[vlovich123]

> A few days earlier I had got an email from a professor in the maths department here at Imperial, expressing surprise that some of our graduate students were paying $200 per month to access models such as Sol and Fable. He said that he thought that these people were crazy. I did not immediately respond. But after meeting with Andrew I emailed the professor back and told him that in my opinion, any PhD student who was not paying $200 per month to access these tools was crazy. In fact during the workshop I learnt from Harvard PhD student Bryan Wang that Harvard were already giving free Fable access to all PhD students, post-docs and faculty at Harvard.

Yeah, given how much it accelerates grad students to produce meaningful output more quickly, why wouldn’t you make an investment of $2400/student/year. Seems like pennies overall.

[adw]

The living-costs stipend for an EPSRC PhD student is around £20k so it's about ten percent of that... big commitment for a student to make!

[vlovich123]

Which is why the school should be covering it.

[adw]

They’re skint too. It’s something you would really like the research council to take on.

[evenhash]

It would be better to just give the students the money and let them spend it as they need.

If I were a student living on a measly $1600/month I would be livid if the school gave me a $200 raise in AI credits, instead of money to buy groceries or pay rent.

[vlovich123]

Cash might count as taxable income whereas this might just be part of your student account that there’s a deal on. In other words this isn’t fungible for a cash benefit - it’s either this or nothing not this or $200 in your pocket.

And while agency in finances is important, if this helps you finish your schooling faster, I suspect you might not care how you get access to a frontier AI model and having 10% of a theoretical $1800/mo carved out isn’t a huge deal.

[Diogenesian]

Many graduate students view themselves as ethical beings, not machines that "produce meaningful output," and everybody here knows (useful) LLMs are indefensibly evil because of stolen training data and enormous environmental impact.

[noslenwerdna]

This is a very close minded definition of evil. What is the threshold of environmental impact before something is evil and its use indefensible?

What level of copyright violation will send us to hell?

[Diogenesian]

I didn't give a definition of evil, so "close-minded definition" is just a dishonest way of expressing that you subjectively disagree with me.

Likewise with trying to make me judge an objective threshold for pollution. It really should be that any polluter needs to morally justify their actions. I find "mostly illusory productivity improvements in white-collar employment" to be an especially indefensible reason for firing up new natural gas generators. Let alone the real motivation being "billionaires want more money." The level of pollution from training and deploying generative AI is simply evil.

And your last question is just pure cynicism. The real sin you're committing here is contemptuously dismissing ethical concerns out of hand.

I assume you use LLMs. I don't. It truly seems like using LLMs makes people stupider and more unethical. Some cognitive work should not be outsourced, especially not to a mindless stochastic parrot.

[noslenwerdna]

Obviously I mean the definition of evil implied by your statement that they are indefensibly evil...

Again, what level of copyright violation is evil? Downloading music without paying for it? Apparently using images/text that artists have made public is evil, so I'm curious what the bar is here for evil.

Using electricity to improve white collar efficiency is also evil. Good to know

[dTal]

Thank you for using the phrase "stochastic parrot". I only request that you use it at the beginning of your long comments, rather than the end. It saves time.

[Diogenesian]

"LLMs are stochastic parrots" and "stochastic parroting is a powerful medium for computation" are not contradictory statements. [Lisp is a mindless symbolic list processor.] The inability of certain people to accept this speaks to a decades-old contempt for scientific thinking in AI.

https://news.ycombinator.com/item?id=48981271

[JCharante]

I wonder what the tipping point is where machines require less energy than humans to accomplish the same tasks.