tudorizer

A lot of attention is aimed at the huge investment rounds, cash burned into training foundation models (the trillions mentioned by Sam A.) and not enough analysts explain the units of economics to understand a business.

If you wonder why investors still think it’s a good idea to part with their money, I tried to break down the economic units and long term potential how all this could make sense.

Partial TL;DR

- Cash burn is not a fair approximation for COGS. OpenAI spends mostly on R&D like a pharmaceutical company does. - ChatGPT 4o could be making more than 12.8% in gross margin. - ChatGPT OSS 120B could be making 89% gross margin. It is 90% cheaper than 4o-mini with equivalent reasoning and 3x faster inference. - ChatGPT 5's gross margin is most likely to fall between 12.8% and 89%.

Full breakdown: https://medium.com/@brenoca/openais-road-to-profitability-8c7231f8494b

Within the single context of writing code, we've had quite a few attempts throught history to generate code. Often times within very rigid constraints.

GenAI is fits in the same space, but with extra steps, benefits and drawbacks. It's not "a junior dev". It's a new hammer.

The craftsman enjoys the new hammer, pushes its limits, nerds out about the intricacies. Tools have limits in terms of wear and tear, plus cost.

Junior devs are humans, looking to survive and flourish. They pick up new tools faster than most. The only barrier the same that has always been: access to said tools and visibility over the outcome.

What's the benefit of over-anthropomorphizing a hammer?