thrwayaistartup

Does a picture of a humming bird lack insight? Does collage art lack insight? Do remixes lack insight? Does mass-produced formulaic pop music lack insight?

Maybe. Or maybe some artists enjoy those creative processes and some audiences enjoy the output. Maybe oil painters who critique photography, and photographers who critique collages, and musicians who critique mash-ups, and DJs who critique modern production studios, and, yes, artists who critique the use of AI models in creative processes, are all just being pretentious assholes.

(It is possible I am simply misunderstand Cave. I take most of his writing to be artistic prose. It's possible that these are sincere metaphysics and that Nick Cave does literally believe in some sort of ur-religious "essential and unconscious human spirit underpinning our existence". In which case I think he's got a nutty religion and consider the fact that AI is an existential threat to that religion mostly a net good for humanity.)

He is asserting the existence of an "unconscious human spirit", asserting that ChatGPT "is fast-tracking the commodification of the human spirit by mechanising the imagination", and that we should fight against AI as we would fight against genocide: "just as we would fight any existential evil, we should fight it tooth and nail, for we are fighting for the very soul of the world."

Incidentally, I agree with the importance of struggle and soul-work. I agree with the general valence of the lament, but come away with a very different call to action. In particular: I just don't think I have the right to impose luddism on the rest of the world for my particular niche while benefiting lavishly from the rest of the world's alienation form their much more essential labor.

To me, it's the ravings of an angry, arrogant, and entitled elitist who fears being dethroned from his comfortable luxury and refined status. And a hilariously hyperbolic one at that. Of all the actual evils I would write something like this about, AI Art probably isn't even in the top 1,000,000. Can you imagine looking at the world today and writing that last paragraph? My god.

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Quotes:

> ChatGPT rejects any notions of creative struggle, that our endeavours animate and nurture our lives giving them depth and meaning. It rejects that there is a collective, essential and unconscious human spirit underpinning our existence, connecting us all through our mutual striving.

> ChatGPT is fast-tracking the commodification of the human spirit by mechanising the imagination. It renders our participation in the act of creation as valueless and unnecessary. That ‘songwriter ‘you were talking to, Leon, who is using ChatGPT to write ‘his’ lyrics because it is ‘faster and easier ,’is participating in this erosion of the world’s soul and the spirit of humanity itself and, to put it politely, should fucking desist if he wants to continue calling himself a songwriter.

> This impulse – the creative dance – that is now being so cynically undermined, must be defended at all costs, and just as we would fight any existential evil, we should fight it tooth and nail, for we are fighting for the very soul of the world.

I have to admit not quite sure what you mean, and I do admit full guilt in starting us down the path of "mixed analogies" :). I'll try my best, though.

> Or past a certain point, the results of discovering improved health and ecological outcomes will become inextricably linked with discovering new technologies that cause conflict? What actually drives such a process?

I do think with respect to life-sustaining things -- medicine, pharma, food, shelter, water, energy -- that a combination of specialization and automation is necessary to increase the collective standard of living, and that labor alienation stems from a combination of specialization and automation.

Where I struggle is coming up with an affirmative argument that an artist should benefit from automation of medicine or farming, but that an alienated lab tech or food factory worker should not benefit from automated art.

Another way to look at this is: the less you pay for art-as-entertainment, the more resources you have to buy free time to produce your soul-work (whatever that may mean to you).

Hannah Höch would like a word.

Actually, I agree. I think Nick Cave is right about this. I do think this sort of alienation has a cost.

But that doesn't mean that there is any remotely moral case for undoing the green revolution and allowing billions to starve. And it does not mean that the machines which feed those billions of people who might otherwise starve are somehow the root cause of a decline of humanity. In fact, quite the opposite.

And this is the paradox: our alienation from agricultural work is precisely what enables our very existence.

My main observation is that there is a way out of this paradox. As it turns out, you can go out grow some food in a garden, or write a song, or paint a picture, even if that work is commodified and there is no paycheck. The commodification and automation of those industries does not prevent one from engaging in them as soul-work.

