MintsJohn

The honest answer is i was fed up and choose the nuclear option out of frustration and just wanting to try a new toy. So yeah your right, i'll try that.

I don't think the inconvenience is that big though few secs loading page per session. The ridiculousness though kinda is, we've had years and years of all manner of crawlers that managed to behave, i've even used site rippers in the dial-up days that avoided hammering servers and fetching dupes, now the ai-bros come along and tear the internet apart, replacing it with their chats systems and generic slop.

Identified AI bots that finally made me cave and put anubis (with very liberal limits) up were anthropic/openai/perplexity according to the headers they sent. They were also over 99% of traffic despite proper robots.txt (site only has a few hundredth visits per day), which they ignore. I don't mind bots or crawlers, but these bots got the same page/query string every time they decided it was time for a crawl, which was about daily, cache control, last modified headers they also never seemed to be interested in. They were very very far from well behaved, unlike search engine crawls, and impossible to tame.

And it's all measured in "intelligence", a completely meaningless term. For coding i'd be much more interested in how much context actually works, what the complexity of algorithms it can understand and create is, for what languages. How much it manages to follow existing structures or that is just adds ad-hoc machinery to pass the test, etc etc.

A smaller model in the same generation will never be the same as a bigger one, assuming this is a smaller model, and the same generation, as naming implies, it will not be comparable, it might be on the benchmarks, even on the benchmarks that matter, but the whole story should also give the drawbacks.

No, the issue is when i visited i got a page of senseless drivel (maybe https://lib.rs/crates/iocaine) with the message i was a bot. There was no way around it except "contact support" as the message said the fix, to solve it myself, was to not be a bot.

https://news.ycombinator.com/item?id=48845668 explains it better than i did.

I accessed through mobile, maybe got a bad ip, i don't don't know. But i never could access my repo, and incidently a day before when i tried to share some markdown file in the repo, they told me it wasn't there (i thought it was a them problem then, as i didn't see it).

So that experience and the way it was handled totally ruined my trust. If randomly people can't even access the repo, and that is "working as intended", what's the use to host it there.

I tried codeberg, used it a year, then early this year in all their wisdom codeberg decided to show adverserial random text instead of my repo, reporteldly to mess up llm training to user agents they weren't sure were human.

Codeberg had one job, serve my repo, it didn't do that, when brought up, I was told it was a feature not a bug, they could maybe whitelist me but that wasn't my problem, it was that random people got totally blocked or from accessing the repo. I moved back to github.

Glm5.1 is fantastic for me. But that could be how I use it, I don't ask it to build entire apps or entire features, instead asking it to build piecemeal functionality. For that it compares very well to chatgpt 5.4 (I haven't extensively tried 5.5, it might be better, might be same). I have given deepseekv4 pro a try but not much more than a try, as it performed subpar on 4 tasks in a row (missing the obvious/intended path, generating subpar slightly buggy code to make things work the not obvious way) , I gave up on it.

Glm5.1 for me was a bit of a llama3.1 moment (first open model i could chat with that was usable in manging my inputs the intended way) for code, the first open model that was actually usable.

Of course the devil is in the details. What you say and the skills needed make sense. It's unfortunately also the easiest aspects to dismiss either under pressure as there is often little immediate payoff, or because it's simply the hard part.

My experience with llms in general is that sadly, they're mostly good bullshitters. (current google search is the epitome of worthlessness, the AI summary so hard tries to make things balanced, that it just dreams up and exaggerates pros en cons for most queries). In a same way platforms like perplexity are worthless, they seem utterly unable to assign the proper value to sources they gather.

Of course that doesn't stop me from using llms where they're useful; it's nice to be able to give the architecture for a solution and let the llm fill the gaps than to code the entire thing by hand. And code-completion in general is a beautiful thing (sadly not a thing where much focus is on these days, most is on getting the llm create complete solutions while i would be delighted by even better code completion)

Still all in all, the more i see llms used (or the more i see (what i assume) well willing people copy/paste llm generated responses in favor of handwritten responses) on so much of the internet, resulting in a huge decline of factualness and reproducibility (in he sense, that original sources get obscured), but an increase of nice full sntences and proper grammar, the more i'm inclined to belief that in the foreseeable future llm's aren't a net positive.

