It may have been due to cpu/GPU support or drivers. It looks like pixel 10 has a custom chip - Tensor G5.

I can look past the sex dungeon, but peanut M&Ms?!

You disgust me.

Basically thinking with a clear head. The idea is that people sometimes do stupid things when they’re horny, whether to impress a girl or to get off or whatever, so “post nut” you’ve “gained a sense of clarity”

Basic ebook support and ereader (epub, pdf, cbr, cbz) + send to device (i.e. Kindle)

Biggest issue is the folder/book structure is very opinionated and isn’t the easiest to work with.

I’ve tried the a number of the ones being mentioned, but the best for me has been Audio bookshelf . It has a good mobile app, allows collections, tries to pull Metadata, offline reading for the apps, etc.

The Windows 12 rumors were due to bad reporting from PC World that it seems AI news articles ran with (I believe an Ai mistranslation was the original issue, but at the very least a translation issue). They added an editor’s note to the original [article] (https://www.pcworld.com/article/3068331/windows-12-rumors-features-pricing-everything-we-know-so-far.html)

But chrome, edge, and safari aren’t open source to my knowledge and they make up almost the entire market. Sure chromium is open source, but that’s not the entire browser. Not to mention, it’s basically Internet Explorer all over again, but with Google behind the reigns.

Looking at android, we get a glimpse of what Google is willing to do to “open source” to keep control.

Yeah, that’s fair. I haven’t jumped into the whole agentic side of things as I find LLMs consistently fail at lower level stuff.

Everyone says it’s great at prototyping or writing documents, etc, but I think that’s just cause people have low standards. When coding I find that it quickly messes things up or lacks good quality control (which you only notice if you’re familiar with the domain). For writing it’s fine, but the tone and language always feels off and certainly doesn’t sound like me.

Either way, I would suggest playing around with them to see how they fit into how you do things. I think we’re starting to see things finally slow down on new implementations, and they aren’t going away, so it may be a good time to see if all the fuss is worth it to you.

The underlying issues, in my opinion, regarding LLMs is their indeterministic nature. Even zeroing out the temperature (randomness of outputs), you can get significantly different results between two almost identical texts.

However, building out an ecosystem supporting new technology is a fairly common progression. If you compare it to the internet things like browser caches, CDNs (content delivery networks), code minifiers, etc. are all ways to help combat latency (a fundamental problem for the internet).

As for the effectiveness of these solutions, RAGs do help a lot when generating text against a select corpus. Its what allows the linked sources in things like ChatGPT and Googles AI results. It’s also what a lot of companies are using for searching their support pages/etc. It’s maybe not quite as good as speaking to a person, but is faster.

Similarly, the reasoning models and managing the models “context” both have shown demonstrable improvements for models in benchmarking.

I’m not sure I personally believe this makes LLMs a replacement for humans in most situations, but it at least demonstrates forward progress for GenAI.

I think you may be mixing a couple of things together, but I’ll take a crack at this.

When you get an Ai generated response from a search engine, this is usually a modified RAG (retrieval augmented generation) approach. How this works is that the content from web pages are already pre-processed into embeddings (numerical representations of the text). When you perform a search, your search text is turned into an embedding and compared (numerical similarity) to the websites to get the most related content for your search. That means that the LLM only parses and processes a very small subset of the returned websites to generate its response.

Another element you might be asking about is how can these agentic AI systems handle larger tasks (things like OpenClaw). That is a bit more complicated and dependent on the systems design, but basically boils down to two things. The first is the “reasoning models” first break concepts into smaller tasks meaning the LLM only has to worry about a subset of a larger task. Secondly, a lot of these systems will periodically merge all past context into a compressed state that the LLM can handle (basically summaries of summaries) or add them to a database for future/faster reference.

At the end of the day, your understanding of the limits of LLM are correct, all the progress we’ve really seen with LLMs (over the past couple of years) has been the creation of systems to work around their limitations. The base technology isn’t getting much better, but the support around it is.

Well, that’s one way to get circumcised.

I think you uploaded the wrong picture, that’s clearly a toad.

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).

Just for context this isn’t anything new, this is a long running issue in the US that Trump has just exacerbated.

To add to that, it’s likely every country has some elements that enfranchise or disenfranchise certain voters. Not to mention rampant propaganda.

While it might be a quote from Regan, it’s a good quote:

Freedom is never more than one generation away from extinction. It has to be fought for and defended by each generation

It’s state by state whether it’s required and/or paid time off. Additionally, just because something is in the law doesn’t mean every employer is good about it.

Except when you add in the element of access to voting. Voting in-person on a work day isn’t necessarily feasible for the average American. By enforcing in-person voting you disenfranchise the groups that are more heavily democratic (younger, working, lower/middle class).