Heated, tense arguments can often be unproductive and unpleasant. Neither side feels heard, and they are often working desperately to defend something they feel is very important. Ruby explores this problem and some solutions.
Epistemic status: exploratory thoughts about the present and future of AI sexting.
OpenAI says it is continuing to explore its models’ ability to generate “erotica and gore in age-appropriate contexts.” I’m glad they haven’t forgotten about this since the release of the first Model Spec, because I think it could be quite interesting, and it’s a real challenge in alignment and instruction-following that could have other applications. In addition, I’ve always thought it makes little logical sense for these models to act like the birds and the bees are all there is to human sexuality. Plus, people have been sexting with ChatGPT and just ignoring the in-app warnings anyway.
One thing I’ve been thinking about a lot is what limits a commercial NSFW model should have. In my experience,...
At the same time, empowering only the user and making the assistant play along with almost every kind of legal NSFW roleplaying content (if that’s what OpenAI ends up shipping) seems very undesirable in the long term.
Why? Do dildos sometimes refuse consent? Would it be better for humanity if they did? Should erotic e-books refuse to be read on certain days? Should pornography be disabled on screens if the user is not sufficiently respectful? What about pornography generated by AIs?
Similar to other people's shortform feeds, short stuff that people on LW might be interested in, but which doesn't feel like it's worth a separate post. (Will probably be mostly cross-posted from my Facebook wall.)
Hmm I guess that didn't properly convey what I meant. More like, LLMs are general in a sense, but in a very weird sense where they can perform some things at a PhD level while simultaneously failing at some elementary-school level problems. You could say that they are not "general as in capable of learning widely runtime" but "general as in they can be trained to do an immensely wide set of tasks at training-time".
And this is then a sign that the original concept is no longer very useful, since okay LLMs are "general" in a sense. But probably if you'd told...
Epistemic status: You probably already know if you want to read this kind of post, but in case you have not decided: my impression is that people are acting very confused about what we can conclude about scaling LLMs from the evidence, and I believe my mental model cuts through a lot of this confusion - I have tried to rebut what I believe to be misconceptions in a scattershot way, but will attempt to collect the whole picture here. I am a theoretical computer scientist and this is a theory. Soon I want to do some more serious empirical research around it - but be aware that most of my ideas about LLMs have not had the kind of careful, detailed contact with reality that I...
Yes, that is what I think.
[legal status: not financial advice™]
Already entry level jobs, which doesn't matter for crypto markets that much.[2]
But judging by progress at other tasks AI climb the seniority ladder to where most crypto holders are within the next few years. SWE Bench Verified went from single digit %s to 64% in a year and a bit, and the METR evals are not looking hopeful for humanity's lead. Tech giants are doing increasing amounts of their work with AI.[3]
Many...
'Poor' people no longer starve in winter when their farm's food storage runs out.
Homeless people sometimes starve, and also freeze in winter.
(But I agree that the fraction of the starving poor was much larger in the past.)
The goal of this post is to discuss the so-called “sharp left turn”, the lessons that we learn from analogizing evolution to AGI development, and the claim that “capabilities generalize farther than alignment” … and the competing claims that all three of those things are complete baloney. In particular,
Curated. This post does at least two things I find very valuable:
And so I think that this post both describes and advances the canonical "state of the argument" with respect to the Sharp Left Turn (and similar concerns). I hope that other people will also find it helpful in improving their understanding of e.g. objections to basic evolutionary analogies (and why those objections shouldn't make you very optimistic).
[Thanks to Steven Byrnes for feedback and the idea for section §3.1. Also thanks to Justis from the LW feedback team.]
Remember this?
Or this?
The images are from WaitButWhy, but the idea was voiced by many prominent alignment people, including Eliezer Yudkowsky and Nick Bostrom. The argument is that the difference in brain architecture between the dumbest and smartest human is so small that the step from subhuman to superhuman AI should go extremely quickly. This idea was very pervasive at the time. It's also wrong. I don't think most people on LessWrong have a good model of why it's wrong, and I think because of this, they don't have a good model of AI timelines going forward.
I would find this post much more useful to engage with if you more concretely described the type of tasks that you think AIs will remain bad and gave a bunch of examples. (Or at least made an argument for why it is hard to construct examples if that is your perspective.)
I think you're pointing to a category like "tasks that require lots of serial reasoning for humans, e.g., hard math problems particularly ones where the output should be a proof". But, I find this confusing, because we've pretty clearly seen huge progress on this in the last year such that ...
This post is inspired by the post "Why it's so hard to talk about Consciousness" by Rafael Harth. In that post, Harth says that the people who participate in debates about consciousness can be roughly divided into two "camps":
Camp #1 tends to think of consciousness as a non-special high-level phenomenon. Solving consciousness is then tantamount to solving the Meta-Problem of consciousness, which is to explain why we think/claim to have consciousness. In other words, once we've explained the full causal chain that ends with people uttering the sounds kon-shush-nuhs, we've explained all the hard observable facts, and the idea that there's anything else seems dangerously speculative/unscientific. No complicated metaphysics is required for this approach.
...Conversely, Camp #2 is convinced that there is an experience thing that exists in
I've got an idea what meditation people might be talking about with doing away with the self. Once you start thinking about what the lower-level mechanics of the brain are like, you start thinking about representations. Instead of the straightforward assertion "there's a red apple on that table", you might start thinking "my brain is holding a phenomenal representation of a red apple on a table". You'll still assume there's probably a real apple out there in the world too, though if you're meditating you might specifically try to not assign meanings to phe...