(in a way it's also a perfect storm, the last decade education unprioritised teaching skills that would matter especially for dealing with AI and started to educate for use of tools instead of educate general principles. The product of education became labourers for a specific job instead of higher abstract level reasoning in a general area of expertise)

This is what finetuning has been all about since stable diffusion 1.5 and especially SDXL. And even something StabilityAI base models excelled at in the open weights category. (Midjourney has always been the champion, but proprietary)

Sadly with SAI going effectively bankrupt things changed, their rushed 3.0 model was broken beyond repair and the later 3.5 just unfinished or something (the api version is remarkably better), gens full of errors and artifacts even though the good ones looked great. It turned out hard to finetune as well.

In the mean time flux got released, but that model can be fried (as in one concept trained in) but not finetuned (this krea flux is not based on the open weights flux). Add to that that as models got bigger training/finetuning now costs an arm and a leg, so here we are, a year after flux got released a good finetune is celebrated as the next new thing :)

Interesting notion, I notice the same with image models, less stylistic more blandness on the latest generation. Only MJ seems to have style as a feature.

I tried it with rust, it's so bad it's simply not usable, it hallucinates methods and even the syntax is wrong at some points (it especially can't get error types correct or seems). Gpt4 doesn't handle rust perfect either, but the code it produces is good enough to only need some touch-ups, it can explain and fix wrong use of (we all known) libraries and even gets async code. But it's especially great for boilerplate, saves so must typing.

I was hoping openai/gpt4 would see some healthy competition, but Gemini doesn't seem to be it. Of course, the rust language might be an edge case.

I'm more and more thinking a government issued digital identity (like https://privacybydesign.foundation/irma-en/) that can be used to proof you're human (and other details of you want) but that can't be tracked back to an individual, but again optionally, can be used to create (multiple) online persona's is the way forward. I used to think of these things as dystopian, but fake content by fake persons is a bigger issue. Of course real persons could create persona's for such a bot, but a (personal and/or community based) blacklist mechanism based on the root account (the real human that created the persona) would go a long way.

No worries, you're not alone. I can see it has decent (not great imho) production values, but it's not for me. It's slow and uninteresting, I'm level 2/3 and facing unbeatable level 5 enemies (a hag in a swamp, some tiny island after a swamp or some underground minotaurs). I know I should find entertainment in doing other things in the game, but I'm 10 hours in already, and progress is agonizingly slow. All I got is that I've bug in my eye I want to get out of it, somehow all my companions have it as well, and there's a refugee camp that's being evicted by more druids. I have no idea what the overarching story is, I just go from little set piece to new little set piece (which feel rather artificial), but it's not very interesting and my characters feel as weak as when I started the game. I have fond memories of bg1 and bg2, played them into early morning cause I wanted to know what was next. But now, I just don't care, I just feel lost and like making no progress at all.

That there seemingly is no great story shouldn't be that much an issue to me, it doesn't always matter to me, but with the battles not being engaging, character progress nonexistent, exploring not being exciting nor rewarding, there's just nothing that makes me want to come back. Now i do have a great dislike for open-world games, and it seems bg3 just has all the elements that makes me dislike it, too much make your own adventure. I don't recall the earlier baldurs gate games being this way.

Well, this just goes to show not all elderly are the same. My relatives would love more remotes and hate more strange non physical interfaces. Controlling lights with voice commands vs a (eventually on a remote) button, button wins 100% of the time.

The biggest hurdle seems to be discoverability. A physical remote makes sense, and doesn't change. Buttons have a singular function and context doesn't matter. Apps are different beasts, navigate up/down/forward/backward (thus context (what did you do before, now doing x does y, but otherwise z)) is just met with glazy eyes. Going back and front just makes no sense, why sometimes you need to go to a menu and other times it's a shortcut button, makes no sense, especially when summoning the menu needs special navigation. To add insult to injury, every now and then apps get an overhaul, and suddenly navigation and buttons changed/looked different.

Now when i say apps, i do mean apps on phones/tvs. The windows UI works for them because the basics are the same for all programs, using word or outlook, menu items have text like "send" "save" and while it takes time, functionality is discoverable. But for tv apps the logic is "click up or down until the icon you want has a different hue, then press a button on the remote to do stuff, but only when the screen shows x,not when it shows z". It's too much functionality condensed in too little UI. I'm constantly baffled by design choices for apps that are supposed to be used by everyone, I'm sure it looks nice to designers and devs, but have they even tried showing their brand new TV interface (these are the worst offenders) to an elderly and gave them simple tasks?

