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Notes -
Some people need a refresher on sigmoid functions. I've thought this for a long time about singularity believers.
Early in the process it looks exponential and projecting forward a few periods gives implausible results. "At this rate of bacterial growth, the entire universe will be this bacteria in a few months" level of silliness. Obviously that doesn't happen and instead some physical constraint is reached and the system slows in growth and flattens off over time.
"At this rate of growth, the entire lake will be this algae in a few days". "Ludicrous silliness!"
The point is we don't have a clue where the sigmoid will level, and there doesn't seem to be a strong reason to think it'll level at the human norm considering how different AI as a technology is to brains. To be clear, I can see reasons why it'll level below the human norm; lithography is a very different technology from brains and it does sure look like the easily Moore-reachable performance for a desktop or even datacenter deployment will sigmoid out well below the human brain scale. But note how that explanation has nothing to do with human brains for reference, and if things go a bit different and Moore keeps grinding for a few more turns, or we find some way to sidestep the limits of lithography like a much cheaper fabrication process leading to very different kinds of deployment, or OpenAI decide to go all in on a dedicated megatraining run with a new continuous-learning approach that happens to work on first, second or third try (their deployed capacity is already around a human brain), then there's nothing stopping it from capping out well above human level.
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