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> why ancient ancestors started sleeping I tend to believe that our ancestors didn't start sleeping, they started waking up ! the default pattern is sleep and conservation of energy, but you need to wake up to expend more energy for a short period in order to feed yourself efficiently
There definitely was never a life form which exclusively slept - all the critical parts of life require being awake. Life that didn't sleep, however, is possible.
i wonder if it relates to that chronic laziness disease, i cant remember what its called
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Jesus christ, not even a biology thread is safe in the orange website.
Indeed. Animals without linguistic ability (like fruit flies) need sleep, but after ChatGPT's release in 2022, now tech bros think LLMs specifically might model the animal brain in general because of anthropocentrism and anthropomorphism. It's also a fundamental misunderstanding of how LLMs work, mixing up inference with training.
Can we say that after ChatGPT's release in 2022, now antitech bros think everything is about LLMs specifically?
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> So the ancient mystery of why we need sleep might have just been answered. There are layers to this, some of which are definitely not ancient mysteries. We sleep because the environment has a day-night cycle. If any task an organism must perform is better done during the day, then evolution has a very clear gradient towards only doing that thing during the day. That leads to doing other things at night, since it wo…
The question isn't the timing but why it happens at all. Even at night, being unaware of one's surroundings during sleep is a huge disadvantage that requires lots of effort and adaptation to work around. It needs to produce commensurate benefits, but we're not sure what they are.
Furthermore, sleep is very specifically about the taking the brain offline: that's what deteriorates first in the absence of sleep and the tortured workarounds for animals that absolutely must avoid sleep (e.g. migratory birds) involve sleeping part of the brain at a time. Any explanation that isn't highly specific to the brain's responsibilities has the immediate hurdle of explaining this away, and for that reason I don't buy the mitochondrial explanation. Mitochondria are too universal and sleep is too specific to the brain. Energy is fungible, so I don't buy that nature wouldn't figure out the "trick" of having a subset of the mitochondrial population sleep at a time.
My money is on the "brain algorithm" requiring an online/offline phase, whether that's contrastive learning or memory consolidation or something else. There are lots of candidates for fundamental brain algorithms with the "feature" that they require an offline phase that cannot be incrementally worked around, and these fit the observations much better.
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And exactly as I said, Ozempic does more harm in the long run.
There are mountains of data that show it actually has long term benefits beyond weight loss (beyond even the obvious health markers that improve due to losing weight). I wouldn’t be surprised at all if the majority of the population ends up taking next gen drugs in this space, most of them purely for longevity.
So the ancient mystery of why we need sleep might have just been answered. The paper shows that cell‑autonomous mild uncoupling in Drosophila sleep‑inducing neurons -- via Ucp4A/Ucp4C -- keeps the flies awake by lowering mitochondrial Δp and therefore electron leak. This suggests a biochemical rationale for sleep -- which is postponed by the uncoupler. That form of pharmacological manipulation is also a very local in…
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Indeed. Animals without linguistic ability (like fruit flies) need sleep, but after ChatGPT's release in 2022, now tech bros think LLMs specifically might model the animal brain in general because of anthropocentrism and anthropomorphism. It's also a fundamental misunderstanding of how LLMs work, mixing up inference with training.
It was applicable to all neural networks, not just LLMs. Can we say that after ChatGPT's release in 2022, now antitech bros think everything is about LLMs specifically?
Prompts are specific to LLMs. Most neural networks don't have prompts.
Additionally, prompts happen during LLM inference, not LLM training. There are many non-technical people who claim they have experience "training" LLMs, when they are just an end user who added a lot of tokens to the context window during inference.
The heart beats non-stop and doesn't sleep. How does this fit with this theory?