this post was submitted on 31 May 2025
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Showerthoughts
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A "Showerthought" is a simple term used to describe the thoughts that pop into your head while you're doing everyday things like taking a shower, driving, or just daydreaming. The most popular seem to be lighthearted clever little truths, hidden in daily life.
Here are some examples to inspire your own showerthoughts:
- Both “200” and “160” are 2 minutes in microwave math
- When you’re a kid, you don’t realize you’re also watching your mom and dad grow up.
- More dreams have been destroyed by alarm clocks than anything else
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Well, the thing is that we're hitting diminishing returns with current approaches. There's a growing suspicion that LLMs simply won't be able to bring us to AGI, but that they could be a part of or stepping stone to it. The quality of the outputs are pretty good for AI, and sometimes even just pretty good without the qualifier, but the only reason it's being used so aggressively right now is that it's being subsidized with investor money in the hopes that it will be too heavily adopted and too hard to walk away from by the time it's time to start charging full price. I'm not seeing that. I work in comp sci, I use AI coding assistants and so do my co-workers. The general consensus is that it's good for boilerplate and tests, but even that needs to be double checked and the AI gets it wrong a decent enough amount. If it actually involves real reasoning to satisfy requirements, the AI's going to shit its pants. If we were paying the real cost of these coding assistants, there is NO WAY leadership would agree to pay for those licenses.
Yeah, I don't think AGI = an advanced LLM. But I think it's very likely that a transformer style LLM will be part of some future AGI. Just like human brains have different regions that can do different tasks, an LLM is probably the language part of the "AGI brain".
What are the "real costs" though? It's free to run a half decent LLM locally on a mid tier gaming PC.
Perhaps a bigger problem for the big AI companies rather then the open source approach.
Sure, but ChatGPT costs MONEY. Money to run, and MONEY to train, and then they still have to make money back for their investors after everything's said and done. More than likely, the final tally is going to look like whole cents per token once those investor subsidies run out, and a lot of businesses are going to be looking to hire humans back quick and in a hurry.
Surely the money to run is very low through, at least per user