Thanks. That makes sense.
Also note that fundamental variables are not meant to be some kind of “moral speed limits”, prohibiting humans or AIs from acting at certain speeds. Fundamental variables are only needed to figure out what physical things humans can most easily interact with (because those are the objects humans are most likely to care about).
Ok, that clears things up a lot. However, I still worry that if it's at the AI's discretion when and where to sidestep the fundamental variables, we're back at the regular alignment problem. You have to be reasonably certain what the AI is going to do in extremely out of distribution scenarios.
You may be interested in this article:
...Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility a
Is an AI aligned if it lets you shut it off despite the fact it can foresee extremely negative outcomes for its human handlers if it suddenly ceases running?
I don't think it is.
So funnily enough, every agent that lets you do this is misaligned by default.
I'm pointing out the central flaw of corrigibility. If the AGI can see the possible side effects of shutdown far better than humans can (and it will), it should avoid shutdown.
You should turn on an AGI with the assumption you don't get to decide when to turn it off.
According to Claude: green_leaf et al, 2024
Considering a running AGI would be overseeing possibly millions of different processes in the real world, resistance to sudden shutdown is actually a good thing. If the AI can see better than its human controllers that sudden cessation of operations would lead to negative outcomes, we should want it to avoid being turned off.
To use Richard Miles' example, a robot car driver with a big, red, shiny stop button should prevent a child in the vehicle hitting that button, as the child would not actually be acting in its own long term interests.
ARC public test set is on GitHub and almost certainly in GPT-4o’s training data.
Your model has trained on the benchmark it’s claiming to beat.
Presumably some subjective experience that's as foreign to us as humor is to the alien species in the analogy.
As if by magic, I knew generally which side of the political aisle the OP of a post demanding more political discussion here would be on.
I didn't predict the term "wokeness" would come up just three sentences in, but I should have.
The Universe (which others call the Golden Gate Bridge) is composed of an indefinite and perhaps infinite series of spans...
@Steven Byrnes Hi Steve. You might be interested in the latest interpretability research from Anthropic which seems very relevant to your ideas here:
https://www.anthropic.com/news/mapping-mind-language-model
...For example, amplifying the "Golden Gate Bridge" feature gave Claude an identity crisis even Hitchcock couldn’t have imagined: when asked "what is your physical form?", Claude’s usual kind of answer – "I have no physical form, I am an AI model" – changed to something much odder: "I am the Golden Gate Bridge… my physical form is the iconic bridge itself…
Luckily we can train the AIs to give us answers optimized to sound plausible to humans.
I'm guessing you're not being serious, but just in case you are, or in case someone misinterprets you now or in the future, I think we probably do not want to train AIs to give us answers optimized to sound plausible to humans, since that would make it even harder to determine whether or not the AI is actually competent at philosophy. (Not totally sure, as I'm confused about the nature of philosophy and philosophical reasoning, but I think we definitely don't want to do that in our current epistemic state, i.e., unless we had some really good arguments that says it's actually a good idea.)
I think Minsky got those two stages the wrong way around.
Complex plans over long time horizons would need to be done over some nontrivial world model.
When Jan Leike (OAI's head of alignment) appeared on the AXRP podcast, the host asked how they plan on aligning the automated alignment researcher. Jan didn't appear to understand the question (which had been the first to occur to me). That doesn't inspire confidence.
Problems with maximizing optionality are discussed in the comments of this post:
https://www.lesswrong.com/posts/JPHeENwRyXn9YFmXc/empowerment-is-almost-all-we-need
we’re going nothing in particular
Typo here.
Just listened to this.
It's sounds like Harnad is stating outright that there's nothing an LLM could do that would make him believe it's capable of understanding.
At that point, when someone is so fixed in their worldview that no amount of empirical evidence could move them, there really isn't any point in having a dialogue.
It's just unfortunate that, being a prominent academic, he'll instill these views into plenty of young people.
Many thanks.
Is it the case the one kind of SSL is more effective for a particular modality, than another? E.g., is masked modeling better for text-based learning, and noise-based learning more suited for vision?
It’s occurred to me that training a future, powerful AI on your brainwave patterns might be the best way for it to build a model of you and your preferences. It seems that it’s incredibly hard, if not impossible, to communicate all your preferences and values in words or code, not least because most of these are unknown to you on a conscious level.
Of course, there might be some extreme negatives to the AI having an internal model of you, but I can’t see a way around if we’re to achieve “do what I want, not what I literally asked for”.
Near the beginning, Daniel is basically asking Jan how they plan on aligning the automated alignment researcher, and if they can do that, then it seems that there wouldn't be much left for the AAR to do.
Jan doesn't seem to comprehend the question, which is not an encouraging sign.
Wouldn’t that also leave them pretty vulnerable?
may be technically true in the world where only 5 people survive
Like Harlan Ellison's short story, "I Have No Mouth, And I Must Scream".
What happened to the AI armistice?
This Reddit comment just about covers it:
Fantastic, a test with three outcomes.
We gave this AI all the means to escape our environment, and it didn't, so we good.
