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Earlier quoted context omitted.
No, but the students that learn and distill what the professor teaches are not obligated to use that information only how the professor wants them to.
Can the professor refuse to teach some students, or must he teach all comers?
According to openAI's own @deanwball: Even OpenAI isn't buying this distillation talk: https://xcancel.com/deanwball/status/2078133895766114412#m
> distillation: why exactly is it bad? After all, what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models that are themselves being distilled? Who is exactly being wronged here? ... The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service th…
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if the professor took all human knowledge, much of which was explicitly not free, and used it to make a for-profit knowledge machine that extrudes unreliable summaries of that knowledge, then yes, being obligated to teach for free would be a fitting punishment.
According to openAI's own @deanwball: Even OpenAI isn't buying this distillation talk: https://xcancel.com/deanwball/status/2078133895766114412#m
"I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks" what risks?
I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). Confused what this means
Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. Confused again.
One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. I don't understand this at all.
Can someone in the know please use plain layman's terms to explain what this tweet is about?
> distillation: why exactly is it bad? After all, what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models that are themselves being distilled? Who is exactly being wronged here? ... The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service th…
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> distillation: why exactly is it bad? After all, what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models that are themselves being distilled? Who is exactly being wronged here? ... The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service th…
But barring the terms of service from forbidding distillation seems like a tough sell. OpenAI shouldn't be allowed to decide what types of customers it wants and doesn't want?
> distillation: why exactly is it bad? After all, what are large language models but the distillation of all of the knowledge on the open Internet, scraped by the frontier labs and distilled into the models that are themselves being distilled? Who is exactly being wronged here? ... The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service th…
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Public libraries, in this instance, is curated data from all the internet, obtained through not legal means (I don't have a problem with this other than lack of attribution, being copy-left). Just to be clear.
But in answer to your incredibly leading and inaccurate framing... they are required (by their job title) to teach to those who who show up in the classroom, it's not their place to discriminate against anyone/thing (even those like itself (other robots)) that also show up in the classroom.
But you can't teach at a university using only knowledge learned from the library. you need a degree. You are free to teach at the park, where anyone can hear you. public in -> public out.
The U.S. "executive" class is so obsessed with the "exploit" part of the explore/exploit cycle that it's very clear they are prematurely closing advancement. Better a little money and power for them now than a lot of money and power for their country/humanity. This has an element of stochastic improvement so it's hard to predict but the chance of the U.S. "winning" this "race" is pretty bleak. You see this all the ti…
An astute Chinese analyst could reasonably forecast that they had little chance of controlling the AI market due to sovereign trust issues, but would also note that AIs are just software.
When the dust settles the US still won't have factories, and the real value of AI models is still going to be embodying them and getting them to do real, consumer facing work.
Perhaps the most striking thing about the AI boom is how quickly the US abandoned the veneer of local manufacturing in favor of more expensive buildings producing nothing you couldn't make anywhere else on the planet...from imported parts.
> It’s striking the extent to which Claude Code and Codex are proving to be quite sticky; whichever harness you start working with is likely to be the one you stick with, and that figures to be even more the case with non-technical users. My experience has been quite the opposite. I was using Claude Code almost exclusively this winter/spring and swapped to Codex earlier this summer. It took no time whatsoever to swit…