Ahmed Al-Ghanim's Profile
Ahmed Al-Ghanim
Submitted
Activity Feed
I completely agree. Many business strategists believe that the second mover is actually most likely to succeed in very innovative industries with relatively low switching costs. Valve could create more barriers to entry by creating a large game library with Steam.
Great post Everett! I completely agree that Nvidia should avoid building its own cloud offering. I also agree that Nvidia shouldn’t forget about the gaming industry, especially with the rise of virtual reality and longer console lifecycles which would increase the appeal of Nvidia’s offering. I’m not sure if Nvidia’s video game offering currently targets gaming consoles as well but that could be an attractive market. Given the question you raise about hosing business data, I wonder if there would be a way for Nvidia to focus solely on the hardware, allowing another player to worry about convincing businesses to relinquish some control over their data. Additionally, by moving to software I worry that Nvidia would stray too far away from its core competency.
A really interesting piece on Alexa. While initially pessimistic about the future of voice shopping, I do think there are a number of features that can address customer pain points when it comes to voice shopping. One could be a feature where the AI behind Alexa could identify the most consistent themes across reviews of the product and list them out to the user. This, combined with Amazon’s 30 day return policy, could be a useful offering for consumers, especially with lower cost purchases. With regards to the first question you raised, I believe it is important for the voice shopping experience to be as consistent as possible across all merchants. Any differences would frustrate users, especially given Alexa’s limited ability to respond to a user’s questions if any confusion arises.
I really enjoyed your post! I recently went to Disney World on a family trip and bought one of these magic bands. It actually syncs to a Disney World app which allows the company to collect even more data on what you do, even after you take off the band (which touches on the question JP raised). With regards to the questions you raised, I think content creation across TV and movies drives the demand for the parks and not the other way around. Additionally, I don’t believe park visitors would be a representative sample of Disney’s consumers, especially since many of Disney’s largest movies are not targeted towards children. I believe these factors are the main issues that would stand in the way of focusing too much on data collected from parks to inform the company’s broader decisions.
Great article Danielle! I think you pose interesting questions which I’d like to answer by focusing on investing organizations. Some concerns investing organizations may have about depending on AI for their investment strategies is that once AI becomes mainstream, the strategies generated by different algorithms, and hence different firms, may be similar. This would decrease the returns of any one institution because over the long-run AI would theoretically increase market efficiencies decreasing opportunities for excess returns. A more dire consequence of this dependence on AI is that if all institutions are following similar strategies, it may increase the cyclicality of business cycles as a majority of firms would buy at the same time, leading to an increases in prices, and subsequently sell at the same time, leading to a crash.
Great article! It’s really interesting to see how this system could be implemented in the future. To answer your question, I don’t think it would be just to rely solely on a computer, especially in the near term, given how each case is unique. I also believe that the grounds for an appeal would increase when an algorithm is used for sentencing, since in the near term there will be a significant chance of an error. I think this could function more as a tool for a police officer or judge rather than the sole sentencing mechanism. Additionally, it would be useful to track the differences in the sentences given by the officer and the algorithm as a way to identify any potential biases.