Oh wow, this is both really cool and slightly terrifying. I definitely have concerns about the prospect of using this technology for police work. I could easily see a situation in which biases in both the AI models and in law enforcement lead to the over-policing of marginalized communities. I also share Irina’s concern about a private company deciding which governments and conflicts can leverage this very powerful technology. Thanks for sharing Yannik.
Oh wow, this is such an interesting application for AI. I wonder if L’Oreal also applies some of their AI tools to optimize their manufacturing and supply chain? It’s also super interesting that they scrape social media to detect emerging trends. Thanks for sharing!
Thank you so much for sharing the story Saad and I love the question Dr. Ming poses at the end. I feel like there’s a broader question here as well about the potentially negative impact of venture capital on AI development. It closes off development in areas that may not be easily monetizable but could still be tremendously beneficial to society.
Really interesting way to explore how the AI handles abstract ideas. It seems like it anchored only to “question” part of the prompt for the panel on the left. The panel on the right definitely seems a bit more abstract. It seems like AI isn’t good at figuring out abstract prompts yet.
I’m constantly amazed at how specific the image request can be with AI image generators. As others have said, it can’t get exact details yet, but it’s honestly passable if you know the prompt! I wonder how much more training these AIs will need before they can get close on the fine details.
Really interesting! It’s fascinating that all of the images are of white-collar, corporate workers.
Thanks for the post Nthato! I had a case over Web3 and Blockchain in VCPE the other day and I left it struggling to figure out what an actual application of blockchain technology would be. It’s interesting to see a really clever example of a company using the technology to actually create value. It’ll be interesting to see how the technology will evolve in the future. Your post also made me finally look into how Ethereum actually, so thank you for that!
I agree, Fiverr is definitely an interesting comparison to ZBJ. Building on Nitya’s comment, I wonder if they continue to charge the 20% commission on transactions because of their low disintermediation. From what I remember, that’s what led ZBJ to do away with their commission. It would be curious to see what plans they have, if any, to expand their service offerings. It seems like there could be a lot of room for them to pivot their business model in the manner that ZBJ did. Thank you for the post Sultana!
This is a really cool business! They’re a logistics company, but also way more than a logistics company. They even provide loans to retailers. Reading through this, I can’t help but wonder if they’ll eventually go the way of Amazon and start using their data/analytics, warehouses, and logistics to create their own products to sell on the platform. Great post Karthik!
This is such an interesting application of data! I also wonder if there could be other insights buried within the data. Would there be a future where, after watching and learning your pet’s behavior, the device would be able to detect when your pet is hungry, thirsty, needs to go to the bathroom, etc? Jumping from that, I could imagine an ecosystem where Furbo integrates with other smart devices in the home to automatically clean up after a pet or find somebody from TaskRabbit to walk your dog while the owner is at work.
This is such a cool startup! The applications seem most direct in property insurance, but I also wonder if there could be applications in other parts of the insurance industry, such as crop insurance in agriculture, or even severe weather early warning systems for towns/cities.
Really enjoyed reading this post and about how Grammarly works on the backend. I’ve been a user for several years and it’s interesting to think that while users have been using Grammarly to improve their writing that Grammarly has been using users’ errors and corrections to improve their machine learning and recommendations. I also had a similar question as Yifei though around their freemium pricing strategy. I wonder if they’ll stick with that as they continue to grow or if they’ll think of other ways of monetizing their machine learning tools (maybe partnering with Microsoft Office?)