At least you got an explanation, I had my Vivid account blocked without one, the only interaction was by chatbot, the only response I got was can't disclose the reason because of compliancy issues. For extra fun trying to get the funds on the account back I had to go to an online form, which didn't have the fields I was told to fill in, and again was met by no response. Eventually had to go through EU settlement to get a human response and an email link to an app for digital identify validation, eventueel I at least got my funds transferred to my main bank. Why the account was blocked remains a mystery, I only used it for online payments and never even contested, refunded or failed one.

Anyway, it's utterly bizarre to me that banks can get a license to run their business with what seems only a marketing and it-team with virtually no recourse for the customer, it was a WTF moment for me and I hope to never get in such a distopian situation for something I really rely on, be it banking or (utility) services.

This is why ,as useful as they are, I also loathe llms, so much textual content is endless drivel, either fully created by AI or helpfully rewritten. Of course it's not new, but what is new (to me) is users using llms in discussion topics to either troll or to make their point, or receiving (real, work related) e-mails fixed up by chat-gpt; madness.

What a weird take. These AIs pretty obviously so work. Sure some parts are surprising, more to me than to experts of course, yet why not take the less understood parts and try to understand them, experiment, see what works and why and how, see what doesn't, that's science, not "boy geniuses".

For code using it like that, I live or as well, no need to try to understand the API docs (if even usable ), just be pointed in the right direction.

But code has a pretty strict check on correctness afterwards, thinking about it its pretty scary how chatgpt results can be used without proper validation. And they will, the step from "looks good to me" to "it is good" is a small one when you just want an answer.

I've been thinking that for months, but recently swung towards being more optimistic about SD again, everything midjourney looks midjourney while SD allows you to create images in any style. MJ really needs to get rid of that MJ style, make it optional as it's undeniably pretty, it's just becoming a little much.

But I still feel 2.x is somehow a degradation of 1.x, its hard to get something decent out of it. The custom training/tuning and all is nice (and certainly the top rain to use SD over MJ, many use cases MJ just can't do) but it should not be used as a band-aid for appearantly inherent shortcomings in the new clip layer (I'm assuming this is where the largest difference comes from, since the Unet is trained on largely the same dataset as 1.x).

It's already possible to tag (parts) of sentences on how tts has to speak them, quiet, excited, etc. Soon it'll be just a matter of what is cheaper, a recording or a tagger/director, and that tagging will be partially automatic. As with many things absolute quality, sadly, won't be the target, good enough to keep people buying the product is.

Not sure how I feel about this prospect, I love audiobooks, and for big titles the narration cost is a drop in the bucket, and I like the idea of real narration. But at the same time lots of indie books don't get an audio version, and that tts allows more books the have an audio version is a plus and having each character get their own voice works be nice.

There's been this big promise of rocm for ages, since it hasn't taken up ever since, I see no reason for it to do so shortly (it will eventually). Yes rdna3 has ml optimizations, sure there is even some non public windows rocm build, but even if everything works out, taking into account the time the leading frameworks need to either fully use rocm at all or even update a to newer version, now is not the time to get an amd gpu when you want to do ml. Given AMDs trackrecord of not delivering workable ml solutions, it only makes sense to do so when the ecosystem is there and stable for a year or so.

Ah yes, with all the GPT3 news I thought MSN was using it. Thank for correcting that assumption. Doesn't make the situation any better of course, it's just that MSN forwarding anything unfortunately is no news to me.

Gossip is presented as gossip, fake news a news (or in this case facts).

(I read the article twice, the website being unknown to me I thought it was fake news, and it still seems weird to me that MSN uses AI generated content, otoh why not, the mess MSN forces on me in windows has been distopian for years, and the mentioned article appears on MSN. Sad times that these days I'm sceptical of anything. I honestly feel this is one of the biggest dangers of our times, the ease with which populations can be influenced and truth is just a matter of alternative facts, the common argument is that it is of all times but that neglects how much easier, more sophisticated, and larger the reach is)

See what is happening with StableDiffusion, a model was released opensource, performance in the same league as closed source, usable on consumer hardware and (non AI) techies start to modify it. The biggest steps/modifications are by specialists no doubt, yet still opensource, but others are happily glueing parts together to make something else. The key really seems to be access, an hosted API is rather hostile to innovation, using and especially experimenting is expensive, modification can only happen within whatever the API allows. For the tech to get bigger and more noticed faster more people need to be able to tinker with it.

