Jared V.'s Profile
Jared V.
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Super interesting! Personally I have been following the COVID cookery subreddit (https://www.reddit.com/r/covidcookery/) and it’s inspiring to see the foods that people have been able to create with their newly found free time. It will be interesting to see if this trend continues post-pandemic, and if so, whether there are market opportunities for companies that can make the production of these baked goods easier and cheaper.
Great article! That is an interesting point that the investment in a physical device like a VR headset could lead to a more sustainable increase in user base in a post-pandemic world. In terms of non-VR games it does seem likely that the surge is a temporary spike while people have more time on their hands and less access to other social activities (I know that has been the case for me anyway), but since games can be sticky it will be interesting to see if there are any particular games that maintain popularity and traction after social distancing restrictions are lifted.
Super interesting example of how a company is using data analytics to generate valuable insights, especially in an extremely noisy and fluid environment like a football game. One concern though is just to ensure that players and organizations aren’t overwhelmed by these new measurements, which could be a distraction, or over-indexing on statistics that aren’t actually relevant or significant in predicting success (i.e. winning games).
Very interesting! This is one of the few cases I’ve seen where AI is being applied to taste, and it will be cool to see if/when it gets to the point where it can provide taste-accurate recipes without chef intervention. I wonder though if there is a limit to how accurate these recipes can get, since I imagine some of the data being fed would be limited by a person’s descriptive capabilities and subjective taste.
Interesting article! I am also a bit concerned about re-identification of individuals, since I would think that if you know just a few pieces of information about a person (home address, where they work, etc.) then it would be pretty easy to pick that person out of the data set. Still, it’s great that Replica is working with cities to get them critical behavioral data for their planning efforts, run simulations and facilitate impact measurement for completed projects.
Great article and comment above. Since it is so difficult to create a defensive moat solely within this space, I’m wondering if it is relatively easier for competitors to expand from existing networks. Uber Eats, for example, may be a case of network bridging, leveraging its existing competencies in customer data, relationships with drivers and mobile app design. It will be interesting to see where this market goes from here and if winners from other networks (e.g. Amazon, Google) also make the leap.
Interesting article! I wonder about competition with Microsoft Teams – which offers some of the same functionality and features as Slack (though with more limited tech integrations). Especially in enterprise sales where the service is bundled with Office365 and many of Microsoft’s products are core to company operations (Excel, Outlook, etc.). My impression is that the simplicity of onboarding with Slack and more app availability may benefit smaller and more tech-focused companies, but IT departments at more traditional firms may be more inclined to stick with a stack that they’re already familiar with.
Thanks for sharing. With regard to clustering, as younger people are now less likely to own cars than in the past, I’m wondering if there now may be more local network effects similar to Uber – where people might rent cars in their area for weekend trips or tasks would be inconvenient to do through ride-sharing or public transportation (e.g. going furniture shopping). This may lead to an opening for competitors to thrive in this particular customer segment if they can build a stronger presence in a given city.
Very interesting article. Having worked in the construction management space I can confirm that it is extremely slow to adopt new technologies and there are still huge areas for improvement. Being able to show the benefits of the Procore platform and enabling a simple on-boarding process are critical to widespread adoption, although the complexity and long timeline of construction projects could make establishing this direct attribution a challenge. This can lead to sort of a chicken-and-egg problem, where construction management companies may not be willing to diverge from traditional “tried-and-true” processes (especially larger ones with more complex budgeting criteria), potentially risking their relationships with clients/contractors and eating into already low profit margins. The upside for Procore is that if it can simplify processes for these customers, reduce costs and improve employee & client satisfaction, it can build a solid recurring customer base while expanding the overall market.
Great article and some excellent insights in the comments. I think Mirror offers a unique value proposition from a hardware + software perspective. I’m not as sure about the home workout market being ready for this kind of technology just yet, considering that companies like Peleton are dumping tons of money into advertising and customer education. I think the use case for Mirror is also less intuitive than a stationary bike, which have had a much longer history in at-home workout environments and have been paired with rudimentary technology for a while now (even as simple as mounted TV’s at the gym). However, I think if Mirror gets it right and builds a following, then opportunity to add features such as augmented reality and third party apps could be huge. Though that involves diving into a space with well funded competitors and could potentially raise concerns around data privacy. It will be interesting to see how this space evolves.
Interesting article and thought provoking questions. I like the idea of infrastructure-agnostic platforms like DataDog that sit on top of a company’s existing stack and provide unique value to their customers. One concern is that existing cloud providers are making efforts to build in at least some of this functionality (e.g. Azure Application Insights and Amazon CloudWatch), and may have an advantage due to their relationships with companies that are already heavily invested in a particular infrastructure, or may have more complex purchasing processes. I’m interested to see how DataDog will continue to compete and differentiate itself.