The teacher who plays in a band in his garage is no different -- from a "soul of humanity" perspective -- than Nick Cave. But Nick Cave's implicit argument argument demands that he is different, and not from an economic perspective, but from a very soul of humanity perspective. It's extraordinarily off-putting to me in that sense.

Of course, engaging in art as hobby instead of for pay does require free time and a share of returns on our societal bargain. On that note: elites like Nick Cave should be spearheading serious conversations about political economics and labor economics, instead of lamenting the loss of their extraordinarily unique status.

It's a wonderful thing to find meaning in one's work, and for the things in which one finds meaning to be well-compensated. But it is no birthright. Contrary to Nick Cave's view, I can absolutely assure you that non-artists in HR departments and nursing stations and factory floors and classrooms often live full happy human inner lives. Those lives are of their own making and do not derive from the artiste class's output.

Manual production of high-quality clothes, tables, and glassware used to be the norm. Generations of people found meaning in these crafts before the industrial revolution changed the economics. People still do these things, only in rare cases as their primary way of making a living. Most art does not sustain developed world middle class existence. Most art is hobby. And that's okay.

The creation of software and AI systems is itself a form of craft-work and soul-work, which many engineers and scientists relate to the same way that Nick Cave relates to music. It is unclear to me why Nick Cave's striving is more important than the striving of engineers and scientists, or why his feeling of what humanity is, is more important than theirs.

If you never want an exit then probably doesn't matter.

The NYT case could take years. In the meantime OAI could choose to go after ToS violators.

The legal system can accommodate more than one unresolved court case at a time. We don't like put a semaphore on related cases or anything like that. (Or, sometimes we do, but guess who you need to hire for many many billable hours to make that happen in your case?).

So, the legal system can accommodate the NYT case against OAI and an OAI case against the author. The operative question is: can the author's pocketbook also accommodate?

(Or, more to the point, can the author accommodate losing access to gpt4? What happens when he wants to launch a new feature or pivot to a new product?)

If I were the author I'd never do this because I would want an exit and this strategy + twitter thread wildly complicates any potential exit.

Even though I don't think there is anything particularly morally problematic here (I'm an information freedom maximalist).

2024 will be the year of synthetic data. 2025 will be the year of "you know you can use your own brain and type out 100 datapoints faster and cheaper than generating and filtering assloads of synthetic data, right?"

Maybe we can even skip 2024 :)

> (e) use Output (as defined below) to develop any artificial intelligence models that compete with our products and services. However, you can use Output to (i) develop artificial intelligence models primarily intended to categorize, classify, or organize data (e.g., embeddings or classifiers), as long as such models are not distributed or made commercially available to third parties and (ii) fine tune models provided as part of our Services

I have two issues with those terms:

1. I think that eventually US courts will determine one of two things: that OpenAI et al are guilty of massive infringement, or that these sorts of restrictive terms aren't enforceable. The need that these companies are trying to treat with terms on output seems unlikely to work out in the end. But we'll see.

2. Even if the terms are enforcable, the human review step in the tweet seems like it's make OpenAI's threading-the-needle position here even more fucking difficult to be taken seriously by any jury or judge.

However, enforcing the terms seems real damn hard in the case of small businesses... as long as you're not stupid enough to admit to violating them in a twitter thread, of course.

I think the author is probably safe from legal action for now because I don't think OpenAI is particularly eager to test the enforcability of their terms. And even if they are, doing so in this case is super high risk and super low reward. Still, I wouldn't test it by openly admitting to ToS violation like this. At the very least seems like a good way to get cut off from OAI APIs.

[1] https://openai.com/policies/business-terms

1. I'm with McKenzie on the coworkers aspect of the dialog. More separation from coworkers is better. In the Good Times (2013-2019,2021) it seems "right" to trade some comp for familiarity and good work vibes, and almost... inhuman... not to. But in the Bad Times you're reminded that an Excel formula could cost you not just your job but also a big chunk of your personal social network. Diversification is good.

