Jesus christ, not even a biology thread is safe in the orange website.
Descartes compared the human mind to waterworks and hydraulic machines, other authors used mechanical clocks, telegraph systems, digital computers, and (in the recent decades) neural networks.
In the end it's all computing and to a degree all of those models serve as good analogies to the wetware, one just needs to avoid drawing wild conclusions from it.
I'm sure there will be new analogies in the future as our tech progresses.
We don't literally train on today's prompts while we sleep, but there actually _are_ some _computing_ tasks going on in our brains at that time that seem to be important for the system.
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?
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.
It is pretty common during the fine-tuning phase.
It's like someone said while driving the car "let's give it some gas" and you said "but the tank is almost full" when they obviously meant "let's press the accelerator pedal"
Since in-context learning is a thing, “adding tokens to the context window”, at least with the intent and effect of having a particular impact on capabilities when inference is run on the context to which they were added, is, arguably, a kind of training.