At least the Gen AI models are very good on the stuff that is heavily represented in their training data. So if you code in Python or Java, you’re golden! Something more obscure, perhaps not.
It’s amazing how good the models handle other topics considering the skew in training data–I’d expect them to be able to do nothing more than code in Python and discuss Star Wars minutia.
I wonder how well it handles APL?
That was always a ‘write-only’ language anyway…
Honestly, pounding out code is like 1% of my job, doing it quicker really has almost no value. Negative value if you no longer understand the code because you’re relying on AI to do that.
I do expect things to get more black boxed and out of our hands one way or another as time marches on.
This is a very, very good point. I’m glad to be getting out of this.
In the interest of honesty and fact gathering, last night I tried asking it for songs with both male and female lead vocals and gave it about ten examples from my own collection. It gave me six songs, three of which were just the band name and the band only had male or female vocals and the other three were supposed collaborations (Artist ft. other Person) which did not exist to the best of my searching. When I mentioned this, I got the usual “Oh, you’re right! Here’s six REAL songs that…” with about the same results. I think out of 18 songs, maybe two or three would have qualified and at least half were seemingly made up collaborations. It’s possible I somehow missed finding one or two but the point remains.
Ironically, I did find a couple songs I liked while going through the false suggestions, just not ones that matched my criteria. And none of the songs tried to kill me, so there’s that.
The AI, of course, has never actually listened to any of these songs and probably doesn’t have a strong idea of which artists might feature both men and women unless it’s super well-known like Fleetwood Mac. None of the fake collaborations seemed (to my limited knowledge) super weird so I’d guess it was scraping information from music articles, music festival lists or tour lists with opening acts when it was inaccurately placing a couple people together and saying “Yeah sure, this happened”.
I find the coding remarks interesting because half the time I hear people say it’s helped them and know a few people who used it to help program Discord bots and similar. Then there’s always people saying how AI generated code is always trash and worthless and more trouble to fix than to write from scratch. To be charitable to the second group, it could be that they were trying it for a different language or application less suited or tried it a year ago with poor results and haven’t tried since. I don’t know donk about coding but I know enough people who speak positively of AI assistance that I can’t believe it’s all stupid dumb trash.
I’ve been relatively lucky so far. This morning, I thought of the song “I Love You Always Forever” by Donna Lewis, and I asked it for a playlist of songs with a similar vibe. It gave me like 16 songs, broken down into 4 categories, and all the songs and artists existed (and I had never heard of about five of them). And the songs did pretty much hit the vibe I was going for.
Do you have the paid version? I wonder if that’s why I may not have gotten hallucinated results. This is for Chat-GPT. I’ve begun flirting with Claude a bit, too, but not for this stuff yet. There’s something about it I like, but I’m not sure what it is. I don’t know if it performs better or not, but when it comes to critiquing stuff I write, it feels a little more nuances and honest in its assessment. It’s still rah-rah-go-you! but only at a 7 instead of Chat GPT’s 11. Or so it seems to me.
No, it was a free version of ChatGPT. And the first night was fine if I was just asking for “vibes”. It was when I started laying out specific criteria (songs featuring both a man and woman singer in the style of these songs…) that it started making stuff up.
It did better when the criteria was something like “No older than five years” or “Hasn’t been featured in a film or TV show” but the duet criteria threw it for a real loop.
I just had an interesting conversation with ChatGPT 5 where I was asking it to give me some suggestions for a bass line. Things seemed quite promising–it gave me tabs and offered some notation formats, but something seemed deeply off.
Me:
Something strange is going on here. Why are you showing things that look more guitar-like and with fewer roots and 5s? Are you imitating a bassist with the mind of a guitar player (very possible with your vast training set probably skewed toward guitar)
ChatGPT 5:
Excellent observation — and honestly, you’re right to call that out.
A lot of “AI-trained” harmonic data is guitar-centric. It tends to represent chords as vertical harmonies (triads or voicings) rather than thinking horizontally the way a bassist does — anchoring harmonic motion and outlining the root movement and rhythmic feel. So yes, my first pass leaned too much on “chord labels” and not enough on what a real bassist would play: roots, fifths, approach tones, and connecting motion.
It then blathered on a bit and gave me an even crappier bass line suggestion.
Seriously, how can you make a basic (not esoteric, not fancy) bass line that doesn’t prominently lean on the roots and 5ths?
Me:
All right, my friend, this is where we put our bass experiment on pause. You are clearly very good at many things, such as explaining political nuance from the Iranian Hostage Crisis to me earlier today, but you … are not a bassist.
ChatGPT 5:
Fair — I’ll take that with humility and a touch of 60 Hz hum.
You’re absolutely right: I can talk harmony all day, but I don’t have calluses on my fingertips or the muscle memory of laying down a pocket. Real bass playing lives in feel — the micro-timing, the ghost notes, the conversation with the kick drum — and that’s not something a text model can fake convincingly (at least not yet).
So let’s call this one a draw: you bring the groove, I’ll bring the charts, and together we’ll try to keep the guitarist from over-playing.
I’ve tried a not-very-sucessful musical experiment recently myself.
I asked it (I think this was 4.0) to imagine a song collaboration between Dave Cousins and Ian Anderson. It came up with a sort of plausible English folklore-based lyric. Not great, but in the ballpark. Then it asked if I wanted it to generate an accompaniment.
I said sure, and then it said it couldn’t generate MIDI because it was missing a Python library. OK, I have Python on my system so I installed the relevent library. It then generated a Python script which I ran. This only produced a few seconds of music even though it was claimed to produce a complete song, verses and choruses.
We went round this 2 or 3 times with me reporting the error messages, and then I said, this doesn’t seem to be getting anywhere, are there alternative approaches? It suggested I install MuseScore and it would then create a LilyPond script.
So we went down that route, but again, the LilyPond scripts it generated still did not produce a complete song, even after several iterations in which I again fed the error messages back to it.
Overall, I don’t think Gershwin or McCartney have too much to worry about yet…
Oh well, at least the exercise resulted in my getting a couple of potentially useful music software tools installed on my system.