2. I now realize what both sides of this are getting at is basically: "how to progress from Junior/Mid Engineer to something after that". There are many paths. The conclusion of the article is good, in that respect. Also: you can just stay a Mid/Senior Engineer. That's okay.

3. Call yourself whatever you want/need to stay employable. Be a good colleague/person. Work is work.

Only a very small subset of industry cares about academic publishing, and even within that subset it's only a fraction of groups at a fraction of corps that consider publishing a primary or even secondary objective.

The groups that do care about those things can be good gigs, but are generally not the place in the company you want to be anyways, unless you can get in and out (for good) in <10 years. If you can do something that actually impacts the business -- that is actually useful to other humans -- no one gives a shit about h-indices or kaggle scores. And you'll be better compensated anyways.

Teaching is great, so there's that. But literally every company will let your ad junct, and Professor of Practice usually pays more than 20% of a faculty salary. You can supervise PhD students as interns or by taking a courtesy affiliation (and often even have more impact on those students than their overworked and under-engaged advisors). And university classroom teaching in the US now looks a lot more like 90s/mid-naughts high school teaching.

Government contracting sucks, and the academic variety is not any better. I'd literally whether watch paint dry at a military base than contract for DARPA. NSF isn't actually that much better.

Who the fuck wants to be a combination high school teacher and federal government contractor? Saints or sociopaths, and there are a LOT more of the latter than the former in higher ed.

The choice is now between increasingly tenuous/meaningless tenure after 5-10 years and a $500K/year lower bound for 10-12 years. That choice is... not a hard choice for anyone who values intellectual freedom. And the right answer sure as shit isn't the faculty position.

A good 50% of those faculty chasing chasing NeurIPS papers are doing so because at least once before going up for tenure they will apply for positions at big tech. They end up coming on not just non-executive, but often outside of management and at the bottom of the (Top IC)-[1-2] total comp band. If they net an offer they'll usually leave. The major barrier to an offer is usually ego and "is this personal actually humble enough to be useful to other people".

The conspiracy: the manager has an axe to grind that aligns with incumbent auto-makers' business strengths, suggesting that the analysis is debased in one way or another.

The "mind explodes": the manager is talking their book; behind the manager is a team using mountains of data to design messages that optimally push the market in the direction they want. The purpose of the message is not to be logically coherent to nerds on the internet. The point is to convince a few portfolio managers to behave in one way or another, and perhaps also to signal sentiment analysis algos.

> This is is just wrong? Syntax rigour has almost nothing to do with correctness.

1. It's all fine and well to wave your hand at "Syntax rigour", but if your code doesn't even parse then you won't get far toward "correctness". The frustration with having to write code that parses was extremely common among the students I am referring to in my original post -- it seemed incidental and unnecessary. It might be incidental, but at least for now it's definitely not unnecessary.

2. It's not just syntactic rigor. I gave two other examples which are not primarily syntactic trip-ups: understanding nested loops and simple recursion. (This actually makes sense -- how often in undergraduate math do you write a proof that involves multiple interacting inductions? It happens, but isn't a particularly common item in the arsenal. And even when you do, the precise way in which the two inductions proceed is almost always irrelevant to the argument because you don't care about the "runtime" of a proof. So the fact that students toward the end of undergraduate struggle with this isn't particularly surprising.)

Even elementary programming ability demands a type of rigor we'll call "implementation rigor". Understanding how nested loops actually work and why switching the order of two nested loops might result in wildly different runtimes. Understanding that two variables that happen to have the same name and two different points in the program might not be referring to the same piece of memory. Etc.

Mathematical maturity doesn't traditionally emphasize this type of "implementation rigor" -- even a mathematician at the end of their undergraduate studies often won't have a novice programmer's level of "implementation rigor".

I am not quite sure why you are being so defensive on this point. To anyone who has educated both mathematicians and computer scientists, it's a fairly obvious point and plainly observable out in the real world. Going on about curry-howard and other abstract nonsense seems to wildly and radically miss this point.

>> They are conceptually/abstractly rigorous, but in "implementation" are incredibly sloppy.

