[alextheparrot]

a16z has a podcast where they explored gross margins a month back. The panel called out AI as an example of a software business that has a high likelihood of not having standard SaaS margins (Most of the panel thought this could be a limitation).

The podcast is nice because I think it holistically explores gross margins in a way that you start to understand how it might impact AI as a viable primary business model and valuations related to companies who that is the case for. Quite complementary to the article.

Might be interesting to people who are interested in this article: https://open.spotify.com/episode/79lJCrHB3nBn1qXCxKA5s7?si=R...

[Jack000]

This is a great feature of the AI space for startups - in the short term it reduces competition, in the long term it's not really a problem. If your business is break-even currently, it will be profitable in 2-3 years due to declining cost of compute. In 10 years the compute costs will fall by an order of magnitude and more efficient models will become available, making the economics closer to traditional SaaS.

This does disadvantage smaller bootstrapped businesses though.

[kippinitreal]

Not true if there’s enough competition that you need more resources for a bigger model in 2-3 years. Anecdotally, it seems like SOTA model training costs are rising much faster than computer cost is falling.

[Jack000]

maybe, but model quality doesn't scale linearly with model size. The performance/dollar metric is more important, and that definitely will decline over time.

Personally, I have a boots trapped business that uses a transformer model. I'm not worried about supermassive models like gpt3 because it would be way too expensive to deploy for my use case, with marginal additional quality.

[cinntaile]

While I haven't listened to this particular one, I just wanted to say that their podcasts are usually quite interesting if you're interested in new technology/science.