Agreed code as coordination mechanism

Code nowadays can do lots of things, from buying items to controlling machines. This presents code as a possible coordination mechanism, if you can get multiple people to agree on what code should be run in particular scenarios and situations, that can take actions on behalf of those people that might need to be coordinated.

This would require moving away from the “one person committing code and another person reviewing” code model. 

This could start with many people reviewing the code, people could write their own t... (read more)

What would a "qualia-first-calibration" app would look like?

Or, maybe: "metadata-first calibration"

The thing with putting probabilities on things is that often, the probabilities are made up. And the final probability throws away a lot of information about where it actually came from.

I'm experimenting with primarily focusing on "what are all the little-metadata-flags associated with this prediction?". I think some of this is about "feelings you have" and some of it is about "what do you actually know about this topic?"

The sort of app I'm imagining would he... (read more)

So the usual refrain from Zvi and others is that the specter of China beating us to the punch with AGI is not real because limits on compute, etc. I think Zvi has tempered his position on this in light of Meta's promise to release the weights of its 400B+ model. Now there is word that SenseTime just released a model that beats GPT-4 Turbo on various metrics. Of course, maybe Meta chooses not to release its big model, and maybe SenseTime is bluffing--I would point out though that Alibaba's Qwen model seems to do pretty okay in the arena...anyway, my point is that I don't think the "what if China" argument can be dismissed as quickly as some people on here seem to be ready to do.

I think that people who work on AI alignment (including me) have generally not put enough thought into the question of whether a world where we build an aligned AI is better by their values than a world where we build an unaligned AI. I'd be interested in hearing people's answers to this question. Or, if you want more specific questions:

• By your values, do you think a misaligned AI creates a world that "rounds to zero", or still has substantial positive value?
• A common story for why aligned AI goes well goes something like: "If we (i.e. humanity) align AI

My current main cruxes:

1. Will AI get takeover capability? When?
2. Single ASI or many AGIs?
3. Will we solve technical alignment?
4. Value alignment, intent alignment, or CEV?
5. Defense>offense or offense>defense?
6. Is a long-term pause achievable?

If there is reasonable consensus on any one of those, I'd much appreciate to know about it. Else, I think these should be research priorities.

AGI doom by noise-cancelling headphones:                                                                            

ML is already used to train what sound-waves to emit to cancel those from the environment. This works well with constant high-entropy sound waves easy to predict, but not with low-entropy sounds like speech. Bose or Soundcloud or whoever train very hard on... (read more)

I'm not alexithymic; I directly experience my emotions and have, additionally, introspective access to my preferences. However, some things manifest directly as preferences which I have been shocked to realize in my old age, were in fact emotions all along. (In rare cases these are stronger than the ones directly-felt even, despite reliably seeming on initial inspection to be simply neutral metadata).

I'm against intuitive terminology [epistemic status: 60%] because it creates the illusion of transparency; opaque terms make it clear you're missing something, but if you already have an intuitive definition that differs from the author's it's easy to substitute yours in without realizing you've misunderstood.

Research Writing Workflow: First figure stuff out

• Do research and first figure stuff out, until you feel like you are not confused anymore.
• Explain it to a person, or a camera, or ideally to a person and a camera.
  • If there are any hiccups expand your understanding.
  • Ideally, as the last step, explain it to somebody whom you have not ever explained it to.
• Only once you made a presentation without hiccups you are ready to write post.
  • If you have a recording this is useful as a starting point.

Nathan and Carson's Manifold discussion.

As of the last edit my position is something like:

"Manifold could have handled this better, so as not to force everyone with large amounts of mana to have to do something urgently, when many were busy. 

Beyond that they are attempting to satisfy two classes of people:

• People who played to donate can donate the full value of their investments
• People who played for fun now get the chance to turn their mana into money

To this end, and modulo the above hassle this decision is good. 

It is unclear to me whether there... (read more)

Have there been any great discoveries made by someone who wasn't particularly smart?

This seems worth knowing if you're considering pursuing a career with a low chance of high impact. Is there any hope for relatively ordinary people (like the average LW reader) to make great discoveries?

I expect large parts of interpretability work could be safely automatable very soon (e.g. GPT-5 timelines) using (V)LM agents; see A Multimodal Automated Interpretability Agent for a prototype. 

Notably, MAIA (GPT-4V-based) seems approximately human-level on a bunch of interp tasks, while (overwhelmingly likely) being non-scheming (e.g. current models are bad at situational awareness and out-of-context reasoning) and basically-not-x-risky (e.g. bad at ARA).

Given the potential scalability of automated interp, I'd be excited to see plans to use large amo... (read more)

Sometimes a vague phrasing is not an inaccurate demarkation of a more precise concept, but an accurate demarkation of an imprecise concept

Today I learned that being successful can involve feelings of hopelessness.

When you are trying to solve a hard problem, where you have no idea if you can solve it, let alone if it is even solvable at all, your brain makes you feel bad. It makes you feel like giving up.

This is quite strange because most of the time when I am in such a situation and manage to make a real efford anyway I seem to always suprise myself with how much progress I manage to make. Empirically this feeling of hopelessness does not seem to track the actual likelyhood that you will completely fail.

Classic type of argument-gone-wrong (also IMO a way autistic 'hyperliteralism' or 'over-concreteness' can look in practice, though I expect that isn't always what's behind it): Ashton makes a meta-level point X based on Birch's meta point Y about object-level subject matter Z. Ashton thinks the topic of conversation is Y and Z is only relevant as the jumping-off point that sparked it, while Birch wanted to discuss Z and sees X as only relevant insofar as it pertains to Z. Birch explains that X is incorrect with respect to Z; Ashton, frustrated, reiterates ... (read more)

I wish there were an option in the settings to opt out of seeing the LessWrong reacts. I personally find them quite distracting, and I'd like to be able to hover over text or highlight it without having to see the inline annotations.