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> That revenue might be split between a few hundred thousand companies. That’s not how power laws work. Over time, many niches will be created but usually it s
by huijzer 3y ago
> That revenue might be split between a few hundred thousand companies.
That’s not how power laws work. Over time, many niches will be created but usually it starts with one big winner taking it all. For example, first there where many half baked solutions, then there was Netflix and now we have all kinds of streaming providers, many of which are trying to find a niche such as Apple-owners or Disney fans. Similarly, we first had an iPhone and now small phones, big phones, tablets, touch laptops etc etc.
- lelanthran 3y ago> Over time, many niches will be created but usually it starts with one big winner taking it all. Usually, yes. But in this case it appeared to have started with multiple small providers, with multiple non-half-baked services. There doesn't appear to be a moat for anyone in this market. Unlike streaming video (Netflix, et al) which has a moat (exclusive content), or social media (network effects), or ad industry (eyeballs). With AI there is no moat that I can think of (quite happy to be provided with potential counter-examples, even if they are only hypothetical). Let me try a different way to explain it: If you're building an ad network, a social media service, a SaaS dev-product provider, a video streaming service, etc, you will be unable to convince users to switch just by having a better product. The moat will keep them on the worse product (eyeballs, network effect, legacy support, exclusive content respecitively) no matter what you do. With AI, there is no moat that I can think of - if you were to start an AI product today, what is the AI-specific moat you can use to keep out future competitors? Legislation, maybe? I'm not sure that iPhones are a good example. It's a product, not a service. By definition there's no moat.
- huijzer 3y ago> With AI there is no moat that I can think of I was also thinking about that yes. I think it’s mostly data (a sort of network effect), capex, and state-of-the-art engineering/research. A bit like TSMC and ASML. Also heavy capex and engineering moats.