I’m pretty sure a chimp moving at 2000 kph is a straight-up hypersonic missile, can run across the ocean, and can sink battleships through kamikaze attacks. I think the chances of defending against 800 billion of them are effectively zero. I think the chances of defending against 80 million of them is still below 50%. These things are literally faster than bullets. I think they outrun the pressure front of explosives.
If they can also throw rocks at 100x the speed of humans, that’s something that could disable a tank in a single hit. I don’t think you appreciate how insanely powerful a hyperchimp is.
Average Human Reading Speed:238–260 WPM (about 5 tokens per second), based on Marc Brysbaert’s reading meta-analysis. [1]
LLM Generation Speed (Output/Decoding):500 to 3,000+ WPM (20 to 100+ tokens per second), depending on hardware, model size, and hosting infrastructure. [1]
LLM Input Processing (Prefill):10,000+ WPM equivalent (hundreds to thousands of tokens per second) when ingesting long contexts into the KV cache. [1]
I’m pretty sure a chimp moving at 2000 kph is a straight-up hypersonic missile, can run across the ocean, and can sink battleships through kamikaze attacks. I think the chances of defending against 800 billion of them are effectively zero. I think the chances of defending against 80 million of them is still below 50%. These things are literally faster than bullets. I think they outrun the pressure front of explosives.
If they can also throw rocks at 100x the speed of humans, that’s something that could disable a tank in a single hit. I don’t think you appreciate how insanely powerful a hyperchimp is.
Human vs. LLM Speeds
Average Human Reading Speed: 238–260 WPM (about 5 tokens per second), based on Marc Brysbaert’s reading meta-analysis. [1]
LLM Generation Speed (Output/Decoding): 500 to 3,000+ WPM (20 to 100+ tokens per second), depending on hardware, model size, and hosting infrastructure. [1]
LLM Input Processing (Prefill): 10,000+ WPM equivalent (hundreds to thousands of tokens per second) when ingesting long contexts into the KV cache. [1]
From Google AI preview