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Woodworking recommendations shall include:

“If I Had a Hammer”

“Sledgehammer”—Peter Gabriel

Anything by The Carpenters

Any works by Woody Guthrie

Hymns about Jesus and St. Joseph

Lumber Capital Log Yard

Anything by Nine Inch Nails

Anything by the Sandpipers

“Turn, Turn, Turn”

“Dust in the Wind” by Kansas

Anything by Dusty Springfield

Anything by MC Hammer

Original Motion Picture Soundtrack, “Saw” horror franchise

Anything by Level 42

https://youtu.be/dQw4w9WgXcQ?si=sTUKhRXXiylavwIm

Anything by 1-hit wonder The Nails and/or powerviolence band NAILS

“Morning Wood” by Beavis & Butt-Head

“The Lumberjack Song” by Monty Python

> how is AI (or a human for that matter) supposed to know what “woodworking-appropriate music is”?

It doesn't, but you'll believe it is because that's what you asked for. It's not like you have a solid test for what it is yourself

Guaranteed it would be unable to avoid searching for and selecting songs that specifically mention wood, woodworking, the shop, etc. It's like when you tell it to write something and give it a "vibe" or "mood" word wishing it could just give tone to the generated text, but instead it incorporates it literally.

As a person who built and uses this feature several times a week, no, it never does this. It just plays a lot of Tom Petty.

Now, see, when AI does something like this, we call that "hallucination".

Thomas explained what he means in a sibling comment an hour before yours.

Because I played a bunch of music while doing woodworking stuff and asked for more like that. Things like this are easy with a simple agent loop. It's not picking random music out of the sky; it's working from my Apple Music library (and then expanding on it from the Apple Music catalog).

>I played a bunch of music while doing woodworking stuff and asked for more like that.

I would probably think about doing a little workspace sharing and ask for more live musicians to come in and do some serious woodshedding themselves ;)

I know some that are getting that buzz-saw sound out of their instruments fairly repetitively already, and there's no place to go but up :)

I'm a terrible woodworker (that's what makes it fun) and if I had a musician in our basement shop there is a very high likelihood I would kill them, or at least seriously fuck up their instrument, when I manage to shoot a wooden spear across the room because of miter saw kickback.

> Things like this are easy with a simple agent loop.

To be fair, they’re also easy (trivial, even) without one. It’s not like “play more music like this” is something we ever needed AI for.

> It’s not like “play more music like this” is something we ever needed AI for.

Borderline off-topic, but I love how fast the goal post moves. A decade or two ago "Similar music to this" was definitively in the realm of AI/ML, now it's some full-stack dev's afternoon to implement.

I don‘t think someone disputes that this is in the realm of AI/ML. I just think its questionable if this kind of usecase is genuinely something were an LLM is necessary or outshines the more traditional approaches

What are you even talking about? No, of course music recommendation systems had nothing to do with LLMs two decades ago (which is obviously the crux of the discussion), that is insane. And no one has said anything about a “full-stack dev's afternoon”, I’ll kindly ask that you don’t straw man. No goal posts are moving, that fallacy does not mean “argument I don’t like or understand”. What happened to good faith discussion? It’s ever more common on HN that someone will just invent some argument in their head, attack that, then act like they are the arbiter of reason when they couldn’t even understand the argument. That’s not interesting. Engage with what was said.

> What are you even talking about? No, of course music recommendation systems had nothing to do with LLMs two decades ago (which is obviously the crux of the discussion), that is insane.

Of course not, but just some years ago, when people talked about "AI" in ML circles, they weren't exclusively talking about LLMs, which you seemed to have automatically and exclusively associated "AI" with. It's much larger than just LLMs, although the ecosystem is flooded with LLMs at the moment. I thought this very movement, where tons of people, not just you, have this "AI === LLMs" association, when again, it used to not be so.

So, in other words, you read what one person (you’re not talking to some vague notion of “people” in the past) wrote, associated it with other arguments you’ve seen (and quite possibly misinterpreted) before and decided to lump everything together and answer those different arguments and be kind of snarky about it.

That attitude is exactly why online (and offline) discourse has gone in the gutter. Instead of addressing what was said and understanding nuance, you instead took the comment, labeled it in a preconceived box in your head, then attacked that group instead of engaging in good faith with the person you were talking to.

