Have Anthropic actually said anything about the amount of false positives Mythos turned up?

FWIW, I saw some talk on Xitter (so grain of salt) about people replicating their result with other (public) SotA models, but each turned up only a subset of the ones Mythos found. I'd say that sounds plausible from the perspective of Mythos being an incremental (though an unusually large increment perhaps) improvement over previous models, but one that also brings with it a correspondingly significant increase in complexity.

So the angle they choose to use for presenting it and the subsequent buzz is at least part hype -- saying "it's too powerful to release publicly" sounds a lot cooler than "it costs $20000 to run over your codebase, so we're going to offer this directly to enterprise customers (and a few token open source projects for marketing)". Keep in mind that the examples in Nicholas Carlini's presentation were using Opus, so security is clearly something they've been working on for a while (as they should, because it's a huge risk). They didn't just suddenly find themselves having accidentally created a super hacker.

"Danny leaves the scene" (because it's just a bunch of kids with scanners and he's got a job at Eidos now) never forget!

Check https://m4de.com/?tag=archives

There's some semi-apologetic interest in ML, esp. smaller local models, in the "permacomputing" (don't like the term but whatev) sphere. But I don't know if there's much of a conversation around LLMs. With all the hype and how resource intensive and externalities-heavy they are, I can see wanting to draw a line, but it's sad to see it become a purity test.

Lately the discussion around this has had me thinking of the William Köttke quote "not only is it ethical to use the resources of the current system construct the next one, ideally, all the resources of the current system would be used to that end".

I think that if the situation was as dire as it's made out to be (I think it is) and projects like uxn were a serious attempt at a mitigating response (less convinced, as cool as they are), there's room for a conversation about beneficial-detrimental (rather than good-evil). Then we could discuss whether it's a good idea to use LLM-based tools when they are available to help build out infrastructure that runs without them, whether there's a nuance as to at what level of automation we draw the line (Ivan Illich, tools vs machines etc), human augmentation vs replacement, the cognitive load stuff Keeter's post touches on and so on.

Unfortunately, part of the polycrisis seems to be a difficulty in discussing things clearly.

> a bit tone deaf

Agree

Bought yet another second hand 11" MBA instead. Now looking at SMT soldering equipmemt for doing ipgrades and repairs.

Haven't used it much apart from some minor tests (I tend to prefer MoI3D, but that's in a different category in several ways...), but as far as FOSS solid modelers it seems like the most promising to me. I do remember some small UI quirks, but overall it felt very approachable and streamlined, and looking at the GitHub repo, development is active. FreeCAD IMHO is just too sprawling and complex, with seemingly little tought paid to UI/UX.

It's certainly not the real one[0], but looks a lot like the Winamp AVS/MilkDrop stuff. My Inspect Element -fu was however insufficient for getting a closer look.

[0] https://en.wikipedia.org/wiki/Neon_(music_visualization)

(Not claiming it would make business sense to try to cater to weirdos like me, or denying that it made sense for Sega to get out of the hardware game or whatever. But probably 95% of their output post-Dreamcast I find completely uninteresting. :)

It's easy to forget today, but the Sega home consoles were always secondary to their arcade business. The main reason the Saturn sold even as well as it did was because it was the only way to play versions of the heavy hitters: Virtua Fighter, Virtua Racing, Daytona USA and Sega Rally in the home, in any fashion approaching the arcade (though still quite cut down). Those Sega 3D arcade games were absolutely mind blowing back in the early-mid 90s, and the pace of technical progress and new ideas was unlike anything since.

And the Dreamcast was conceived from day one to make it easy to port games from the Sega Naomi arcade system, and those arcade ports are probably the main reason people still play the Dreamcast to this day.

I think you overestimate how much your average person-on-the-street cares about LLM benchmarks. They already treat ChatGPT or whichever as generally intelligent (including to their own detriment), are frustrated about their social media feeds filling up with slop and, maybe, if they're white-collar, worry about their jobs disappearing due to AI. Apart from a tiny minority in some specific field, people already know themselves to be less intelligent along any measurable axis than someone somewhere.