I figured the same, but I did not encounter such exercises, and regardless having the ability to send sysex to my MIDI devices is not required for such a thing.
This site insisted on having write access to my connected MIDI devices, which is a bit concerning as it's not required for what the site actually does.
I've always kind of assumed in the industry when it comes to top 40 music this kind of thing has been in heavy use at big labels since at least the dawn of the millenium when Pro Tools also took off, it's just not been nearly as obvious.
The other replies have explained what's jumping out but I'd agree that without the other surrounding sentences of the article's introduction I'd be inclined to think that quoted sentence by itself might be human. The full text, however, doubles down on the AI-smelling constructions and IMHO almost certainly indicates some AI provenance.
People have been talking about the book on here since it came out; I see no reason to believe people aren't genuinely interested in it. I loved it, personally.
In my experience, the Epic downloader would frequently lead to degraded performance and/or system instability when I'd leave it running; I've never noticed such problems at all with the Steam client.
I accidentally clicked through the explanatory text after the first slide (I was still clicking the pump and didn't realize one more click was going to skip through); I have not been able to get the applet to rewind back to the beginning.
The scare quotes around words that don't warrant it, or are unnecessarily idiosyncratic, are something I get pretty often in response text from Gemini.
I'm really surprised that didn't jump out at more people; I had to get halfway through the comments to the 27th mention of "Department of War" to find the first comment pointing out that using the name is itself a capitulation.
For me there seems to be a listing of configurable settings or something but it only pops up for a single frame after I right-click-drag a component - this seems like a broken mouse interaction.
I strongly suspect there's a major component of this type of experience being that people develop a way of talking to a particular LLM that's very efficient and works well for them with it, but is in many respects non-transferable to rival models. For instance, in my experience, OpenAI models are remarkably worse than Google models in basically any criterion I could imagine; however, I've spent most of my time using the Google ones and it's only during this time that the differences became apparent and, over time, much more pronounced. I would not be surprised at all to learn that people who chose to primarily use Anthropic or OpenAI models during that time had an exactly analogous experience that convinced them their model was the best.
While this is certainly very true, I find coding through an LLM to require far less effort dedicated to this cognitive switching than does writing in some programming language, primarily because I no longer have to load the mental context for converting my high level human instructions to code that a programming environment actually supports. The mental context seems more lightweight and closer to the way I think about the problem when I'm not sitting at the computer actively working on it. If an idea comes to me while I'm away from the computer I can momentarily sit down, type in whatever I just thought of, and get going almost immediately. I think it also saves a huge amount of cognitive load and stress (for me) involved with switching around between different programs and languages, an unfortunate fact of life when dealing with legacy systems.
I just kept scrolling, hoping it would learn from how long I paused over content to read it the way FB's seems to, but it seems you're right, in this case "likes" are required.
It's really a stretch for the article to suggest their gear might not have supported fractional bpm. MIDI itself has always supported it and analog sequencers before that support it even easier. Not to mention external clock sync has been a thing for decades.
All I can really say is that doesn't match my experience. If I fix something that it implemented due to a "misunderstanding" then it usually tends to break it again a few messages later. But I would be the first to say the use of these models is extremely subjective.
For me it just depends. If the response to my prompt shows the model misunderstood something, then I go back and retry the previous prompt again. Otherwise the "wrong ideas" that it comes up with persist in the context and seem to sabotage all future results. The most of this sort of coding I've done was in Google's AI studio, and I often do have a context that spans dozens of messages, but I always rewind if something goes off-track. Basically any time I'm about to make a difficult request, I clone the entire context/app to a new one so I can roll back [cleanly] whenever necessary.