emptiestplace

I had to think about this for a minute because the abstraction levels idea is very appealing, but ultimately I think this comparison is specious and misses the core issue entirely.

XY problem is a communication and problem-solving anti-pattern where someone has already decided on an approach and is just asking about implementation details, rather than being open to potentially better solutions that might emerge if they just explained wtf they are trying to do first. Framing it as different abstraction levels obscures this real issue and incorrectly suggests it's just a natural variation in thinking styles rather than a specific mistake in problem-solving approach.

Sorry, I was mistaken about having used LiteLLM - this is the one I was using: https://github.com/wangxj03/ai-cookbook.git, and you can see the hardcoded shit here: https://github.com/wangxj03/ai-cookbook/blob/main/anthropic-... - it does not actually restrict anything though, and like I said, I noticed it was getting slow when it was sending 100-200K token requests.

Also, it's pretty easy to find unresolved bugs related to openwebui not handling context length parameters correctly - I believe I actually read something from the author saying that this parameter is effectively disabled (for non-local LLMs maybe?).

I think that's probably the shim I was referring to - it has hardcoded context length, but it is either implemented incorrectly, Anthropic ignores it, or maybe it's on openwebui to manage the window and it just isn't? Not sure. I found it kept getting slow, so I was starting new conversations to work around that. Eventually I got suspicious and checked - I'd burned through almost $100 within a few hours.

LibreChat isn't as nice in some areas, but it's much more efficient in this regard.

Needs some usability testing - I suspect even five minutes of watching a non-technical user trying to use it would be very illuminating. UI is unintuitive throughout. Consider, one of the most frequent actions you will ever do in this type of app is start a new conversation, and here it is represented by a little button near the bottom of the sidebar where you might look for 'Settings' - apparently collapsing the sidebar is much more important. Tiny text, low contrast text, confusing collapsing/expanding sections, lack of whitespace and/or colour to differentiate message pair halves, confusing hover actions for copy, no floating or bottom of code block copy button... I'm pretty sure configuring API keys was weird for some reason as well, but I can't remember what it was.

LibreChat is probably the one you want to compare to - Claude is not supported by OpenWebUI, and the shim will cost you dearly in terms of tokens.

There is very little I find more frustrating than software that could so easily be nice to use but isn't.

To inspire more of the same.

> We don’t need the military-industrial complex

I hope you realize that part isn't going anywhere any time soon.

> Not everything is an XY problem

Pretty close, though.

It's back, but the nice thing is it's 10x more complicated now!

Season 3 is so great it easily eclipses the first two, despite my pretty strong nostalgia-bias. It's like the first two were just a warm-up - and we needed the 25 years just to prepare ourselves for what he really wanted to do.

We've had failed projects since long before LLMs. I think there is a tendency for people to gloss over this (3.) regardless, but working with an LLM it tends to become obvious much more quickly, without investing tens/hundreds of person-hours. I know it's not perfect, but I find a lot of the things people complain about would've been a problem either way - especially when people think they are going to go from 'hello world' to SaaS-billionaire in an hour.

I think mastery of the problem domain is still important, and until we have effectively infinite context windows (that work perfectly), you will need to understand how and when to refactor to maximize quality and relevance of data in context.

I love the questioning my sanity before I've completely opened my eyes part. It's like a jump start to my day.

> Consequently, for an LLM to predict the next word in a sentence generated by a human, it must model these processes.

No.

What could go wrong?

> I believe everything Annie says here.

How is this relevant?

I think they removed it.

I appreciate harm reduction but I think any such 'perfect' drug would lead to dehydration / starvation deaths, or at least a lot more people living on the streets.

Excellent joke explanation!

What a hilariously absurd statement. You might want to actually try it.

This App Store review makes Mubi sound promising:

"MUBI IS TERRIBLE! *---- 6y ago • Nick2866 MUBI is terrible there's no good action or horror films it's crazy because almost all of the movies on the app I haven't even heard of and I'm a big movie buff. So just don't waste your time with MUBI just get Netflix or amazon prime."

The LLMs themselves aren't the fundamental concern; rather, they represent an unprecedented amplification of existing socioeconomic stratification mechanisms. They will likely accelerate the already problematic concentration of capital and opportunity among those positioned to leverage them - and we will see, inevitably, a continuation and intensification of patterns we've observed since the dawn of industrialization.

> if LLMs were really that miraculous, we wouldn't have such detractors

I don't think you thought this through.

I keep saying this but nobody seems to really get it or care: LLMs are magic. This isn't at all like conventional software where someone plans for every possible path, or even software where paths are generated procedurally. These models show truly emergent behaviors that go far beyond their training. And yet people dismiss them simply because they're probabilistic (more likely because they've heard some version of this, actually), as if that somehow invalidates the fact that they're doing things they were never programmed to do.

Our understanding of consciousness is about to undergo a revolutionary transformation, and a lot of people ... aren't going to like that, either.

It’s going to take a lot more backlash than this—they have too much financial incentive to push royalty-free tracks.

Wish I'd known about Swift's 'A Modest Proposal' first - I came expecting practical Unix time insights, but found an attempt at satire in need of both editing and purpose.

That sounds quiet.

I'm a little lost, but it seems like you aren't - how does virtualization help with the actual work of splitting codebases into reusable components?

Who is going to pay for this?

This is beautiful, do you think we might be going in such a direction?