81–90 of 218 posts
The biggest issue with Nvidia is their revenue is not recurring but the market is treating their stock as it were, which is correlated with all semi stocks, with a one-time massive CAPEX investment lasting 1-2 years. Simple as this - as to why its just not possible for this to continue.
Their margin is ridiculous and they are still unable to meet demand.
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Not sure why you're getting downvoted. If you speak with AI researchers, they all seem reasonable in their expectations. ... but I work with non-technical business people across industries and their expectations are NOT reasonable. They expect ChatGPT to do their entire job for $20/month and hire, plan, budget accordingly. 12 months later, when things don't work out, their response to AI goes to the other end of the…
> If you speak with AI researchers, they all seem reasonable in their expectations. An extraordinary claim for which I would like to see the extraordinary evidence. Because every single interview still available on YT form 3 years ago ...had these researchers putting AGI 3 to 5 years out ...A complete fairy tale as the track to AGI is not even in sight. If you want to colonize the Solar System the track is clear. If…
In reference 14 we read > However, what’s become clear is that OpenAI plans to pay for Nvidia’s graphics processing units (GPUs) through lease arrangements, rather than upfront purchases I wish someone here could explain it to a dummy like me. Nvidia tells OpenAI: heres some GPUs, can you pay for them over 5 years. How is this an "investment" by Nvidia? That reference keeps calling this an investment, but what they d…
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AGI is not near. At best, the domains where we send people to years of grad school so that they can do unnatural reasoning tasks in unmanageable knowledge bases, like law and medicine, will become solid application areas for LLMs. Coding, most of all, will become significantly more productive. Thing is, once the backlog of shite code gets re-engineered, the computing demand for a new code creation will not support bu…
> AGI is not near There's also plenty of argument to be made that it's already here. AI can hold forth on pretty much any topic, and it's occasionally even correct. Of course to many (not saying you), the only acceptable bar is perfect factual accuracy, a deep understanding of meanings, and probably even a soul. Which keeps breathing life into the old joke "AI is whatever computers still can't do".
I don't think I'll ever stop finding this funny.
It was written by Opus 4 too.
Fiber networks were using less than 0.002% of available capacity, with potential for 60,000x speed increases. It was just too early. I doubt we will see unused GPU capacity. As soon as we can prompt "Think about the codebase over night. Try different ways to refactor it. Tomorrow, show me your best solution." we will want as much GPU time at the current rate as possible. If a minute of GPU usage is currently $0.10, a…
> I doubt we will see unused GPU capacity I'd argue we very certainly will. Companies are gobbling up GPUs like there's no tomorrow, assuming demand will remain stable and continue growing indefinitely. Meanwhile LLM fatigue has started to set in, models are getting smaller and smaller and consumer hardware is getting better and better. There's no way this won't end up with a lot of idle GPUs.
Fiber networks were using less than 0.002% of available capacity, with potential for 60,000x speed increases. It was just too early. I doubt we will see unused GPU capacity. As soon as we can prompt "Think about the codebase over night. Try different ways to refactor it. Tomorrow, show me your best solution." we will want as much GPU time at the current rate as possible. If a minute of GPU usage is currently $0.10, a…
> I doubt we will see unused GPU capacity I'd argue we very certainly will. Companies are gobbling up GPUs like there's no tomorrow, assuming demand will remain stable and continue growing indefinitely. Meanwhile LLM fatigue has started to set in, models are getting smaller and smaller and consumer hardware is getting better and better. There's no way this won't end up with a lot of idle GPUs.
Fiber networks were using less than 0.002% of available capacity, with potential for 60,000x speed increases. It was just too early. I doubt we will see unused GPU capacity. As soon as we can prompt "Think about the codebase over night. Try different ways to refactor it. Tomorrow, show me your best solution." we will want as much GPU time at the current rate as possible. If a minute of GPU usage is currently $0.10, a…
> I doubt we will see unused GPU capacity I'd argue we very certainly will. Companies are gobbling up GPUs like there's no tomorrow, assuming demand will remain stable and continue growing indefinitely. Meanwhile LLM fatigue has started to set in, models are getting smaller and smaller and consumer hardware is getting better and better. There's no way this won't end up with a lot of idle GPUs.
2% of it is dedicated to thinking.
My guess is that as a species, we will turn a similar percentage of our environment into thinking matter.
If there are a billion houses on planet earth, 2% of it are 20 million datacenters we still have to build.
In reference 14 we read > However, what’s become clear is that OpenAI plans to pay for Nvidia’s graphics processing units (GPUs) through lease arrangements, rather than upfront purchases I wish someone here could explain it to a dummy like me. Nvidia tells OpenAI: heres some GPUs, can you pay for them over 5 years. How is this an "investment" by Nvidia? That reference keeps calling this an investment, but what they d…
At the end Nvidia retains ownership of what are probably very low value assets.
Contrast that with car leases: there is a robust market for used cars.
Nvidia is in effect financing the GPUs by not requiring the full payment up front.
Do the lease payments add up to the total cost?
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>Meanwhile LLM fatigue has started to set in Has it? I think there is this compulsion to think that LLMs are made for senior devs, and if devs are getting wary of LLMs, the experiment is over. I'm not a programmer, my day job isn't tech, and the only people I know who express discontent with LLMs are a few of programmer friends I have. Which I get, but everyone else is using them gleefully for all manner of stuff. An…
You should get on Reddit, people hate AI with a passion there. People I meet in real life hate it also. I think the public actually hates AI more than it should now.
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>Meanwhile LLM fatigue has started to set in Has it? I think there is this compulsion to think that LLMs are made for senior devs, and if devs are getting wary of LLMs, the experiment is over. I'm not a programmer, my day job isn't tech, and the only people I know who express discontent with LLMs are a few of programmer friends I have. Which I get, but everyone else is using them gleefully for all manner of stuff. An…
You should get on Reddit, people hate AI with a passion there. People I meet in real life hate it also. I think the public actually hates AI more than it should now.
Those people (well really it's teens and college kids) live on reddit, they are so far from an accurate representation of reality its insane.