Catloafdev

Certain political topics bring out bots and narrative-pushing. It's very obvious with certain topics.

The value proposition isn't there.

If you reframe the perspective from 'free $500 sitting on a server' to 'requires actively utilizing an unreleased 0 day exploit on a server that will certainly be able to track exactly what was done, for a payout of... $500?'

That's pennies for something like this.

Add two zeros and it might get nabbed.

Edit: others have pointed out it's not really a 0-day anymore, they're right, so it's likely more a matter of time.

Is the CSS on the page all messed up for anyone else or just me?

https://i.imgur.com/fRVxjzq.png

Wholesale blocking foreign country IP's is both an extraordinarily common practice and extremely effective. It has nothing to do with the political topics you chose to voice.

> Muse is VERY sticky

How, exactly?

I can't help but give the biggest eye-roll at the barrage of 'fear open models' coming from Anthropic.

Is that why his parents are claiming foul play and hired a private investigator?

> I used Grok Bot and gave it all my financial details and connected it to my work Slack and regret it

This is not the kind of story I would want to publicize if I were a CEO.

Strip mining is an extraordinarily appropriate metaphor.

Imagine a mine has an unknown number of rare materials. And you know the general location of a few of the most valuable spots. But you don't know what may be valuable right next to it. If the pieces that we know are valuable are suddenly gone, the incentive to mine that particular area drops considerably, dropping the chance to discover potentially brand new materials that would have been found the normal way.

This is a pretty hilarious thing to read juxtaposed with AGMAI's requests.

Basically "Here you go, have fun with this, fuck all your demands, by the way we're gonna be releasing the model stay tuned!"

Yes - the Chinese labs serve a market that rely on open-weight models and managed deployments, and the labs gain competitive relevance by releasing those models. The cache optimization feature they came up with required new software to utilize on the inference-end, meaning that open source software would need to be specifically updated to work with these models. It wasn't the type of advancement that they could even theoretically keep secret.

Which version are you using? Using code mode in the desktop Claude app, I do not see thinking traces at all, and I don't see any way to toggle it.

Thinking traces aren't in the Claude app (at least, not visibly). I assumed it's only available (if at all) via API.

Buddy you aren't addressing the comments that are replying to you.

You gotta stay on-topic. You keep coming up with random things to compare to that make no sense to anybody but you. Who said it was legal to say "kill the king"?

> Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5.

Sounds like they noticed the complaints. I'm curious to see what LLM-isms this one may have.

So we're basing winners and losers on vibes rather than money or performance?

Qwen3.8 Flash Next just released which hits that range.

Also, Deepseek V4 Flash can be run relatively well in hybrid 2-bit quantization on 128gb devices, with way better results than you'd expect for a typical 2-bit quant.

Those are currently the 'smartest' options for that memory level.

>until China solves the ASML problem

Which they are in progress on: https://www.reuters.com/world/china/how-china-built-its-manh...

Intel shares are still up over 100% since the Trump admin invested in them and started going to bat for them.

I don't think your information is entirely accurate.

>the only reason ... is that current AI inference is unnecessarily RAM intensive

There's no indication that this will change, and every indication this will continue to grow. This is not some temporary thing. Demand is already exponentially higher than what is possible to produce, and there's no current reason to believe it has any ceiling.

I fear that, whenever consumer-facing supply finally starts to return, the opportunity cost will be priced in. Consumer RAM may end up being nearly as pricey as HBM for a while, and I don't see any reason why it would ever go back down on it's own, unless there are entirely new fab processes that don't meaningfully overlap HBM.

It's not strictly compute, because this has noticeably improved in open-weight models too, such as Gemma and Qwen. I suspect they noticed this issue and adjusted their training to be better about it over time.

No, it doesn't. Nobody would go do this just to report it to Sony for a few pennies. That is a non-existent motivation for people in the know, who understand the opportunity cost.

This seems extraordinarily sketchy.

I'm not saying "LLM's are only capable of AI slop."

We're specifically talking about the context of 'LLM-aided human output' not about general capability of these systems.

People can sniff out LLM generated stuff relatively quickly, the WR raises the floor.

The bar just took a very noticeable jump that people are still adjusting to.

Anything the WR can do on it's own is often seen as 'AI slop' - so now what matters is the QB. Because any random junk QB that doesn't meaningfully improve the WR's output is indistinguishable from AI slop. The distinguishing factor is solely the QB.

Sometimes I wonder what goes on in someone's brain to think these things.

Then I realize I'm probably better off not.

That's the verbiage racists use to try to make it sound like it's not racism.

Spoiler: it's racism.

No, it definitely was not as bad 10 years ago as it is today. Just objectively not true at all.

So if an OpenAI employee just went on his own and did this, rather than 'an AI', what legal repercussions would there be?