Pretty sure whatever he died from came from bats. Or hamsters

1. 'She', not 'he', AIUI. I can assure you from personal experience that anatomically Russians are indistinguishable in all important respects from other humans.
2. Or more likely marnosets. The commonest vector for plague in this region is the mamoset. I'm not even sure hamsters are found within several thousands km of this area.
3. The disease has a long history in this area. A recent article : "Lethal plague outbreaks in Lake Baikal hunter-gatherers 5,500 years ago" https://ancillary-proxy.atarimworker.io?url=https%3A%2F%2Fdoi.org%2F10.1038%2Fs41586... Nature Vol654 697, 18 June 2026
     "Here we describe early plague strains that are associated with two phases of outbreaks among mid-Holocene hunter-gatherers near Lake Baikal in southeast Siberia, beginning from about 5,500 years ago. These outbreaks occur across four hunter-gatherer cemeteries, with a 39% detection rate for plague infection. By reconstructing kinship pedigrees, we show that small familial groups were affected, consistent with human-to-human spread of disease, and that the first outbreak occurred within a single generation. The infections appear to have resulted in acute mortality, especially among children (aged 8 to 11 years)."

We're all the descendents of the people who for whatever genetic reason survived the plagues in the past and thats why plaque hasn't reoccured as an epidemic since the middle ages.

Except - that was our (mostly) ancestors acquiring a degree of immunity to a strain of the bacterium circulating 250 and more years ago.

It's fairly unlikely that current wild-type strains are the same strain.

Bacteria do evolve in the wild, you know. (Everything evolves in the wild.)

("It actually makes RAM needs worse" -> "MoEs actually make RAM needs worse")

It actually makes RAM needs worse than a dense model, for a given quality.

That said, inference techniques like FreeToken are improving MoE swapping performance, so it's not as bad as it once was. Honestly, I would not be at all surprised if we start doing training in a swap-aware manner, where expert cache misses count as loss and models can queue experts to start loading before they're needed. Could even train in two tiers of loading - RAM and disk. Wouldn't that be great? Could run multi-terabyte models on consumer hardware. Training would tend to tend to concentrate key logic and reasoning on small number of very active experts, mixed reasoning/knowledge on less common experts that are usually kept in RAM, and rarer knowledge on experts that usually remain on-disk until needed.

There are well known, reputable abliterators on HuggingFace.

Also, censorship usually (not always) is something you care about for chats, not agentic work.

A .safetensors or .gguf model cannot run code unless you let it. No agentic framework = all it can do is write text. It can't hurt you directly. At worst, it can only lie to you.

It's big, but not good for its size. They're using tricks to pretend that they're better than they are. For example, compare the numbers that they list for the competion on DeepSWE up against the actual DeepSWE scores.

Not cool, Mistral.

Artificial Analysis is overrated, but yes, Mistral is playing fast and loose with their claims.

It takes one hell of a toll to try to do verbal exams 1:1 on students to evaluate them.

Nobody said "verbal exams 1:1".

The only thing that is required is that they be separated from their computers and their phones.

Nobody, I repeat, nobody who uses AI is going to see "OpenAI adding watermarks" and think, "Oh, I better use AI more, especially OpenAI".

And nobody, I repeat, nobody who doesn't use AI is going to see "OpenAI adding watermarks" and think, "Oh, I better use AI more, now that it'll be easier to see that what I did is made by AI."

It is not "an advertisement of the power of the technology". It's a regulation forced on them by the EU's AI Act, which neither companies nor users want.

Perhaps you should be realizing by now that homework is no longer a viable way to test how well students actually know the subject matter, and the only viable way to do so is in-class tests/exercises - frequent enough and worth enough of the grade to force them to study between lessons.

OR, alternatively, you could just keep doing what you're doing, and instead, in effect grade people on:

Comparably poor grades:
* People who actually do the work by hand
* "AI N00bs" who let stuff like that slip through

Comparably good grades:
* AI-experienced people who know enough to skim over the work, do multiple passes, or issue prompts that prevent such tells from getting into the work

Wherein, in effect, your net reward/punishment is inverted vs. what you should want it to be.

Closing one's eyes and ears to the fact that the environment students operate in has changed isn't an acceptable option. Education must adapt. And watermarks, BTW, will only catch "the n00bs"; more experienced / up to date students will keep track of what watermarks and what doesn't, and use AIs that don't watermark, or de-watermarking services.

I'll repeat: watermarks are anti-marketing. They discourage use.

SynthID in text genuinely is invisible. The probability shifts are small, and all the pathways are valid pathways to express the same thought.

And no, you cannot "collide" text watermarks. At best, it'll only have the latter one's watermark. At worst, both.

It'll still get tagged by SynthID.

You have to use a non-watermarking LLM. Saying "Don't do anything that will watermark it" doesn't help.

Watermarks are "marketing"?

What user wants watermarks?

It's not hard to see how this can backfire. People treat watermarks as the Word of God. But let's say, for example, a journalist, in an article, quotes a White House press statement for something, but the White House used AI. Since they don't "measure how much a human contributed", and detect the watermark in the White House statement in the journalist's article, they'll just flag the whole journalist's article as AI.

And honestly, "not measuring how much a human contributed" is IMHO a massive flaw in general even if the author was using AI. If the person wrote an article, and then told an AI, "correct my spelling, grammar, and poor phrasing", that's IMHO entirely different from the person just telling an AI "Write this article for me", and just pasting whatever it spits out in as their own, whole cloth. Contribution assessment is, IMHO, essential for fairness. And also, eminently doable. It is perfectly technologically possible to not just see, "does this signature exist", but even get a sense of exactly what the AI contributed vs. what it didn't.