This is about “teleporting” information not physical material (if my understanding is correct)

I tried Calibre web and Kogma.

Calibre is just bad software at this point, it’s clunky and not really designed as a server.

Kogma was fine, but a web only interface made it hit or miss. The big selling point for me with audio bookshelf was the ability to download local copies.

Oh yeah, the multiple libraries is a good point!

You can read using the web client or dedicated apps (android and ios). I feel like the clients work just as good if not better than similar software.

I haven’t tested how it handles two versions (audio/ebook) of the same book, but I have ebooks and audio books and it works well for me.

The only real downside I’ve run into is it’s very opinionated about folder structures around authors.

The one I’ve enjoyed the most is https://www.audiobookshelf.org/, it may be “focused” on audio books, but works really well for everything. It also supports offline mode (meaning downloading local copies in the app).

Sounds like we are talking about different kinds of “access”. My original post was just lamenting that to the general web, discord is like a black hole. Things go there and never come out as you can only access the content through its app.

A lot of discord content is private, and those that aren’t require you to have discord to search. On top of that, I’m pretty sure you need to join a server before you can search it’s contents.

Since I don’t use discord, there is no real way for me to access content hosted on it. Compared to Reddit or a Forum, I don’t need to be a member of the community to access information shared there.

At least public githubs aren’t difficult to access and/or crawl. The big issue with Discord is that there is a wealth of information locked behind a proprietary system.

Unlike forums or even reddit, there is not way to get to most of the information posted on discord.

Not sure if you really want to know, but a Google paper is where transformers (backbone of LLMs) were first mentioned (2016 I believe). Google initially used transformers for translations and eventually search, but OpenAI experimented with them for text generation (gpt 1+) eventually leading to chatgpt.

I feel like a majority of tech has been in this rut for a while. CPUs, GPUs, audio, wifi, 4g VS 5g, screens/tvs, etc. all seem to provide the most incremental upgrades each iteration. For a while phones seemed to be making leaps and bounds, but feel relatively the same generation to generation now.

I think the main area I feel like I’ve seen some movement is battery tech. Some new materials and better/longer batteries are making some movement, but tech hardware feels relatively static the past decade or so.

I’ve downloaded some 4k content to do side-by-side with 1080p and it’s a struggle to notice the difference.

The issue is more that there aren’t rules. Given there are billions of parameters that define how these models work, there isn’t really a way to ensure that it cant produce unwanted content.

Yeah, if I’m making something “masked/obscured” I should export it so that it’s in a raw format. That way there is no Metadata or information that could be leaked by accident.

Think of the Trump Epstein files, in those they kept them as pdfs so you could just unhighlight the redacted sections. If they had export it as a jpeg/png you wouldn’t be able to extract any information.

There are ways to remove the content from a pdf, but as we’ve seen, that leaves rooms for errors.

If the image/video just has black pixels on the content, then there would be no information to extract and any attempt would just be filling things in.

When you talk about layers, you’re assuming that the creator left information behind in the Metadata, which wouldn’t require AI to extract.

I had someone swear to me that Github templating was better, but I’ve only worked with Gitlabs templates. Why do you like Gitlab over Github?

I was going to ask how this is different than a Reinforcement Learning algorithm but then they called out Deep Minds Alpha-Go

All of them. If you’re seeing sources cited, it means it’s a RAG (LLM with extra bits). The extra bits make a big difference as it means the response is limited to a select few points of reference and isn’t comparing all known knowledge on a subject matter.

Thanks for the details, seems like that may be why the older Chromecasts are still supported.

I thought for Chromecast the “casting” part is just telling the Chromecast what to play. Do you need your phone on while Chromecast shows content?