Some indications in the text suggest that their insights are somewhat limited.
> In other words, once you ignore the cost of building infrastructure, AI is very profitable.
Once a provider stops such investments, they stop being "frontier" which makes them unattractive immediately. These two things are tightly connected.
> If the AI industry has to pay off 5 trillion dollars over the course of 20 years, that's 250 billion dollars a year. For context, Alphabet (parent company of Google and Youtube) reported earning almost 162 billion dollars of revenue just in 2019.
Revenue vs profit
> Most (or maybe even all) programmers and mathematicians are worse at their respective field than an AI swarm equipped with a good harness
Anybody doing serious software engineering will wholeheartedly disagree.
> People can theoretically switch from model to model, but people tend to settle in with a product and develop brand loyalty. For example, I pretty much only use ChatGPT, not because I have any really reason to, but because it was the first LLM that I ever used
LLMs are just one piece of the tool chain, a mostly interchangeable one. Which one a concrete product uses is not of concern to the end user. This quote very much misses the role of LLMs and their providers in the big tech picture.
> In 2023, a memo from Google called "We Have No Moat, And Neither Does OpenAI" was leaked, which outlined how the open source community was keeping pace with AI labs
Labs releasing the weights to their models is not what is typically called the "open source community".
I could go on but it's just not a very well-argued opinion piece. Unclear how it made it to the HN front page.