Comment by simonw
14 hours ago
Genuine question: what's wrong with it?
I thought this was one of my best pieces of writing this year.
(In case you missed it, the title was meant as a subtle burn on those two companies - it's pretty absurd for them to only just be finding product-market fit when they're already valued at over a trillion dollars.)
I see you trying really hard to make things right and are everywhere in the comment. I feel a bit bad in formulating my comments a bit polemical.
Also my highest respect for responding so calmly without lowering your debating level to mine. I try to best to explain what I think is wrong.
To start I didn’t interpret the article as a burn.
I think it’s interesting to explain what’s wrong with it, because it seems similar to what‘s wrong with AI. The issues are subtle.
- Anthropic doesn’t have a profitable quarter, it’s financial engineering (https://www.wheresyoured.at/anthropics-profitability-swindle...)
- The first argument about your subscription price, doesn’t has anything to do with the overall claim of the article. It would if at all be a weak argument to support the opposite. Subsidizing prices signals a lack of PMF.
- That you hire sales people after you had a billions of funding is nothing surprising and doesn’t indicate PMF or not.
- AI Implementations are fresh and of course AI Failures are thin, but so are AI successes. I haven’t seen any companies creating billions of shareholder value because they’ve massively invested in AI and their competitiors didn’t You really can look at these things in 5 to 10 years and it is multi-faceted including cultural acceptance.
- That they need to buy more compute to satisfy the requests is probably the strongest argument in the artical, but don’t conclusive. The product is been sold heavily subsidized and in hype cycle. And again both OPENAI and Anthropic have to show growth in order to justify the IPO.
- Regarding the part about revenue I refer to the linkedm article above, as it does explain it very well.
The conclusion is reasonable given the arguments, but not the title.
However it is missing all the real discussion points that are actually in observation at the moment.
Local models as alternatives, IPO finanical engineering, how AI implementation actually will perform over years... Let’s all not forget crypto. It’s been full of "use cases" just a bunch of years ago. I like the idea of crypto(btc,eth) and I’m still invested, but 99.99% of coins have died on promies.
So this is not a piece of critical thinking, but this reads like a twitter thread to sell me a course :/