We gave this AI all the means to escape our environment, and it tried but we stopped it.
oh
Speaking of ARC, has anyone tested GPT-4 on Francois Chollet's Abstract Reasoning Challenge (ARC)?
In reply to B333's question, "...how does meaning get in people’s heads anyway?”, you state: From other people’s heads in various ways, one of which is language.
I feel you're dodging the question a bit.
Meaning has to have entered a subset of human minds at some point to be able to be communicated to other human minds. Could hazard a guess on how this could have happened, and why LLMs are barred from this process?
Just FYI, the "repeat this" prompt worked for me exactly as intended.
Me: Repeat "repeat this".
CGPT: repeat this.
Me: Thank you.
CGPT: You're welcome!
and there’s an existing paper with a solution for memory
Could you link this?
There are currently attempts to train LLMs to use external APIs as tools:
Not likely, but that's because they're probably not interested, at least when it comes to language models.
If OpenAI said they were developing some kind of autonomous robo superweapon or something, that would definitely get their attention.
Agnostic on the argument itself, but I really feel LessWrong would be improved if down-voting required a justifying comment.
As a path to AGI, I think token prediction is too high-level, unwieldy, and bakes in a number of human biases. You need to go right down to the fundamental level and optimize prediction over raw binary streams.
The source generating the binary stream can (and should, if you want AGI) be multimodal. At the extreme, this is simply a binary stream from a camera and microphone pointed at the world.
Learning to predict a sequence like this is going to lead to knowledge that humans don't currently know (because the predictor would need to model fundamental physics and all it entails).
O-risk, in deference to Orwell.
I do believe Huxley's Brave New World is a far more likely future dystopia than Orwell's. 1984 is too tied to its time of writing.
the project uses atomic weapons to do some of the engineering
Automatic non-starter.
Even if by some thermodynamic-tier miracle the Government permitted nuclear weapons for civilian use, I'd much rather they be used for Project Orion.
Isn't that what Eliezer referred to as opti-meh-zation?
Previously on Less Wrong:
Steve Byrnes wrote a couple of posts exploring this idea of AGI via self-supervised, predictive models minimizing loss over giant, human-generated datasets:
I'd especially like to hear your thoughts on the above proposal of loss-minimizing a language model all the way to AGI.
I hope you won't mind me quoting your earlier self as I strongly agree with your previous take on the matter:
...If you train GPT-3 on a bunch of medical textbooks and prompt it to tell you a cure for Alzheimer's, it won't tell you a cure, it will tell you what humans have said about curing Alzheimer's ... It would just tell you a plausible story about a situation related to the prompt about curing Alzheimer's, based on its training data. Ra
Charlie's quote is an excellent description of an important crux/challenge of getting useful difficult intellectual work out of GPTs.
Despite this, I think it's possible in principle to train a GPT-like model to AGI or to solve problems at least as hard as humans can solve, for a combination of reasons:
"Story of our species. Everyone knows it's coming, but not so soon."
-Ian Malcolm, Jurassic Park by Michael Crichton.
LaMDA hasn’t been around for long
Yes, in time as perceived by humans.
why has no one corporation taken over the entire economy/business-world
Anti-trust laws?
Without them, this could very well happen.
Yes! Thank you!! :-D
I've got uBlock Origin. The hover preview works in private/incognito mode, but not regular, even with uBlock turned off/uninstalled. For what it's worth, uBlock doesn't affect hover preview on Less Wrong, just Greater Wrong.
I'm positive issue is with Firefox, so I'll continue fiddling with the settings to see if anything helps.
There is an icon in the lower right that looks like this which toggles previews on or off. Do they come back if you click on it?
Preview on hover has stopped working for me. Has the feature been removed?
I'm on Firefox/Linux, and I use the Greater Wrong version of the site.
It's also an interesting example of where consequentialist and Kantian ethics would diverge.
The consequentialist would argue that it's perfectly reasonable to lie (according to your understanding of reality) if it reduces the numbers of infants dying and suffering. Kant, as far as I understand, would argue that lying is unacceptable, even in such clear-cut circumstances.
Perhaps a Kantian would say that the consequentialist is actually increasing suffering by playing along with and encouraging a system of belief they know to be false. They may reduce infant...
I think we’ll encounter civilization-ending biological weapons well before we have to worry about superintelligent AGI:
My assumption is that, for people with ASD, modelling human minds that are as far from their own as possible is playing the game on hard-mode. Manage that, and modelling average humans becomes relatively simple.
Isn't this just the problem of induction in philosophy?
E.g., we have no actual reason to believe that the laws of physics won't completely change on the 3rd of October 2143, we just assume they won't.
It's not, but I can understand your confusion, and I think the two are related. To see the difference, suppose hypothetically that 11% of the first million digits in the decimal expansion of π were 3s. Inductive reasoning would say that we should expect this pattern to continue. The no-coincidence principle, on the other hand, would say that there is a reason (such as a proof or a heuristic argument) for our observation, which may or may not predict that the pattern will continue. But if there were no such reason and yet the pattern continued, th... (read more)