I think you could bring a gas-mask if you're worried about this.

Some people were worried that this might scare others or be too inconvenient. However, reading the WSJ article, it seems to me that dangerous fumes are noticeable when they occur. So you could bring the gas-mask and put it on if you notice an off smell or see smoke.

I use twitter a lot (maybe 45 minutes a day on average), and I don't think I do that. I don't think I boost misinformation. Unless replying to people who spread misinformation to argue with them counts.

https://x.com/williawa

Feel free to look through and prove me wrong. I think you might be able to find tweets I'll feel somewhat bad about if you post here, but I think they'd be me calling someone an idiot or something, not me spreading misinformation. 

There are other people who I think this applies to too. Like @Isaac King or isaac king I think are very active twitter users who are reasonable. Even Eliezer who you seem to be pointing to as an example of someone who is negatively affected by twitter, I think is not really very bad. I think his twitter conduct is less than literally perfect, but I can't remember him boosting misinformation in a clear cut way.

Or, I can remember a few instances spreading what I'd call "misinformation", like saying, without caveats, that "saturated fat is healthier than polyunsaturated fats" (paraphrase it might've been just unsaturated fats), but I think he sincerely believes that, and not because of twitter, so its not an example of what you're talking about.

Hmm, I've heard many conflicting anecdotes here. My own experience is that GPT5 is extremely bad at agentic coding compared with eg Opus 4.1 and even Sonnet 4. And that's not taking time into account. It uses like 10-100x the time sonnet does which makes it mostly worthless to me.

For me it's only been good at 1-turn stuff, similar to o3-pro (or, my experience with o3-pro). Like I'll tell it to fix a bug, with detailed info and context and then run it for a while, and it's pretty good at fixing bugs that way. But if it doesn't work, I'll just revert all its changes and fix the bug myself. If there is multi set stuff like fixing a bug and then writing tests. Or implementing module x and hooking it up to interface y, it just isn't very good.

That seems like one of those problems which if considered in sufficient generality even god cannot solve.

I'm wondering. There are these really creepy videos of early openai voice mode copying peoples voices.

https://www.youtube.com/shorts/RbCoIa7eXQE

I wonder if they're a result of openai failing to do this loss-masking with their voice models, and then messing up turn-tokenization somehow.

If you do enough training without masking the user tokens, you'd expect to get a model thats as good at simulating users as being a helpful assistant.

Okay, the "genetic knob" is maybe the right language. What I meant is that for evolution to be able to inner-align humans to IGF, you'd need

1. Humans occasionally wanting IGF, and using that to inform plans
2. Humans doing those plans
3. This being a successful strategy (eg, humans planning for IGF didn't just overthink stuff and die)
4. This being "accessible to the genome" in some way. Eg you could turn up and down genetic knobs that increased peoples propensity for 1,2,3.

I'm saying (1) was not present, so (1,2,3) were clearly not present.

Its possible a proxy like seeing surviving grandkids was present, but that in that case (2,3) was not present.

In that case, my theory is consistent with the evidence, but doesn't necessarily explain it better than other theories. That's fine.

Wrt your "what actually caused it"

1. Stuff like compute or intelligence limitations are subcomponents of (2,3)
2. Path dependence this is what the whole post is about in some sense. Or the brain is conservative. Similarly, I think ML models are conservative, in the sense that: if you do "light" SFT/RL models will find the explanation of the samples you gave that fits with the base-model prior, and boost the underlying circuitry.

Does this make sense?

Yeah, to be clear, I don't think that, and I think most people didn't think that, but Eliezer has sometimes said stuff that made it seem like he thought people think that. I was remembering a quote from 2:49:00 at this podcast

...effective altruists were devoting some funding to this issue basically because I brow beat them into
it. That's how I would tell the story. And a whole bunch of them, like their
theory of AI three years ago was that we probably had about 30 more years in which to work on this problem because of an elaborate argument about how large an AI needed AI model needed to be by analogy to human neurons and it would be trained via the following scaling law which would require this many gpus which at the rate of Moore's Law and this like attempted rate of software progress began 30 years
and I was like:

this entire thing falls apart at the very first joint where you're trying to make an analogy between the AI models and and the number of human neurons this entire thing is bogus it's been tried before in all these historical examples none of which were correct either and
the effect of altruists like can't tell that I'm speaking sense and that the 30-year projection is has no grasp on reality if they can't tell the difference between a good and bad argument there until you know like stuff starts to blow up 

now how do you tell who's making progress in alignment I can stand around being like no no that's wrong that's wrong too this is particularly going to fail you you know like this is how it will fail when you try it but as far as they know they're inventing Brilliant Solutions...

Indicating bioanchors make a stronger statement than it is, and that EAs are much more dogmatic about that report than most EAs are. Although to be fair, he did say probably here. 

This is not a response to your central point, but I feel like you somewhat unfairly criticize EAs for stuff like bioanchors often. You often say stuff that makes it seem like bioanchors was released, all EAs bought it wholesale, bioanchors shows we can be confident AI won't arrive before 2040 or something, and thus all EAs were convinced we don't need to worry much about AI for a few decades.

But like, I consider myself and EA, I never put much weight on bioanchors. I read the report and found it interesting, I think its useful enough (mostly as a datapoint for other arguments you might make) that I don't think was a waste of time. But not much more than that. It didn't really change my views on what should be done. Or the likelihood of AGI being developed at which points in time except on the margins. I mean thats how most people I know read that report. But I feel like you accuse people involved of having far less humility and masking way stronger stronger claims than they are.

Hmm, I don't entirely see your point. That's a good proxy, but its still a proxy. The arguments in this post indicates evolution could get desires for surviving grandchildren into us, and I think it has done that to some degree.

Edit for clarity: And by "surviving grandchildren" I mean that up to what humans could detect in ancestral environment. Eg adopted children as babies or genetically engineered ones'd still count I presume

if the AI doesn't improve its world model and decisions aka intelligence, then it's also not useful for us

This seems obviously false to me. GPT5 doesn't do this, and its relatively useful. And humans will build smarter agents than GPT5.

Kindness also may have an attractor, or due to discreteness have a volume > 0 in weight space.

I don't see why it'd have an attractor in the sense of the example I gave. 

This is the picture I have in my head. I'd put kindness like top right, and corrigibility in the top left.

Meaning, kindness and pseudo-kindness will diverge and land infinitely far apart if optimized by an AGI smart enough to do self-improvement.

But pseudo-corrigibility and corrigibility will not, because even pseudo-corrigibility can be enough to prevent an AGI from wandering into crazy land (by pursuing instrumentally convergent strategies like RSI, or just thinking really hard about its own values and its relationship with humans).