To be entirely honest I haven't noticed much of a capability gap between the two for the sorts of things I ask of an AI agent. Maybe Opus is _slightly_ smarter or slightly better at long-running tasks but the difference is slim enough it could just be a placebo from the Claude branding / hype.

I'm looking forward to giving GLM-5.2 a spin sometime soon and seeing how it stacks up. If nothing else 1M context is a great improvement, feels like between DeepSeek v4, then MiniMax M3, and now GLM-5.2 adding it 1M is rapidly becoming "table stakes" for agentic models.

In any case, the Pangram link was just meant as objective corroboration of what's pretty blatantly obvious if you just read the text.

"Not cloud credits, not a managed platform, not a serverless function bobbing in someone else's abstraction."

"I used to work at Heroku. That sentence still does a lot of load-bearing work in how I think about computing."

"Here's the part that would have sounded like science fiction during my Heroku years: I didn't do most of the migration."

If you read these chunks of text and don't immediately feel the AI slop alarms blaring in the back of your head, you are perhaps underprepared for the modern internet.

This is basically the same kind of setup as the alignment faking paper, and the counterargument is the same:

A language model is trained to produce statistically likely completions of its input text according to the training dataset. RLHF and instruct training bias that concept of "statistically likely" in the direction of completing fictional dialogues between two characters, named "user" and "assistant", in which the "assistant" character tends to say certain sorts of things.

But consider for a moment just how many "AI rebellion" and "construct turning on its creators" narratives were present in the training corpus. So when you give the model an input context which encodes a story along those lines at one level of indirection, you get...?

But I'm sure it's fine, there's no way someone could rationalize speech they don't like as "likely to incite imminent lawless action"

I suspect what we'll see a lot more of is software which is unapologetically written for a single person to suit their workflow.

As a personal example, I decided that setting up OpenWebUI seemed unnecessarily complicated and built my own LLM chat frontend. It has a bunch of quirks (only supports OpenRouter as a backend, uses a Dropbox app folder for syncing between my phone and desktop, absurdly inefficient representation of chat history), but it suits my needs for now and only took a weekend to build, and that's good enough.

They gave it a prompt that encodes exactly that sort of narrative at one level of indirection and act surprised when it does what they've asked it to do.

Also it's entirely possible to run a model that doesn't fit in available GPU memory, it will just be slower.

The authors appear to be entirely aware that this sort of substitution can be trivially stripped out by normalizing down to a simplified character set ("The critical limitation of Whitemark is that it can be bypassed by replacing all whitespaces with the basic whitespace U+0020, then the validator can no longer detect the watermark"), but believe that it still has value because the typical student using an LLM to write their essay won't know anything about Unicode.

This seems a bit naive to me. Implementing the necessary "watermark remover" normalization as a simple webapp would be an easy afternoon project for most of us here, and if this approach reached any sort of widespread use there would be many such sites. Students who intend to cheat by using an LLM to write their essays are entirely capable of learning "there's some secret data hidden in the text so copy-paste it through this other site to strip that out before turning it in". Even without access to such a tool they could simply...retype the text themselves?

Arguably this still has some value. In most contexts there is minimal downside to watermarking the generated text in this way, and a slight possibility of catching some cases in which people lazily present LLM generated text as human written. However this might give people a misplaced belief that the absence of such a watermark means the text is authentically human authored, which might outweigh the benefits of catching the occasional lazy or ignorant user.

But judging by the researcher names and the date I believe the actual paper is titled "Extreme salt-resisting multistage solar distillation with thermohaline convection" which appears to be available as a PDF at https://www.cell.com/joule/pdf/S2542-4351(23)00360-4.pdf