Why does it raise alarm? Pretty sure all this spending was planned.
Think of it as the difference between the waiter describing dishes with ingredients you don't really understand (or maybe even taste) vs presenting the bill for the meal.
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Why does it raise alarm? Pretty sure all this spending was planned.
Think of it as the difference between the waiter describing dishes with ingredients you don't really understand (or maybe even taste) vs presenting the bill for the meal.
Earlier quoted context omitted.
> Everyone is in too deep to now admit that there’s a problem I'm not sure how to square this with the dramatic improvement in LLM capabilities in the last 8-9 months. If anything, it makes the earlier investments look prescient?
I'm not sure I've seen what I would call dramatic improvement since maybe GPT4? Sure, things got better. But I'd call it iterative more than revolutionary. I still wouldn't trust any of the models to do anything meaningful unattended. They all still do dumb shit all the time. Plus, even if they were genuinely dramatically better, the businesses sure as hell aren't. They're burning money left and right, they have no m…
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> Everyone is in too deep to now admit that there’s a problem I'm not sure how to square this with the dramatic improvement in LLM capabilities in the last 8-9 months. If anything, it makes the earlier investments look prescient?
The problem is that the dramatic improvement in capabilities is not translating to a dramatic increase in revenue.
Earlier quoted context omitted.
The problem is that the dramatic improvement in capabilities is not translating to a dramatic increase in revenue.
> not translating to a dramatic increase in revenue. Completely false. AI and AI related revenues are growing exponentially .
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I'm not sure I've seen what I would call dramatic improvement since maybe GPT4? Sure, things got better. But I'd call it iterative more than revolutionary. I still wouldn't trust any of the models to do anything meaningful unattended. They all still do dumb shit all the time. Plus, even if they were genuinely dramatically better, the businesses sure as hell aren't. They're burning money left and right, they have no m…
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Earlier quoted context omitted.
The problem is that the dramatic improvement in capabilities is not translating to a dramatic increase in revenue.
The article notes Google Cloud revenue grew 82% YoY
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> Everyone is in too deep to now admit that there’s a problem I'm not sure how to square this with the dramatic improvement in LLM capabilities in the last 8-9 months. If anything, it makes the earlier investments look prescient?
Presumably at some point you need a measurable productivity return yea? Maybe organizations are not built around skill and aptitude so much as liability, which LLMs cannot provide barring (very welcome and also very unlikely) legislation in the US.
At what point? This technology is brand new. Did you think we were going to double productivity in 3 years?
Capacity is being built. It's hard to build data centres, there are no chips, there is no memory, it's hard to get talent, we don't have the energy to power the facilities.
No one knows where this is going. We are scratching the surface. There is an absolute boom happening, and yet every day I have log onto Hacker News and read this nonsense about everything falling apart. Are we living in the same universe??? So-called "technologists" saying, "meh, it's not that cool". Okay.
Guess what? You're not Michael Burry. Nobody cares or will care that you "called it". Look around this place: you aren't even slightly contrarian.
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"Anthropic and OpenAI generate a lot of revenue with relatively few employees – an estimated $9M and $5.5M in revenue per employee (RPE), respectively. If either company were to go public, it would have a higher RPE than any public tech company on Forbes’ Global 2000 list." https://epoch.ai/data-insights/revenue-per-employee-ai-compa...
Revenue isn't profit though. Anthropic is already profitable OpenAI financials have looked doomed for the past year