A lot of people thought the same thing with everything going from analog -> digital. Or heck, even learning an instrument when MIDI was first introduced.
Even before generative AI, there is a long-going debate in audio circles around simulated guitar amplifiers. The truth is, the simulations of them have gotten so insanely good that now one could simply purchase an all-in-one pedalboard and have basically all of guitar history at your toes.
My rule-of-thumb is this: "does this tool I'm using in particular take away from the authenticity of my performance or songwriting?" Example: I am very keen on performing vocals and guitar at the same time, and I don't have an expensive studio setup, and my office has background noise. I use these tools, and yes even some open source AI ones, 1) remove background noise of the individual tracks and 2) do a final master against a recording I want to target (using something like Matchering or similar [0]). It still sounds like me, my voice isn't perfect, my beat isn't consistent, but it sounds like I rented some studio space. So for me it was a cost-saving measure.
>> one could simply purchase an all-in-one pedalboard and have basically all of guitar history at your toes
And this is actually a problem. Great art usually comes from constraints, real or artificial. These things are a lot of fun to tinker with (a really fun hobby) but one amp, one guitar, and a small number of effects pedals will probably lead to you actually make more and better stuff.
I have an all-in-one amp / pedalboard and it's just more practical, even though all I do is just pick an amp, plug in my guitar and play. They take up less space and cost less money in the long run if you actually do want to use many pedals.
I get what you're saying but in general this specific case I think the all-in-ones win for most people.
This was definitely true for me, which is why I write everything acoustically and ensure the song is "good" before going in my later age. If I want a specific effect, I then google what pedals were used in a particular song or artist, then I try to recreate the chain, and then tinker with that on top.
Ultimately I spent so much of my time worrying about "what crazy expensive equipment should I buy" when I was younger and more into this stuff, and I should have simply just played my shitty instruments and recorded on my shitty equipment. That's on me, but I also find it empowering as an artist that I can clean up my recording in the way that replaces my need for expensive equipment while maintaining (in my humble opinion) a sense of authenticity of my performance. I agree there may be too many knobs, but finding the knobs that I want has never been easier and I would rather live in the now than in the past.
> A lot of people thought the same thing with everything going from analog -> digital.
A lot of people were right. Music gear lead heavily back into analog after the initial analog to digital transition. I started out using computers exclusively. When I purchased my first analog synth, I couldn't believe how much better it sounded than my VST's. It's hard to quantify exactly why, but my ears lit up the second I started using it.
In terms of amp modeling software, some of it is indeed very impressive. But, tends to fall apart when you need to tweak parameters. I assume this has to do with the capture process. But, if you are happy to use stock patches, it's basically an amp replacement.
Even before generative AI, there is a long-going debate in audio circles around simulated guitar amplifiers. The truth is, the simulations of them have gotten so insanely good that now one could simply purchase an all-in-one pedalboard and have basically all of guitar history at your toes.
My rule-of-thumb is this: "does this tool I'm using in particular take away from the authenticity of my performance or songwriting?" Example: I am very keen on performing vocals and guitar at the same time, and I don't have an expensive studio setup, and my office has background noise. I use these tools, and yes even some open source AI ones, 1) remove background noise of the individual tracks and 2) do a final master against a recording I want to target (using something like Matchering or similar [0]). It still sounds like me, my voice isn't perfect, my beat isn't consistent, but it sounds like I rented some studio space. So for me it was a cost-saving measure.
[0] https://github.com/sergree/matchering