The "Fantasy, but the chemistry works" phrasing in the last box on the first tab makes me suspect chatbot input.

Which is a pity, because I like the exhaustive structure. I just can't trust it. But I guess if I was going to dive into inventing weird cheeses, I wouldn't start with a blog post anyway.

(It would be so easy to generate 50k "Periodic table of <noun>" pages and just throw them into the wild. The public internet really is cooked, isn't it).

I once printed out a directions from an online map that contained "pass straight over the next fourteen roundabouts" (I think it was on the way into Reading). Lose count, and you are stuffed. I much prefer a turn-by-turn approach.

I'm really surprised that you're that deep into folk and have never heard of Connie Converse. She's turned up on my radar multiple times over the past couple of decades, and I don't go looking for her, or much folk content.

I guess it underlines that we all live in filter bubbles - I had assumed she was more well-known than she really is based on news stories like this. Every other artist mentioned on this page? I've never heard of them. Off to youtube...

Well, to be fair, I don't listen to a lot of recorded music, and while I hear a lot of music it's mostly in whatever circles I am in.

For instance, I learned "Big Cheesburgers" by Blaze Foley picking bass on stage during a performance at a winery long before I ever heard a recording of him playing it. Same with, say Chick Pyle's "Jaded Lover" or Nancy Griffth's "I Wish it Would Rain" or, for that matter, Rodney Crowell's "I Wish It Would Rain". Those are all folks I either met in passing or knew folks who knew them well.

So while I have a pretty deep familiarity with music from folks with Texas connections, I don't know a whole lot of stuff outside of that area unless there is a connection to my proximately local folk festivals... David Amram or Stan Rodgers or Trout Fishing in America for instance.

I don't think I am unique in that approach to folk music. A lot the lineage of that stuff is mostly people playing in song circles or in small performances picking up a song from someone else, who in turn picked it up from someone, going back to Leadbelly or whoever.

I like recordings- it's super frustrating to hear a song and then not be able to find it anywhere. Especially if I want to learn it and add it to the other 400 or so songs I have memorized at any time, or go back and re-learn something.

Bubbles are real, but I am okay with them because in a certain sense that's what it means to be in a community. But communities aren't usually fragile like bubbles, and folks can come and go without gatekeeping, so that seems closer to how I think about these systems for knowing about folks.

fyi https://books.google.com/ngrams/graph?content=cyberdeck&year...

(I'd like to know who was using "cyberdeck" in 1976)

Ok, I see - it's a consequence of the smoothing function used in the graph. First actual use is 1979.

That's not the model, that's the box the model came in.

It's unlikely we've hit the limits on improving agent UX, but there are some fundamental limits on LLMs that seem unlikely to be fixed by better UX.

That's funny, 'cos being anti-gay contravenes the UK Online Safety Act too.

Yes. I made no claim your legislators are competent. (Congratulations on the summary dismissal of the hereditary peers!)

I've done some personal CRUD stuff like that. Worked well - I fixed bugs as I found them, only hit one thing it couldn't do (I find codex weak at front-end stuff generally).

Would never publish it though, or approach paid work like that.

Everyone needs a to-do list: kendo.

If you want to organize more work items, you might benefit from a Kenboard.

Assuming improvements in LLMs follow a sigmoid curve, even if the cloud models are always slightly ahead in terms of raw performance it won't make much of a difference to most people, most of the time.

The local models have their own advantages (privacy, no -as-a-service model) that, for many people and orgs, will offset a small performance advantage. And, of course, you can always fall back on the cloud models should you hit something particularly chewy.

(All IMO - we're all just guessing. For example, good marketing or an as-yet-undiscovered network effect of cloud LLMs might distort this landscape).

If I'm reading this correctly ("a single homepage load of http://garryslist.org downloads 6.42 MB across 169 requests"), the test harnesses were being downloaded by end users. They weren't being installed as devDependencies.