Audalin

I knew a Horn of Plenty is a good choice, but I didn't think it's that good. Thanks!

Oh, forgot about healing wells, thanks for the reminder. You should probably be able to throw the ankh directly too? But I don't encounter them every run (e.g. didn't have any this one) so they aren't reliable.

I know ascending is easy (did it many times, though only with 0-1 challenges, none of them Swarm Intelligence) and adds a 1.25 multiplier and I'll do it when I go for that badge - but I didn't plan for it (thought 6 challenges would be 2-3x harder than it turned out) so I wasn't prepared to ascend this run. I'd have probably died in the 21-24 zone.

So you think it should be On Diet? Hmm, maybe. But exploration with both On Diet and Into Darkness will be challenging.

My intuition:

• There're "genuine" instances of hapax legomena which probably have some semantic sense, e.g. a rare concept, a wordplay, an artistic invention, an ancient inside joke.
• There's various noise because somebody let their cat on the keyboard, because OCR software failed in one small spot, because somebody was copying data using a noisy channel without error correction, because somebody had a headache and couldn't be bothered, because whatever.
• Once a dataset is too big to be manually reviewed by experts, the amount of general noise is far far far larger than what you're looking for. At the same time you can't differentiate between the two using statistics alone. And if it was manually reviewed, the experts have probably published their findings, or at least told a few colleagues.
• Transformers are VERY data-hungry. They need enormous datasets.

So I don't think this approach will help you a lot even for finding words and phrases. And everything I've said can be extended to semantic noise too, so your extended question also seems a hopeless endeavour when approached specifically with LLMs or big data analysis of text.

LLaMA can't. Chameleon and similar ones can:

• https://arxiv.org/abs/2405.09818

For Tolkien's work, there is the twelve volume "The Complete History of Middle Earth" which is about as inside baseball as you can get for Tolkien.

I'd replace HoME with Parma Eldalamberon, Vinyar Tengwar and other journals publishing his early materials here.

Recommending Italo Calvino's Six Memos for the Next Millennium, the lectures he has been preparing shortly before his death.

Not an assembly guide for a work of literature, but it'll help your own process if it's already ongoing and you want to improve.

The lectures also have some comments on what Calvino himself was doing here and there and why.

ChatMusician isn't exactly new and the underlying dataset isn't particularly diverse, but it's one of the few models made specifically for classical music.

Are there any others, by the way?

Both work very well for the entire journey there and back. I use the first I get my hands on (typically scale armour) and upgrade it to +8. But if it's plate armour, you might have to start using it before gaining the necessary strength, so be ready to spend more time and food on a few levels in the prison area.

The Phoebus cartel strikes again!

I expected that recording would be the hard part.

I think some of the open-source ones should work if your phone is rooted?

I've heard that Google's phone app can record calls (though it says it aloud when starting the recording). Of course, it wouldn't work if Google thinks it shouldn't in your region.

By the way, Bluetooth headphones can have both speakers and a microphone. And Android can't tell a peripheral device what it should or shouldn't do with audio streams. Sounds like a fun DIY project if you're into it, or maybe somebody sells these already.

Haven't heard of all-in-one solutions, but once you have a recording, whisper.cpp can do the transcription:

• https://github.com/ggerganov/whisper.cpp

The underlying Whisper models are MIT.

Then you can use any LLM inference engine, e.g. llama.cpp, and ask the model of your choice to summarise the transcript:

• https://github.com/ggerganov/llama.cpp

You can also write a small bash/python script to make the process a bit more automatic.

I enjoy xenharmonic music and modern academic music the most, but I'm not familiar with everything there, so any recommendations are welcome if you, reader, have something in your mind.