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I’ve been using LLMs to help build out audio-related projects that I didn’t think I’d get a chance to pursue until I retired.
Under the hood, are they crap? Maybe. Probably, even. But they function well enough to make my own weird music with, and they’re available for use now - not twenty years from now when I retire.
The era of custom software on tap is here. As someone who is primarily interested in making unique stuff, it’s a great time to be alive.
Larnell Lewis also delivered a world-class performance on that entire album.
The guy has a lot of interesting work, but I think the thing that blew me away the most is the composition 'Warble'. If memory serves, that's the piece where he explored 64th note and dotted 32nd note displacements in order to mimic J Dilla's 'wonky' swing. I've tried capturing the Dilla swing; it's nearly impossible to do on the drums without sounding like you don't know how to play the instrument. Nate Smith, on the other hand, makes it sound fantastic.
The guy is a wizard.
It’s a great supplement because it gives you a chance to understand the ‘why’ of things and not just the ‘how’. The writing style is neither too dry nor too watered-down. It feels like the piece that was missing from K-12 education.
On a side note, I’ve found the LLMs to be terrible at math, but insanely good at writing LaTeX. I’ve been using GitHub Copilot to speed up the rewriting of my class notes and I’m just gobsmacked at how accurately it can print out the steps to some calculation after feeding in the original problem.
If your digestive system tends to have you issues when given unexpected inputs, as is the case for a lot of people, then this is just what you do to stay comfortable while away from home.
It still sounds fantastically weird.
I’m not a beginner per se - I started writing Objective-C and Python more than a decade ago and I’ve written a depressingly large amount of SQL in that same period. But when my current employer decided I was going to be a web developer, I needed to start from the ground up with Django.
Copilot has been a godsend for me. I still need books and Stack Overflow, but the conversations I’ve had with Copilot about architectural decisions, project structure, external library choices, syntax, etc., has saved me a ton of time that I would have otherwise spent reading ad-riddled Medium articles to learn.
As a not-beginner beginner, it’s been a huge productivity boost for me.
Agree with op though that it’s pretty bad with SQL. Other than reminders about basic syntax, conversions from T-SQL to Oracle SQL syntax, or mindless column aliasing, I don’t bother much with it.
I have had a long-standing interest in digital signal processing as it relates to music and audio. Any math or physics training that can help me get makes heads of something like ‘The Scientist and Engineer's Guide to Digital Signal Processing’ would be great.
Honestly though, my math-related knowledge is so stunted that I’ll be happy just to gain a sense of what all is out there.
I recently started working at a university so I’m taking advantage of the tuition reimbursement to build up my math knowledge. It’s a long-term project because I can only take one class a semester, but I’ll probably stay here until retirement (wife is tenure-track faculty at same university), so I’m in no rush.
This would be a huge red flag in an interview that your would-be coworkers are incompetent, psychopathic, or both.
That said, Bargue's process was intended for communicating good taste to 'lesser' commercial and decorative artists as much as it was used for training fine artists. It's a method that essentially boils down to copying pictures of sculptures which are twice removed from nature.
Before and since Bargue, we've had great artists who gained their chops by being students of nature. Many of them never saw a Bargue plate. Many of them didn't use the sight-size method. And there were a lot of skilled Bargue disciples who never had any real impact on art history.
All that to say, I don't think the parent comment is at all out of line. Copying Bargue plates is a fine warm-up or substitute for life drawing, but it's neither necessary nor sufficient to becoming a great realist (we had those long before Bargue). Plus, the world has churned out countless nobodies skilled in the art of copying Bargue plates (which I say as someone who would like to be one of those countless nobodies). It's just not as important as people think.
Again, this isn't my wheelhouse at all. I'm just repeating something I hear often when this topic comes up.
I’m assuming it’s a bad idea for reasons that I haven’t thought through; I’d love to hear them from anyone who has spent time on the issue.
This release used modular synths, an Octatrack, Ableton Live, acoustic drums, and tons of soft synths.
https://open.spotify.com/album/5SYOh9MmkJX4ztmmKkpmyJ?si=9R6...
Running a Docker container for SQL Server and doing some work with pandas will eat up my 16gb pretty easily.
The focus on NLP is because in 20-30 years, discrete data won't be entered into EMRs by providers at all.
Here's the pitch: Providers hate EMRs. They begrudge the time they spend working in EMRs instead of focusing on patient care. They loathe spending their office hours working on documentation. They hate spending their time in meetings with IT staff talking about EMR workflows and form-building. They hate getting lectured by accounting staff about how their documentation affects billing. They couldn't care less about this stuff and in an ideal (or even just a slightly more efficient) world, they wouldn't have to.
Every EMR that depends on webform-like inputs that map to database fields is going to be seen as a roadblock to patient care, which is what providers see as their primary concern.
I think the focus on NLP makes a ton of sense if you frame the problem with EMRs that way. EMR software will continue to be the bane of providers' existence right up to the day that providers can simply talk to their EMR in whatever way they want and have the computer interpret their speech and reliably spit out the discrete data that the accountants and number-crunchers want.
Obviously, I'm talking about a monumentally complicated undertaking and it's a bit on the ridiculous side. But I honestly believe we're going to go there, if only because providers won't be happy until we do.
Analysis of these elements (form, line, space, color, and texture) is usually a part of the sort of art criticism you'd find in academic studio art, art history, or even just the New York Times art section.
The visual design field has a similar, extended set of elements for describing the formal elements of a design piece.
In both art and design, works are usually considered effective if they use the formal elements of art/design to support what you refer to as the semantics of the subject. That's a broad generalization, but you see it in practice a lot, so it seems like a fair thing to say.
Academic art history is starting to feel the influence of machine learning and computer vision precisely because computers can be trained to recognize the formal elements of art and associate their use with movements and historical periods. There are way more detailed articles than this one, but this will get you started if you're interested in this sort of thing:
https://www.technologyreview.com/s/537366/the-machine-vision...
This quote makes me want to drop everything and walk off into the forest.