And Altavista was slow! Google was so much faster, it felt way nicer to use. But LLMs are slow; forcing my google queries through an LLM is destroying that speed.
It remains to be seen what they actually end up selling for, but it seems like Slate intend to offer a 200 hp motor, 52 kWh battery ... and the rest of a whole vehicle for $28k. That makes $27k for this "eCrate" package (which, granted, comes with 14 kWh more battery) seem like an absolutely terrible price.
Sometimes I wonder if the throat-clearing is an indispensable part of getting to the "good bits" that follow. Like, do those extra tokens give it more "room to think" even if they're basically meaningless in themselves?
It seems to me that the distinction becomes irrelevant as soon as you connect inputs and outputs to the real world. You wouldn't say that a 737 autopilot can never, ever fly a real jet and yet it behaves exactly the same whether it's up in the sky or hooked up to recorded/simulated signals on a test bench.
I'm sure it's fine you do it properly ([1] for example). The issue here was the utter lack of engineering, not the specific manufacturing technique (although those do seem to be highly correlated, due to low-end 3D printing having become very cheap and easy).
The extra fun thing about this is that eval has different semantics if it's assigned to a different name, in order to allow JavaScript implementations to apply extra optimizations to code that doesn't call a function literally named "eval": https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...
The "scraping helped slow it down" theory makes no sense to me. What do you think has a higher coefficient of friction - tire rubber on asphalt, metal on asphalt, or metal on metal?