Patric Cao's Profile

Interesting! Most of the examples others wrote in the blog have been where the AI is used for the company and not as a service to a variety of clients. It makes me wonder how intellectual property is contracted out. I know that consulting firms like to be coy about their engagements and even make an effort to prevent conflicts of interests across their staff. But when the machine learning model learns from each engagement and improves, who’s the say that the next powerplant 2 years from now that contracts with McKinsey won’t benefit from the learnings.

Really cool idea. It makes me wonder if they could also launch a styling service for customers as well – “we design the perfect look for you – using ML”. Because right now Finesse is in the business of “predicting trends”, but if they could also influence the trends, they could increase their “prediction” – almost in a self-fulfilling prophecy and being the industry maker.

Loved this idea. I wonder if ELSA can also learn on its students as well. Potentially storing “correct” and “incorrect” answers to better design curriculum for students based on their profiles. This obviously lends itself to data security and privacy concerns as very personal recordings could be collected.

Really the stuff of nightmares! I totally hate that all this AI generated were images of old men (at least there’s some melanin though!). Glasses also seem to be the norm, but there definitely should be some flags for AI creators from just the small learnings in this exercise about racial and gender bias in AI results.

That is so strange! Even before reading your post, I noticed all the “kind nurses” that were generated were all female and light skinned. Also their hair styles are the same (bundled in a pony tail in the back) and with a brunette color. Arm positioning also seems to be the same. All of this makes you question what exactly is the informing data set and how can make sure there is sufficient diversity such that the results aren’t biased.

So interesting! The AI really hasn’t gotten down generating exact details yet, but it strangely reached a point where our brains can fully recognize exactly what it’s trying. The sweaters definitely are Harvard and that’s definitely Joe Biden. Scary stuff!

This blog post reminds me of a conversation that I had with a guy who ran a shipping/trucking company in the Chattanooga (during my HBS FIELD trip). Apparently Chattanooga is a central hub in the US for trucking logistics. His opinion on the growth of these trucking and shipping digital platforms is a lot of skepticism. A great deal of these deals made by shippers and trucking companies are based a lot of relationships and remain static after they are set. So these digital platforms often don’t really take off because the % of the trucking market that’s willing to change from relationship-based connection versus virtual/digital connection is lower than most entrepreneurs expect.

Thanks for the post! Actually, before reading this post, I always wondered why GoodReads had a horrible-looking webpage and UX. But after you mentioned they’re a monopoly, things totally make sense. I think the unfortunate thing is that even though they are the only provider of this service (even a service I would WANT to use), because the UX is bad, I just never bother and instead go on the subreddits where people read the same genres that I read. I wish they’d understand that even though they have the largest market share on this service, they are still missing out so many other potential users because of the lack of UI/UX investment.

Really interesting post! I hadn’t heard about TBL, but this sounds like the place to look at when I travel. It makes me wonder though how difficult it is to retain and growth with these customers given customers will only travel a few times a year and their first entry point into a trip is with the flight provider/hotel providers. Things like tours come after the fact and in the value chain, so TBL might be in a more susceptible position in the competitive market.

Very interesting blog – I really enjoyed reading how Marriott has evolved through its technology journey since the 70’s to now. I’m a Marriott loyalist but I haven’t appreciated the data analytics behind my Bonvoy membership with the hotel chain. I wonder what their next set of priorities are in the next phase of tech evolution. I am concerned about the volume of hacks occurring at Marriott and how this affect customer loyalty. The way this article reads, it appears as though Marriott has been investing to achieve short-term gains in its data analytics efforts but hasn’t been investing in the security of that – exposing customers to the negatives while the firm reaps the benefits of customer data mining.

Really interesting concept. I don’t think about these problems when I shop in the store. I definitely see the problem it solves for customers and corporate partners, but I’m really curious to see how this firm grows (has grown) and monetizes. To me, the user must always have free access to the app because they are the “product” – much like how Facebook monetizes its platform.

Perhaps the greatest monetization and revenue opportunities lie in these data analytics and consultative services that Ibotta can offer big box retailers, buyers, and CPG brands. An unanticipated challenge for their business development and GTM strategy team might be that the retailers and brands may grow upset about how the data is used (e.g. a brand may not want the retailer to see the data on their shelf placement or otherwise but it may affect the way those two negotiate retail agreements).

Really interesting! Makes me wonder if there is a world where Penguin Random House or any other book retailers can ever compete with Amazon in the book market. Maybe there’s a possible roll-up investment thesis to merge otherwise underperforming book retailers to get brand and data synergies to rival Amazon.