A rust-bearded robot driver sits on a barstool, sipping nonalcoholic syntha-fuel. "They're replacing me with a human!"

It occurs to me that I had an advantage over kids today, in that there were different forces at play, such that I had to take tests in classrooms, so it was either learn shit or get a bad grade. I don't think of the forces that put me into classrooms as all that exceptional, but I think the young 'uns really do have one really unusual one, that I (as well as my parents' generation, now that I think of) just, somehow, skipped right over.

You see, back in my day, we did a lot less of this ..

Quite a few students had expressed anxiety about being in a classroom after a gunman killed two students and injured nine

.. and instead we just let the ever-pending horror of nuclear war terrify us. And the neat thing about nuclear war, is that someone is going to hatefully and gruesomely murder you no matter where you where you are, so a classroom isn't really all that different than home.

I'm wondering, what can we do to help younger people be terrified out of their minds all the time instead of just in common-sense situations like crowds? We need to help them understand that they're safe nowhere, so they're not-particularly-unsafe anywhere, so they can show the fuck up and take exams.

While you may be correct that the claim about consciousness being from beyond the observable universe is not falsifiable thus beyond the scope of scientific credibility, so too is any current understanding that would support an assertion that "Anthropics models work *just* like human consciousness".

We have pondered the question in a philosophical way, and can assert certain trends based on evidence, but in a comprehensive fundamental sense, the question has to date remained philosophical at the levels that the Anthropic paper needs. Note that the paper even explicitly acknowledges this facet of their work as philosophical, and the generated responses reflect upon that. It puts a lot of weight on the models being able to self-assess accurately and then using the result to show that they can self-assess a consciousness. Including one area where I noted that the "j-space ablated" output indicated that it was just token prediction, and seems like they use that to illustrate that it is conscious that it lacks consciousness...There's a lot of circular reasoning around the headline claim.

I read it more as "we're already in compliance, no changes"

And now we'll have another long lawsuit about whether or not they're in compliance. They'll need to make changes in 9 years when that suit plays out and a year later it's irrelevant.

Feel like those are more akin to science philosophy than concrete scientific understanding. Which tends to happen in scientific pursuits when we dig deeper than what we can realistically actually explore in a strictly scientific way. Biggest problem is we struggle to recognize it as philosophy when it comes out of scientific thinking. We *want* to know more than we can piece together through scientific basis and for lack of a better option we go for the unfalsifiable and subjective opinion.

I recall a physicist explicitly addressing the phenomenon in his field. He refrained from participating in the musings because all he could do was figure out what math worked and hope someone comes up with better math, the wilder speculation upon unobservable implications was beyond the scope of what he felt science could do, but it's a very popular thing in physics.

You default to a windows user agent as of earlier this year?

I've had to tweak it on a rare occasion, bit I haven't left the default as lie and be windows for a long long long time.

I imagine the stats website is more likely to capture my default than the random site I've tweaked.

I perused the paper, I think the comment was pretty spot on. Specifically the part where they have as a casual assumption that they know how human consciousness works.

It's basically shaking the magic 8 ball and it works, but it's totally a judgement call when it has worked 'enough'. It doesn't necessarily progress from easiest to hardest issues to find, it just is a bit random. Hard to say how many passes before you've *probably* got the real ones. My experience has not been that false positive rate increases, sometimes you might have all false positives but a continuation will flag real issues.

Indeed, they take needles in haystacks and make smaller haystacks that have some of the needles. They don't catch some things and they falsely flag a lot of things, but they do either directly or get close to something.

One issue in our codebase that was caught was pretty much spot on. Now upon it being highlighted, it was obvious to anyone that the inexperienced developer screwed up, problem was no one had the attention span to notice. The other issue close to real that it caught was actually not the flaw it indicated, however while looking at the jankiness that caused it to mis-indicate, a real issue was discovered. So it's indicated "fix" would have done nothing and left the codebase vulnerable, but the finding *was* useful in identifying an actual problem and fix.

However, it does open up a gigantic mess in customer engagement. Customers like to use every security tool at their disposal and hold the vendor accountable. Fine, except now we are inundated with false positives because the LLM indicates something, the customer has no way of knowing if the LLM is right or not, and we have to address false positives. We are now having to consider how to "fix" false positives by steering the LLMs away from indicating bogus things when analyzing our product. When it was the occasional misguided security researcher making a misunderstanding, no huge deal, we could discuss nuance and come to an accord. With the LLM mess, there's no skilled human to appeal to, a skeptical customer, and just a lot of volume...

And they are starting to lose confidence. They only work for Vizzini to pay the bills, not a lot of money or revenge.

Whatever you may think of capabilities, the narrative has always been about what they think sounds best in the moment.

So at one point, only the owner class matters, investment is King and every other concern can be bulldozed. The business opportunity down market would never be as much as what employee replacement would be.

Now they see a need to balance it because shockingly the people still have some leverage, whether it's banning construction projects or getting skittish with retail investment. Further the stories around employee replacement have gone permanently bad at prominent companies like Ford. So they need to move the goal posts to dodge the negative optics and recalibrate expectations.

Does AI still use Em dashes?

Everyone asks it not to. And the models probably adjusted due to feedback.

It'd be like looking for lead in the air to detect a car that drove by. The time where that detection work has passed.

The first like shows a 10% drop over a few years then flat (long range).

Basically flat (mid range)

And 15% drop then flat (standard plus)

Not linear at all.

Lead used bad chemistry and no/poor cooling.

The first gen i3 used crumnny tech too.

I can't speak to the early GM products.

But for the most part effort was put into good temperature management (Tesla) and more robust battery chemistry (pretty much anything in the last 10ish years).

The Leaf was made super budget and it killed the batteries.

I cannot agree more with this sentiment. It feels outright insulting to asked to read LLM output in a context where it is *supposed* to be human feedback. Tell me what you would have told the LLM to say, I can take it from there. I don't need you to LLM it up, because it will bury your point in a bunch of crap.

Could it provide useful info? Maybe, but I can do that myself if so. I want *your* thought on something, however incomplete it might be.