Which they aren't intending to do, but it's just part of the fud currently spread around.

Rarely have I seen so much fud spread, while also systematically using the least charitable interpretation of anything stability.ai or emad said/announced. (the whole covid skeptics shit storm comes to mind).

I could understand where this would be coming from if it was aimed against the use of these AI models, but this seems to be from the proponents.

Of course, I can see the dissatisfaction, but not the escalation, does any one really think stability.ai should associate itself with software piracy?! Cause that's what this started about, enabling the use of a a stolen model and weights. The way I set it the only safe action for stability.ai was to distance themselves from this as much as possible.

Of course the reddit “takeover“ happened a week before these events, the active mod, the one that started the linked topic, kept his moderation rights. One issue was that SD wanted to disclose private information to the modaal that required an NDA, not all ex mods wanted to sign. Either way the situation is more complex, not handled ideally, but again, using words life tricked is the least charitable interpretation. And for better or worse with stability.ai controlling the subreddit, in order to put distance between them and the tools that enable the use of pirated models (and in that repo there is an explicit discussion topic on how to use the pirated model to get the same results as novelai (the source of that model)) of course the link to the github repo that enabled the use of these was removed from the stickied topic listing blessed UIs and other things.

I'm curious whether this really is "the fastest model yet" there are pytorch optimizations as well.

Something like global optimization has been done in pytorch, here's a blog about it: https://www.photoroom.com/tech/stable-diffusion-25-percent-f...

Mixed precision seems pretty much default looking at a few Stable Diffusion notebooks.

More intriguing, there's also a more local optimization that makes pytorch faster: https://www.photoroom.com/tech/stable-diffusion-100-percent-...

Unless it's already there, that last one would be interesting to add to keras.

All in all this machine learning ecosystem is wild, as a software dev, things like cache locality and preferring computation over memory access are basic optimizations, yet in machine learning it seems wildly disregarded, I've seen models happily swapping between gpu and system memory to do numpy calculations.

Hopefully stable diffusion changes things, the work towards optimizations is there, it just seems often disregarded. As stable diffusion is one popular open model that, when optimized, can be run locally (and not as saas, where you just add extra compute power, which seems cheaper than engineers) and has a lot of enthusiasm behind it, it might just be the spark that makes optimization sexy again.

But that's exactly what happens, AI isn't randomness, it's a set of predefined calculations. The randomness is in the seed/starting point. For e.g Stable Diffusion it is given/user input, resulting in perfect reproducibility.

Or wait, if its just about stable diffusion multiple people try to create onnx and directml forks of the models/scripts, which atleast in theory can work for AMD gpus in windows and wsl2

A few times I've been looking at nim, always thinking of looks nice. Then I consider what libraries I need (most recently (rpc over) websockets, html parsing/manipulating), and can't seem to find them. The language nim is great, unfortunately the ecosystem seems rather in its infancy.

It'd be a shame if full frame consumer cameras were to disappear from the market, the ai enhanced photography from smartphones just always feels fake to me. Yet I wouldn't be surprised if it were to happen, wouldn't be the first time the lowest common denominator becomes the benchmark standard for various reasons (ease of use, low cost access), happened to music with mp3.

I don't think it's just genetics, or genetics are rapidly changing in the last 100 years.

Personally I think it's some combination of gut biome, all than not messed up childhood eating habits (I've been taught to eat till stuffed, not so great in combination with my next point) , and way too calorie heavy (processed) food (it's not a challenge to find food where a quarter package is a healthy amount, way more challenging to find food where they food for a full package) not too mention it's made to keep you eating (so more is sold, sigh) . I'm always surprised people claiming not to have cravings whatever (even when the stuff is put in front of them), or be satiated by eating what for me is half a meal (even when I maintained a normal weight) .

Regardless eat less and try harder are hard to keep up, for me personally protein doesn't help to satiate me either. Part of it is that (for me) it's much easier to get into a habit to eat too much than to keep up the habit of eating just enough (I dare say 2+ years of keeping it low is a habit, but now for 3 wars annually 5kg was added: next try keto, hope it works as well as advertised)