(2022) article. Interestingly, a lot has changed in just under 9 months in the AI world. GPT 4 has come and it's actually an AI crunch, not a gain. I wrote in another post I submitted but the gist is that bootstrapped startups and incumbents will be the true winners while VC backed startups won't, because there is no moat in AI to defend their high valuations.
I work in a domain of applying AI to specific enterprise domain. It's not like you can crawl our data in the open web. Getting any data from clients is years of lawyer struggles and chicken and egg problems to solve. Fine-tuning models to client expectations - they are not going to go through the process again with someone else.
And moat in B2C AI is owning tons of your personal data and habits that Google and Facebook do. It's just not trully utilized with GPT models yet.
I heard from a large AI founder recently on this topic. Data is an okay moat, but in this craze we'll see the power of data shrink. Companies are getting enough VC funding ($10m-$100m+) to buy any data they need. A better model could also make up for a lack of better data.
Instead, the best moat is to know that your product isn't a thin replicable wrapper for ChatGPT but instead has a large surface area, with lots of well-built features. Continue building those features at a fast pace, and you can win.
GPT-3.5, GPT-4, and similar are fairly new. There are many uses of the technology that remain unexplored by product people, not to mention the technology is getting more advanced and has more capabilities by the week (or day or month, depending on your perspective).
The new AI platform may over time enable more products than even the shift to mobile.
ADDED:
What's implied is that the moat could be built and some kinds of moats are not yet well-known or prevalent. Proprietary data is often mentioned. But also the application on top of LLMs (or LFMs) needs not be just a thin layer with little technical barrier.
Comments
(2022) article. Interestingly, a lot has changed in just under 9 months in the AI world. GPT 4 has come and it's actually an AI crunch, not a gain. I wrote in another post I submitted but the gist is that bootstrapped startups and incumbents will be the true winners while VC backed startups won't, because there is no moat in AI to defend their high valuations.
https://news.ycombinator.com/item?id=36761643
Data is moat in AI.
I work in a domain of applying AI to specific enterprise domain. It's not like you can crawl our data in the open web. Getting any data from clients is years of lawyer struggles and chicken and egg problems to solve. Fine-tuning models to client expectations - they are not going to go through the process again with someone else.
And moat in B2C AI is owning tons of your personal data and habits that Google and Facebook do. It's just not trully utilized with GPT models yet.
I heard from a large AI founder recently on this topic. Data is an okay moat, but in this craze we'll see the power of data shrink. Companies are getting enough VC funding ($10m-$100m+) to buy any data they need. A better model could also make up for a lack of better data.
Instead, the best moat is to know that your product isn't a thin replicable wrapper for ChatGPT but instead has a large surface area, with lots of well-built features. Continue building those features at a fast pace, and you can win.
GPT-3.5, GPT-4, and similar are fairly new. There are many uses of the technology that remain unexplored by product people, not to mention the technology is getting more advanced and has more capabilities by the week (or day or month, depending on your perspective).
The new AI platform may over time enable more products than even the shift to mobile.
ADDED:
What's implied is that the moat could be built and some kinds of moats are not yet well-known or prevalent. Proprietary data is often mentioned. But also the application on top of LLMs (or LFMs) needs not be just a thin layer with little technical barrier.
Completely agree - much reduced opportunities for differentiation with the new LLMs.