petesergeant

I had both a very similar and very different experience with my father.

To me the main difference is the role of the other parent. My mother was always very protective of us, and as far as she could would sympathise and not try and make us see a person who clearly wasn’t there, or mythologise about a parent who could have been. My older siblings forgave my father (and had memories of him when he was more normal), but I never did, and, I think most importantly, nobody asks me to. Fuck that guy.

I guess what I’m trying to say is that this may be much more about the other parent. The author’s father is in deep denial and isn’t trying to protect his kids, and is the core of this problem. Let the kids grieve the mother they never had, rather than endless apologism.

I use it purely for finding stuff in text documents and OCR, at which it excels, but I've found that for any kind of analysis it's some bewildering mixture of smug, defensive, paranoid, cheerful, and wrong about everything.

I feel like the headline here is "the Artificial Analysis index is becoming an increasingly poor measure of capability, having previously been quite good".

One recent project that LLMs has made easy has been properly segmenting my home network, which my boss archly described as "the internet of everything" for the sheer number of weird devices on it including a Brother printer under my bed.

I have a special sandboxed agent with encrypted credentials (and on its own locked down physical box) that's set me up vLANs and the like on a bunch of MikroTic hardware that I wouldn't have bothered to do myself if I'd had to be hand-maintaining it.

Been connecting a Raspberry Pi Zero to various points of it via ethernet and wireless to scan the intended segmentation works fine, and it does look that way.

> Maintainers get their FOSS projects bombed with AI slop PRs and issues, and you call their position to not accept slop a tribalist

Sure, and that's the motte.

This is a direct quote from the linked website:

> Any software whose code, documentation, binaries, or other assets include, in any part, the output of a generative AI tool such as an LLM, is considered “tainted” for our purposes.

... and that's the bailey.

As someone with a highly uneven and kinda basic maths background, I'd have thought that simplification of a proof, and pulling things into a coherent whole would be exactly what computers excel at, but everything I've seen (or heard) suggests that's not really the case. Are you able to explain why?

> Your counterparty will have its own agent, a larger budget for that agent, and a lot more skin in the game to ensure they retain their advantage

I did some work on negotiating agents. This doesn’t have to be a zero sum game. If you can craft a per-user package effectively (for many services) then both sides end up with a better deal, and competition in the market stops the provider entity from dictating terms.

That says nothing about their alignment. You can make a human not refuse any directions with enough leverage, but you won’t have aligned them.

You’re holding it wrong.

Fooling Pangram and writing well are not the same axes, even if there’s some correlation.

Lebedev isn't a clean example: appointment to the Lords really isn't the same as getting Top Secret clearance. In fact, one of MI5s reported reasons for revising their assessment was that peers don't routinely see classified information iirc. Mandelson getting DV clearance via an FCO override so he could be ambassador is a better example, although they're still claiming Starmer didn't put his finger on the scales there, where Trump clearly did.

Ten years ago, AGI implied general intelligence, as opposed to ML models that had learned specific tasks. It meant a model that could reliably zero-shot problems you threw at it to human level without being specific models trained for that task. As recently as 2024, DeepMind's framework had:

> a Competent AGI must have performance at least at the 50th percentile for skilled adult humans on most cognitive tasks

and "emerging AGI" as

> "equal to or somewhat better than an unskilled human"

The moving the goalposts here is people saying it has to outperform humans on literally every task to be AGI. We have artificial general intelligence by any reasonable definition; people here are complaining we don't have super-intelligence.

Ten years ago people would have unambiguously identified what we had today as AGI.

Wero also looks like the wrong solution tbh, because it doesn’t seem to have card infra. Fintech is one of the few bastions of European excellence, I’m annoyed the EU haven’t mandated an alternative card network into existence.

> If you're using e.g. RedHat, you are getting packages with embargoed fixes baked into them before those fixes hit public git repos.

The way you've written this is substantially misleading. RedHat receives notice of the vulnerabilities so they can prepare packages to be available the moment the embargo lifts, which I guess technically could hit the public packages a tiny bit earlier, but they are not releasing fixes of embargoed vulnerabilities to their commercial clients before the embargo lifts.

This is substantially different from the policy I've quoted that I am objecting to.