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Daniel Quiroga
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Great post!
I never imagined AI was so present in the army, thanks for the article. I see great potential in AI/Human combinations versus pure AI. Specially in vehicle control, 100% autonomy is decades away, but having a virtual copilot already doubles the pilot pool in the army. Hope we can see more AI/Human duos rather than the AI going solo.
Great post and great technology! I smiled when reading about reuniting refuge families. Technology commercialization has historically been difficult. This is just another example of how big AI can be used for the good; we need more stories like this.
While reading, I imagined a possible use case in which families can find missing relatives. Kidnapping is still present in Latin-America and all too often cases are unresolved. Having an AI that constantly scraps the web for image matches of lost relatives would be extremely valuable for hurting families.
Thanks for the post! I love ClassPass. It is such a great way to make new friends in new cities while keeping helathy. However, the value fo the variety of the offering, quickly decreases. Once I find the class I like, I don’t really new to pay for the option to go to other clasess. For this, I wonder how sustainable ClassPass is.
Thanks for the post!
Venmo is indispensable in the US. Even though the core functionalities are similar to PayPal, Venmo offers much better UX. Its social component allows for viral growth(network effects) and the many functionalites make it a powerful tool. All being said, it is still not clear to me why PayPal has not fully integrated with Venmo and continues to compete with it in some markets.
Netflix definitely rocks when it comes to data!
I also believe the next steps for Netflix are VR and gaming. Netflix knows how many users love sci-fi and would pay extra for a VR experience Moreover, gaming production is similar to film production: create something and hope it’s a home run. Netflix revolutionized film production by using data to create sure-things. Can Netflix use movie data to create sure-thing games? Probably yes. Historically, movie-based games have been more successful than independent stories as they exploit existent customer bases.
Great post!
Data in the healthcare space has always been tricky as it is typically protected by privacy regulations worldwide. To make matters more complicated, most of the data is unstructured and can’t be used directly on ML.
I see great potential for the commercialization of EMR. Drugs undergo extensive testing before being rolled out to the market (for obvious reasons). However, the case could be made that this is not enough. Testing thousands of patients is not representative of a global population. People with existing rare diseases might have negative reactions to the drug and have not come up during FDA testing.
Thanks for the post, Manu!
Payment fraud has historically been the most painful problem in the fintech industry. However, this is often not a user’s concern but a company’s problem, in this case, American Express. Users are not incentivized to participate in enhanced security measures to minimize fraud. These measures can be as simple as logging in for international travel on the American Express portal or activating two-factor authentication for large transactions. To continue the example above, users who don’t record international travel frequently get their cards blocked, negatively affecting user experience. To make matters worse, blocked cards don’t generate revenue for American Express.
American Express is taking the right approach by developing its algorithms in a separate entrepreneurial environment. Who knows, maybe in the future the solution spins out and process more than only American Express transactions.