Thanks for the post, Kaitlyn! One question I had as I was reading through was how AirDNA can collect more information about small local markets given that the frequency of bookings is lower but this data is critical for forecasting local demand. One potential option that I thought they could consider was whether or not there was a way to aggregate data from multiple small local markets without compromising the integrity and accuracy of the data and negatively impacting the conclusions being drawn from the available data set.
Really enjoyed reading your post! I used to refer to GitHub when I had to code for engineering classes and I find it fascinating that there is a potential to auto-complete code using natural language prompts. The flywheel that Copilot would generate for GitHub would be fantastic and it would also offer users what many of them are looking for – a quick, easy solution to their coding challenges. I am interested to see where these capabilities land in the next couple years!
Really enjoyed reading your post! I had not heard about Spotify facing controversy from playlists with songs associated with fake artists. I wonder how royalties will be paid out in the future if AI is used to make music and generate playlists. Maybe it will be a first to market allocation where the musician who produces a song with the beat / melody first gets the majority of the payments. I’ll be interested to see!
Thanks Anand! Really interesting how different the Dall-E product is compared to the Craiyon product. I also think it is extremely valuable to point out the biases that are built into these AI programs. Your blog post makes me wonder how we can improve the algorithms to eliminate these biases.
Thanks Kate! I think you’re completely right when you point out that training an algorithm for interpretations instead of just facts is where there tends to be difficulty. I also really liked the feature picture you chose because it shows the nuances of the AI program.
Interesting topic! I think you were spot on recognizing that the food looks familiar at first glance but then when we take a closer look we realize that many of the items in the photos are actually very non-descript. It is so interesting that the AI got the colors and general “feel” of the southeast asian-inspired dishes right even if the actual details of the sides are not very clear.
Thanks Yannik! Though I don’t personally use Strava, I have a lot of friends who do and I have been shocked by how engaged the user base is. For this community, the freemium model is ideal. It makes the app completely accessible but given the level of commitment that many users demonstrate, there is a high potential revenue upside due to users purchasing access to additional tools. Given the recent push for people to have more active lifestyles, I think that this platform will continue to gain traction.
Thanks Kate! I’m interested to see how this app sustains its growth and continues to increase its user base. Given that the slogan is “designed to be deleted,” I am skeptical about the prospects of significant user growth in the future. I think that there is definitely customer demand for the platform but I worry about the customer retention piece given the fact that the purpose of the app is for people to find a match and then delete it. My only thought, as you pointed out at the end of your post, is that there is always going to be a demand for dating so while there may be churn, there will continue to be new people who are looking for a platform that helps them find a match.
Really enjoyed your post! As someone who is a captive TikTok user, I find it interesting to learn how the algorithm and machine learning behind the platform work. I think TikTok’s true success is due to its ability to cater to both directions of the two-way platform. It not only provides the music library and interface for content creators, but it also caters content to viewers to increase the level of engagement and viewing. I have to wonder whether TikTok is a social media fad or if it is a sustaining interface.
I really enjoyed reading your post!
I have been a loyal Spotify user for almost 10 years. I originally used Pandora for music streaming but I ended up shifting to Spotify because I felt that it did a better job curating my music recommendations. I didn’t realize that the algorithm was built off of a combination of three different ML features but after reading your post I now understand why the recommendations felt more curated to my own personal music interests. I had also never heard of collaborative filtering. This form of ML benefits from a larger user base because the ML capabilities improve with a larger data set (i.e. more Spotify users). For this reason, I think that Spotify’s algorithm will continue to improve as the company grows and attracts more customers.
Garmin is a great company to choose for this blog post! I considered getting a Garmin watch to help track my training runs because it is known for having great tracking / GPS and ability to offer customized training plans based on prior performance. I think that this company will likely expand into other athletic spaces (e.g. swimming) over the next couple year and that the popularity of the brand will grow as the analytical capabilities continue to improve.
I really enjoyed learning about Samsara. I had never hear of the vehicle gateway or what it does in a car and I find it fascinating that this piece of equipment can measure and collect data, and then transmit it to the cloud through the SIM card and cameras. In my opinion, the fact that Samsara is able to leverage this data to create a baseline for safe driving and offer coaching to prevent driving related accidents is extremely impressive and valuable.
I really enjoyed learning about RedRaven through your post. Before reading through what you wrote I had a very limited knowledge of what an industrial internet of things was but your post inspired me to do a bit more research on this concept. I think that the benefit derived from RedRaven’s ability to identify mechanical, hydraulic, and wear issues with their pumps and valves before scheduled maintenance sessions / equipment runs to failure is extremely valuable because it not only decreases the cost of the repair but it also prevents significant downtime in the manufacturing process.
Really enjoyed reading your blog post! VPP is located near my hometown so it was fun to read about the advancements that the company has made over the past couple years. I sent a message to my friend who is a vet and her clinic actually part of the VPP platform. As you pointed out in your post, one of the biggest challenges that the clinic is facing is how to transition to using the new systems, as many of the vet technicians are used to paper data records. I foresee that once clinics are fully on board with this platform, there will be massive value in the time saved on the tasks that you outlined (especially scheduling and reporting).
Really enjoyed reading your post! I didn’t know anything about Falabella and felt like I got a sense of the business through what you shared. I thought that the way you structured your sections was engaging and I especially liked your point about the decision to change the logo. Though management was striving to show the new integrated e-commerce platform, it also lost touch with the value that was created by customers’ emotional link to the brand. In this way, I think we see that data is valuable but isn’t the solution to everything