Thoughts About "AI" (Winter 2024 Edition) - AKA: No, I do NOT want to have to "talk" to your "chatbot"

I briefly interrupt coverage of my Music Visualisation Project to cover a brief rant about the topical "AI" issues that are all the rage right now.

 

My current position on all this "AI" hype is:

1) TBH, I bloody HATE all this "me too" bandwagon jumping crap that's going around at the moment, and hope it all blows over sooner rather than later - just like "Crypto" and "NFT's" and "Metaverse" fads before it did. The sooner the better!

See also this "supremely on the point" blog post ;) -  https://ludic.mataroa.blog/blog/i-will-fucking-piledrive-you-if-you-mention-ai-again/

 

2) The UX of all these "AI" tools is fundamentally flawed:  i.e.  

     "I do NOT want to have to fucking 'talk' to your bloody 'chatbot' to do stuff!"

 

3) The majority of all this "AI" hype is all being poured into all the wrong directions: 

    "We should be focussing our efforts on helping people do what they cannot do otherwise (i.e. augmenting human abilities),  NOT trying to replace them  (i.e. destructive misery causing)"

    That there is perhaps the best way to sum up the ethical line / standard I use to decide what I spend time working on. I'm only interested in working on stuff that betters humanity's ability to do stuff they otherwise wouldn't be able to do without the technology. Other stuff (e.g. ad networks, DRM, fintech, killer robots, facial recognition, tracking + surveillance tech, making people/industries/etc. "redundant", etc.) I refuse to work on  (and really, anything I am not interested in, I do a categorically *awful* job at...)

 

4)  In that light, will I work on or play with AI stuff at some point?

     Short Answer:  If AI is the right tool for the job, I will consider it.

     Operative word: "right tool"

     So far, none of the problems I have been working on have required reaching into that toolset, so I haven't bothered to really delve too deeply into it. But if the opportunity arises where AI presents a better solution than we can achieve otherwise, I will consider it then.

     Prime Example:  With some of the image generation + editing tech out there now, we finally have the a set of powerful tools for fixing a whole bunch of previously prohibitively difficult-to-fix problems, giving us the ability to do spot fixes for defects that would've previously ruined many images / videos. In that sense, these user-guided "repair" tools are precisely the "powerful magic fix-it tools"  that we've all dreamed of having all these years, and so, by my previously stated principles, they may well be the right tool for the job in those cases. But using these tools to construct entire fabrications from scratch, trained off everyone's data (however ill-gotten)? Nope - that's pretty much something that should not be done!

[MusicViz Project] Part 2 - Motivations + Rough Directions

This is Part 2 of what will hopefully be a series of posts documenting my attempts to build a music visualiser for automatically creating interesting dynamic visualisations for my back-catalogue of music I've been writing + recording of the past few years. Last time I checked, in total there's probably somewhere between 3 and 5 hours of "finished" or "presentable" tracks, with most averaging about 1 minute in length (most come in under that around 52-55 seconds), with only a few reaching 1:10 mins, and only 2-3 blowing out to ~2:30 mins.

Most notably, there are 2 playlists (or really "albums" by this point) of material I produced during the few months I was holed up in my room writing my thesis. During most of the day and night, I'd be listening to these playlists while slaving away in my text editor, desperately trying to make some progress (some days much more successfully than others); and then, to take a break / recharge, I'd write or record some music based on fragments that would come to mind. Rinse and repeat for several months. As my thesis grew, so too did these playlists, which each ended up over an hour long in the end.

For several years, I've been wanting to package these up in a suitable format to release into the world. Currently, only a small handful of these tracks have been heard by anyone other than myself, but certainly not the entirety of these playlists in their totality. Yes, granted, the expected audience is probably vanishingly small, as they are certainly not "mainstream", and don't fall neatly into established categories... hence, even if/when I do release these, I hardly expect many people to actually listen. Then again, if anyone's interested, I have actually since produced a few more hours of similar / evolved material since then LOL - heck, I'm listening to one of the newer playlists as I write this, and even I am surprised by some of the material I recorded even a few years ago.

[Music Viz Project] First Version of Pitch-To-Colours Mapping

After procrastinating over this for a few years, I've finally put together a first version of a mapping for the colours I typically associate with each pitch - one of the key elements for the music visualisations I've always wanted to generate for all the music I've been writing + recording over the past few years.

This is actually my second attempt at putting together such a chart. The first one (which I can't seem to find right now) was only partially complete, as at the time, I kept struggling over whether I'd picked the perfectly calibrated shades for each, which then meant I never got the basics down.

 

So without further ado, here's a rough chart:

 

 (Disclaimer: I wanted to clean it up more, but Musescore doesn't let me easily insert/delete excess notes in the middle of a line without re-entering the notes and then losing the colours. So... meh!)