of the Prodigio, and think that Nespresso could gain insight for its users, regarding consumption habits and which household user prefers which type of cup. Nespresso could then begin to offer a weekly/monthly subscription service of cups that would be based on the preferences of the consumer, and delivered right to their door. This would reduce a friction point of having to re-order.

Great post, M, thank you. While reading, I was thinking about whether the first CIO Patti Reilly White faced challenges when she introduced the Check-Level Analysis. There is little doubt that the data that Darden tracks with the Check-Level Analysis can prove useful, but I wonder how the implementation process worked – as we saw in class – when her team first received the data and proposed new ideas based on the findings? Were there operational changes to improve efficiencies or perhaps push-back from servers or chefs regarding food prep time? And perhaps the optimal menu based on the data was at odds to the chef’s knowledge of what may sell at a given location? Very interesting!

Great post, Mike M, and what a fascinating company. I am very intrigued with how Palantir sources and prices its projects and contracts – there is no doubt that the services they deliver for both the government and private consumers is incredibly valuable. Palantir also seems like a company who’s commitment to software and data driven culture would be unmatched. With their value proposition and private status, this seems like an incredibly exciting place to work – probably a lot of energy surrounding solving this complex and important problems. With that said, I wonder what an advantage would be for Palantir to go public? It seems like the secrecy of their work and private funding status go hand in hand. If I were Palantir, I think I would want to stay private, not get involved with quarterly numbers and investor relations, and continue to produce exceptional work. No questions asked.

Great post, Jessica, thank you. This is so interesting, as the traditional VC model seems a bit under attack. As you mentioned, if this model can remove many of the biases inherent within investors, that could be a huge value-add for the VC team in assessing an investment decision objectively. I like the idea that a mission for machine learning, data analytics, and AI is to process enormous amounts of data, and freeing up the humans to use judgement and analysis — as we’ve discussed in class, and an area that AI still struggles with — to ultimately make the investing decision. Therefore, this could be a tool both for Correlation Ventures and, as you mentioned, a tool they can license — that’s an interesting thought too.

I wonder too how the entrepreneurs feel about receiving money from Correlation’s AI. If I were an entrepreneur, I would hope my investor is passionate about serving on my board and helping our company succeed – not investing because the algorithm thought so. I doubt Correlation lacks passion for the investments, in fact, I would imagine they would be more excited once the data supports their intuition. But as an entrepreneur, I want to be lock step with my VCs, utilizing their understanding of an industry and harnessing their guidance, to grow the company and achieve profitability quickly. I wonder how Correlation provides those sorts of services to its many investments.

As always, great post Mike M! I think this will be a powerful tool for Facebook and its community. I agree with your thought too, that Facebook is uniquely positioned to deliver value by the nature of its user base. The power of a connected community is best demonstrated by JJ Watt’s efforts this fall, raising $37 million for Houston residents following Hurricane Harvey, through a social media campaign and engaging with a nationwide community.

I am less concerned with users struggling to figure out how to use the tool when the time comes though. Fortunately and hopefully, this tool will not have to be employed often, but when it does, the FB community will be willing and able to figure it out. This connected feature, like JJ demonstrated, will be a undisputed beneficial use of new tech and the crowd.

Interesting post, thanks! I am amazed at the $1 billion post-money valuation — clearly investors are long Glassdoor’s community and value proposition. I find that motivating employees for submissions is an interesting challenge for these review sites. Without sounding too anecdotal, it seems often that people are motivated to contribute to review platforms following exceptional experiences (work environments in this case) or pretty terrible experiences. Often for would-be hires, the most useful and best representation of a company probably lies somewhere in the middle of the stellar and abysmal reviews, so how will Glassdoor incentivize and capture that voice? Thanks.

Very interesting post, Kat, thanks! In previous examples of crowdsourcing that we’ve seen, such as website design, marketing campaigns, algorithms, etc, the crowd represents an untapped set of experts who can help the client in new, creative ways. I am interested in how the crowd that Lay’s has tapped into knows what flavor chip they will want Lay’s to produce? I am skeptical — though clearly impressed — about how a crowd of voters at home can predict whether a Cappuccino or Wasabi Ginger potato chip will actually be appetizing. These flavors are certainly interesting (exotic?), and I understand why they would receive votes – from other non-expert Facebook browsing Lay’s enthusiasts — but should that be enough for Lay’s to give the green light on production? Again, the sales tell all, and clearly the effort has worked over the last few years, but I’d love to hear about how management eventually got on board with this idea. Thanks!

Great post, Mike M. Drizly has certainly identified a consumer pain point and its platform is well positioned to solve a lot of their issues. I wonder about how Drizy will interact with state and county regulations going forward. I am sure they have a fine legal department and regulation is top of mind as they seek to grow, but perhaps like Uber, Drizly may find itself brushing up with the law throughout it’s growth period — and perhaps lobbying for certain distribution laws to change. Excited to watch the evolution.

Great post, Juan, thanks. This Spotify IPO is certainly interesting for many of the reasons you pointed out. I found this interesting: http://www.ifpi.org/downloads/GMR2017.pdf a music industry report. Music producers are still not happy with how the industry has evolved and are looking to work with Spotify and other streaming platforms to re-claim more value for itself. The evolution of Spotify’s business model and the future of this industry is very exciting.