And by the way, I’m very much aware of the difference between AI and LLM, but whether you like it or not the terms are conflated today and being pedantic about it is a losing battle. In this case it was patently obvious what was meant. You’re (presumably) not an automaton and are thus (presumably) capable of understanding the difference, meaning you are definitely able to choose to steel man instead of straw manning.

> than attacked that group instead

What on earth are you on about?

Take a breath, I'm not arguing for/against anything at all, I conceded myself it's "borderline off-topic", you don't have to take it as I'm trying to challenge anyone's worldview or anything, it's basically an offhand observation.

> man instead of straw manning.

You may not actually understand what a "straw man" is, as I haven't even attempted to refute or engage in any argumentation at all.

Anyway, clearly a fruitless conversation to continue, I'm not sure who you're arguing against/for here, I didn't intended to even try to argue against/for anything here, so I'm just gonna peace out. Hope you enjoy the rest of your Saturday as much as I've enjoyed mine so far!

Come on, if you respond to a comment then expand on it to explain why you made it, hiding behind it being “borderline off-topic” and an “offhand observation” feels disingenuous. Can you understand that?

Here’s a silly example: Imagine you had made a comment about something different on a different thread. Then someone responds to you by saying “borderline off-topic, but I find some comments on HN about this subject to be really stupid”. Would you not be justified in thinking that the comment responding to yours was a response to you?

Maybe you really did mean nothing by it, but are you able to understand how every choice you made contradicts that, even if inadvertently?

> Anyway, clearly a fruitless conversation to continue

Are you also able to understand how this type of high-ground dismissal makes it worse?

> Hope you enjoy the rest of your Saturday

Thank you. You too. Genuinely.

Oh, you two!

The true power of LLM powered interfaces is the malleability of the whole thing. Sure you can write traditional software to handle “more like this”, but how hard would it be to handle “more like this but uptempo”, “more like this but not the same artist”, ad infinitum?

I have a bunch of skills Ive created for random work that have “predefined interfaces” like a single url. I very frequently trigger these skills with freetext prompts instead and get all the intelligence of the skill while bypassing what it was actually designed for. This aspect of malleable API is extremely powerful and is probably the only reason I keep AI in the loop of some of my custom software vs removing it and avoiding the cost/nondeterminism.

> we already have recommender algorithms, why do we need to get a LLM involved

and we had autocomplete for coding (IntelliSense), why do we need to get LLM involved?

LLMs are at a whole different level than recommender algorithms

tried it with GPT:

> A steady mix of instrumental grooves, classic rock, and bluegrass—styles commonly favored in woodshops.

Green Onions - Booker T. & the M.G.’s

Up Around the Bend - Creedence Clearwater Revival

Jessica - The Allman Brothers Band

Long Train Runnin - The Doobie Brothers

Honey on My Tongue - Steep Canyon Rangers

2 of those acts are in my woodworking rotation.

Recommendation algorithms are, frankly, weird as a user. Something watches your tiny interactions and, with zero concept of anything happening, gets surprisingly good at predicting your next interactions.

It’d be like eating and having an alien with no concept of food or taste staring at how much your facial muscles change and making notes. Then recommending places to you based on the other people they’ve been studying.

> how is AI (or a human for that matter) supposed to know what “woodworking-appropriate music is”?

Well someone is going to be concentrating, but it’s a long period, with loud activity. maybe you’d guess at decently active music, not relying on careful complex listening, probably fairly steady rather than sudden dramatic changes.

Maybe it could save previous playlists and what you’ve said about them, or ask questions like “so like, really calm or techno or what?”. Adding just a bit of common sense makes an enormous difference with this kind of thing.

They are weird. But stuff like this solves one of my great challenges in life, which is that I've got many tens of thousands of songs in my library but only manage to hear tiny repetitive epicycles of them. I don't want a tight rotation of the same 200 songs, and I don't literally want to randomly walk my whole library, and I don't want to allocate lots of time curating exactly what I'm going to listen to. LLMs are great at this.

(Actually I totally do want to allocate lots of time curating exactly what I'm going to listen to, but laying out playlists is its own hobby, and woodworking time is for making wood shoot across my basement when I pinch the saw blade, not for making mixtapes.)

Oh I mean LLMs are the opposite, they’re not the same blind optimisation thing weirdly watching you with no core understanding. They’re great for this kind of thing.