Quote: "The entire system only works if AI revenue grows fast enough to outrun the obsolescence treadmill. For that to happen, Microsoft would need approximately $130 billion per year in new AI revenue, Google $100 billion, Amazon $120 billion, and Meta $70 billion. Against a current reality of $18 billion in total industry AI revenue and zero profits, that gap is not a rounding error. It is the entire bet."
This submission is junk, and the the title is editorialized.
Direct reply from Claude: https://claude.ai/share/628e6a1d-087d-4454-95e3-cf8a3c4a5b72
"The case for a bright future is strong."
I trust Claude over JCW2001
It is not magic, it is not an oracle, it is not good at analysis, and is particularly bad at predicting the future.
(If OP was trying to make the bull case then the same snark would still apply.)
Instead of massive scaling advantages which has given software its extreme valuation, it now hit on something that is almost a perfect commodity. Energy and depreciation are easy to calculate and its subject to global competition.
Great for consumers, less so for people looking for a ROI.
It used to be hard to be "web scale" and available, now that's either k8s or a few checkboxes in AWS.
Yahoo used to be able to "coast" on the compellingness of their services because 80% attractive with 100% available and 100% global reach crushes 90% attractive with 95% available and 25% global reach.
I was often confused by the hyperfocus of analysts asking "Is Y! a tech company or a content company?"
What they were really asking was if we should be valuing Yahoo! as 30%+ margin on putting ads next to Yahoo! News articles, or 10x multiplier on originating GMail/Search?
I think "data is the only moat", and in a way that goes back to the "first to market / eBay" POV, and the difference between first to market and fast follower is super interesting!
b) in my observation, the longer context window, the more unhinged/pessimistic LLM output becomes
The numbers are bad therefore it will collapse.
What's interesting to me is how quickly the big AI labs are losing their competitive edge even before becoming profitable. Models that are less than one year behind the leading ones are effectively commoditised already. If OpenAI and Anthropic disappear tomorrow, it will be no more than a brief inconvenience to LLM users. They're spending a lot of money for an almost negligible advantage.