Maturity in concept-space and the ability to reason abstractly can be achieved without the sort of formal rigor required by far less abstract and much more conceptually simple programming.

I have seen this first hand TAing and tutoring CS1. I regularly had students who put off their required programming course until senior year. As a result, some were well into graduate-level mathematics and at the top of their class but struggled deeply with the rigor required in implementation. Think about, e.g., missing semi-colons at the end of lines, understanding where a variable is defined, understanding how nested loops work, simple recursion, and so on. Consider something as simple as writing a C/Java program that reads lines from a file, parses them according to a simple format, prints out some accumulated value from the process, and handles common errors appropriately. Programming requires a lot more formal rigor than mathematical proof writing.

Maybe that's not true for al (although a 35 minute bike ride with existing fitness gets you a long way surprisingly fast). But one can lift while watching TV. One can do squats while doing laundry. Etc.

Of course, in each case, one of those two options is far less comfortable. For commuting that's particularly true in the winter. But WRT physical fitness, the barrier is almost always "discomfort" and almost never "time".

Universities DO have a monopoly on credentialing. Credentialing, contrary to popular opinion in these parts, is actually a useful function.

Providing education and credentialing is not typically free. You need to acquire physical space, hire teachers, and so on. Education could be at least one order of magnitude less expensive than it is now, and it some cases probably even two orders. Education could also be subsidized 100% for the first N most qualified candidates, at point of use, using tax dollars. But there is no way to make it free.

The average college tuition and fees at four-year schools in 2020-2021 was $19,020.

> and the average student will roll out with between 100k-200k in debt

The average federal student loan debt is $37,338 per borrower.

Like I said, everyone keeps missing the point.

You can see this in high school test scores, in placement exams, in Freshman college performance, and even in new grad hire cohorts.

The autodidact set has realized that they can teach themselves a lot of what they would've learned in coursework at colleges. There are still some elite career pathways where formal education is necessary, but an autodidact who doesn't want to follow one of those career pathways now knows that they can go without.

American colleges provide a useful-if-overpriced service to non-autodidacts, but their product is not ready to deal with students who are YEARS behind in their formal education.

More importantly, though, most judges are not philosophers.

That's super interesting and is news to me. Thanks for sharing. Would you mind linking to relevant statutes or court decisions?

(This isn't a "citation needed" post -- I believe you, and I'm genuinely curious to read more, but can't find anything!)

This is categorically false for both software and movies.

For other media, this ignores the effect of zero-effort copying.

A good example from a recent gig: one of our scientists had a HUGE pile very complicated MATLAB, based on several dissertations worth of novel work on both numerical analysis and highly domain-specific mathematical modeling.

Our software engineers needed to either call into or directly use the MATLAB code. Sometimes changes were necessary. This caused a ton of friction for two reasons. First, our SWEs didn't know much MATLAB. Second, you'd have to read two or three papers of complicated mathematics to even understand what the code was doing prior to changing it, and most of our software engineers topped out with Calculus or maybe a Linear Algebra course. So our engineers were unfamiliar with both the tech stack and also the "knowledge" stack.

In that case, I think it's more accurate to say that the software engineers were unfamiliar with the scientist's tech stack than the other way around. There's no way in hell them or anyone else was going to come anywhere close to correctly rewriting the MATLAB code in any reasonable amount of time. And even if you could, the knowledge stack problem still exists.

You can think of hiring those types of scientists as one-man startups that are bringing in their own tech stack and debt that your existing org has no idea how to integrate. You need to plan that reality into both compensation amount and vesting/earning scheduling.

For compensation, err on the side of "way over asking", since this is going to suck harder than the scientist thinks. They are probably going to want to leave, and you need to be able to get them to stick around. (The dynamics here are similar to a startup founder or exec after a merger, but with slight difference: the scientist's "FU money" is a pretty much guaranteed cushy professor of practice gig.)

For vesting, err on the side of paying out bonuses or RSUs early but with a big vesting cliff 2-4 years out. So they get the cash before it vests. Get 'em hooked and don't let 'em leave until the work is caught.

And definitely bank on them leaving once the first cliff is hit.