Damn those goalposts are slippery.

Ah, solipsism. Motivating humanity since... never.

Hahahahahahahahahahahahaha.... You think Trump is fixing this?

Nope, as per usual this will be ignored if you make a generous tithe... erm... donation... erm... gratuity in advance to the Trumpublican party.

It's a law that won't ever be enforced... unless you're a company the tangerine thundercunt doesn't like.

The end game is not to protect US workers, but strip what few rights they have down so that they're as cheap as the Indian workers.

If you were worried about being chased by kill bots, go and watch some videos from drone operators in Ukraine. Robots don't need feet for that job.

This is all moot because it's false that if you use AI you cannot gain copyright on the work. I literally hold a copyright registered with the US copyright office (I registered with them, despite not being a US citizen, because they're precedent-setting), fully disclosing the use of AI in the process, and directly speaking about the matter with a copyright examiner.

What the standard is is that raw, unfiltered outputs are not copyrightable (and even then, there's wiggle room; the argument put forward by the copyright office was "based on their current understanding" (as of several years ago) and presumed very minimal control by the user over the outputs (which was actually already obsolete by the time they put it out, but that's nitpicking)). But the human creative action you take with those outputs can cause the resultant product to be copyrightable. This can be things like sample mixing, mastering, adding vocals, etc, but can also even just be the selection process itself. Yes, assemblage, selection, curation, etc are all potentially copyrightable acts.

In my case, while the samples were (overwhelmingly) AI, the whole project was weeks of work, involving hundreds of generations, track splitting and reassembling, things down to the level of editing individual phonemes (or for example in one part, stripping the vocals and instruments from a sample down to just the residual "other" channel, throwing it into reverse, and then piling on progressively more reverb and volume up to a sudden cutoff to create a tension-point transition). No issues whatoever registering the copyright on it. I'm sure you could do far less and still have a copyrightable work.

I think people need to keep in mind that marketability (aka enjoyability), talent, and effort are three independent axes. You can be talented at one or more aspects of music production, a genuine skill (play a guitar, sing, etc), but put forth either high or low effort, and make good or terrible music, all independently. You can put forth a lot of effort, but you may or may not be talented, and it may or may not be good. You may make a great enjoyable marketable track, but may or may not have notable talents, and may or may not have put in a lot of effort.

In general: I judge how much I want to listen to it by its enjoyability; I attribute how much the author deserves credit / how much it's "art" by how much non-rote effort they put in; and I value the artist's skill based on their demonstrable talent. All of this independent of what specific tools were used. That said, knowledge of certain facts may colour one's enjoyability of a track. If you hate AI and know / suspect it's AI, that'll strongly colour your enjoyability of it. Or if you know the artist is a bad person or whatnot, that again can colour your enjoyability of a track that you'd otherwise enjoy in a vacuum.

One thing I've been thinking recently is being in the AI trade but only with high seniority, not common stock. So if there is a "pop", but the underlying business remains sustainable, the high seniority investors end up with the assets and make a mint when the market returns to balance, whereas the stockholders are the ones who suffer. This could mean a mix of convertible bonds / convertible ETFs, preferred shares, senior corporate debt, physical infrastructure (power suppliers, REITs, etc), BDCs and private credit vehicles, etc. Or possibly even common stock in some of the diversified giants (Google, Microsoft, etc), who - while they'd take quite a temporary hit in a crash - would survive and then buy up all the distressed players.

Oh, shoot, I forgot my "Claude-isms" ;)

I mean, Leopold was literally fired from OpenAI after one year.

(Though I would hardly call Altman "a genius". He's a rather sociopathic VC guy who happened to be in the right place at the right time)

I'm holding out for so many things.

New fabs are finally being built but they take like 3-5 years, so that's not going to solve anything any time soon :P

Situational Awareness is a "hedge" fund that did the opposite of hedging - they made a bunch of leveraged bets that were all linked to each other in typical market movements. It was headed by Leopold Aschenbrenner, a guy just a couple years out of college, whose employment career had been very brief stints at the FTX crypto exchange firm (until it collapsed) and at OpenAI (until he was fired a year later over an alleged information leak). No financial management experience whatsoever. But he was into Effective Altruism, writing AI whitepapers, all that sort of stuff that Silicon Valley tech bros like, and so when he started a hedge fund, $45B was quickly pumped into it.

Nah, this isn't a sort of bubble-popping event. It's a tangential player in the stock market, not some key participant in operations or loans in the AI ecosystem. My main concern: inference IS profitable. Very. But the heavy leverage of the industry is also very real, and can very much still spread like a contagion. And a likely trigger for that is inflation, triggered by trade wars and the ongoing Hormuz and Ukraine conflicts (or worse, new ones added to the list!). One, inflation directly increases their costs, but two, it causes central banks to raise rates. This starves companies of capital (both loans and equity), incl. to refinance existing liabilities, while also hindering income (e.g. new orders get put off or cancelled). It can easily flip a leveraged company into insolvency, and then that can ripple if there's nothing to stop it.

An investment opportunity can be brilliant, a massive world-changing field with huge margins, but still be a terrible investment. One, because the companies you invest in need to survive continuously and not get blipped out by an adverse market event until they have more ability to withstand them. And two, also, because there's a problem where investors don't merely value the whole market as if it has high odds of success, but value the specific player they're invested in with high confidence as if it will dominate said market. Which, obviously, all players combined cannot do.

The AC is incorrect. LLMs do it because their training data does it. Their training data includes lots of literature, scholarly humanities writing, journalism and ad copy. Naturally it sounds pretentious.

t is also why AI cannot replace any of the dangerous gross jobs people actually want replaced

https://renxhomes.ca/promise-r...

https://www.hitachicm.com/eu/e...

https://www.deere.ca/en/autono...

https://ntwist.com/blog/autono...

https://getsomatic.com/

https://blog.robozaps.com/b/hu...

It can, and is. Interaction with the real world is harder and takes longer because we don't have giant piles of training data sitting around ready to go like we do for images and text. There are also safety concerns and cost barriers that aren't there with things like text.

No post processing needed. LLMs sound like they do because that style was prominent in their training data and was scored highly by their trainers. If you ask most of the language models not to use excessive punctuation, lists, headings, polish your knob, and write at a grade six level, they generally sound reasonably human.

If you're watching some random thing on YouTube you should be wondering that regardless of whether it sounds like it was written by an LLM or not.