It's really about (a) sending a message that we don't support Musk or other fascists and (b) discouraging other people from buying them.
It's true that some people might have Teslas without having monetarily support Tesla somehow, but not very many, and if they got their Tesla for free then they aren't really losing anything.
To that end, vandalizing Cybertrucks would send the clearest message, they're the most obviously Musk thing. If enough Cybertrucks are vandalized, the media will report on it, and people will get the point. It would hurt Tesla's sales, Tesla's stock, and Musk's image.
This is just theoretical mind you. I'm not advising you to vandalize anything, since that would be illegal.
I know you are agreeing with me, but it being a "series of multiplications" is not terribly informative, that's basically a given. The question is how many flops, and how efficient are flops.
Obviously it depends on your GPU. A crypto mine, you'll leave it running 24/7. On a recent macbook, an LLM will run at several tokens per second, so yeah for long responses it could take more than a minute. But most people aren't going to be running such an LLM for hours on end. Even if they do -- big deal, it's a single GPU, that's negligible compared to running your dishwasher, using your oven, or heating your house.
I don't have a source for that, but the most that any locally-run program can cost in terms of power is basically the sum of a few things: maxed-out gpu usage, maxed-out cpu usage, maxed-out disk access. GPU is by far the most power-consuming of these things, and modern video games make essentially the most possible use of the GPU that they can get away with.
Running an LLM locally can at most max out usage of the GPU, putting it in the same ballpark as a video game. Typical usage of an LLM is to run it for a few seconds and then submit another query, so it's not running 100% of the time during typical usage, unlike a video game (where it remains open and active the whole time, GPU usage dips only when you're in a menu for instance.)
Data centers drain lots of power by running a very large number of machines at the same time.
This I can believe tbh. It's a very useful tool in the hands of an expert. Otherwise it's like giving a chimp a gun.
Maybe this is why I am surprised at people's hatred of ChatGPT. It's borne of misuse of a tool for experts, like newcomers struggling with a C++ compiler error.
LLMs are basically just good pattern matchers. But just like how A* search can find a better path than a human can by breaking the problem down into simple steps, so too can an LLM make progress on an unsolved problem if it's used properly and combined with a formal reasoning engine.
I'm going to be real with you: the big insight behind almost all new mathematical ideas is based on the math that came before. Nothing is truly original the way AI detractors seem to believe.
By "does some reasoning steps," OpenAI presumably are just invoking the LLM iteratively so that it can review its own output before providing a final answer. It's not a new idea.
I do agree that grad students don't exactly live in luxury, and frequently develop mental health crises. But their contributions and insight are what power their labs. Profs often have to spend so much time teaching and chasing grants that they can't do much real research. Academia overall is in a sad state.
But Tao is a superstar, and a charismatic blogger. I'd be disappointed to learn he mistreats his grad students. (I don't know if he even has any tbh)
The constitution is like the laws of physics; god will enforce it. If not god then perhaps ligma.