Should be fixed now, thanks for the heads-up. The same problem also broke images on a bunch of my other old posts; please do leave comments if you find more which I haven’t fixed yet.
johnswentworth
Karma: 44,799
When Are Circular Definitions A Problem?
Yeah, that’s one of the main things which the “causal models as programs” thing is meant to capture, especially in conjunction with message passing and caching. The whole thing is still behaviorally one big model insofar as the cache is coherent, but the implementation is a bunch of little sparsely-interacting submodel-instances.
I think there might be a simple miscommunication here: in our title and report we use “talent needs” to refer to “job and funding opportunities that could use talent.” Importantly, we generally make a descriptive, not a normative, claim about the current job and funding opportunities.
I think the title of this post is actively misleading if that’s what you’re trying to convey. “Defining” a term to mean something specific thing, which does not match how lots of readers will interpret it (especially in the title!), will in general make your writing not communicate what your “definition” claims to be trying to communicate.
If the post is about job openings and grant opportunities, then it should say that at the top, rather than “talent needs”.
Personally, I consider model-based RL to be not RL at all. I claim that either one needs to consider model-based RL to be not RL at all, or one needs to accept such a broad definition of RL that the term is basically-useless (which I think is what porby is saying in response to this comment, i.e. “the category of RL is broad enough that it belonging to it does not constrain expectation much in the relevant way”).
This model does allow for that. :) We can use this model whenever our two agents agree predictively about some parts of the world X; it’s totally fine if our two agents learned their models from different sources and/or make different predictions about other parts of the world.
Why Care About Natural Latents?
You are a scholar and a gentleman.
Way back in the halcyon days of 2005, a company called Cenqua had an April Fools’ Day announcement for a product called Commentator: an AI tool which would comment your code (with, um, adjustable settings for usefulness). I’m wondering if (1) anybody can find an archived version of the page (the original seems to be gone), and (2) if there’s now a clear market leader for that particular product niche, but for real.
The word for a drug that causes loss of memory is “amnestic”, not “amnesic”. The word “amnesic” is a variant spelling of “amnesiac”, which is the person who takes the drug.
Thanks! Fixed now.
Oh yeah, I guess that could be a learning effect. When reading it I assumed the lack of need for repeating the numbers was just because the drug was wearing off.
Another class of applications which we discussed at the retreat: person 1 takes the amnestic, person 2 shares private information with them, and then person 1 gives their reaction to the private information. Can be used e.g. for complex negotiations: maybe it is in our mutual best interest to make some deal, but in order for me to know that I’d need some information which you don’t want to share with me, so I take the drug, you share the information, and I record some verified record of myself saying “dear future self, you should in fact take this deal”.
… which is cool in theory but I would guess not of high immediate value in practice, which is why the post didn’t focus on it.
I would love to hear suggestions for other things I could try. If you have any, let me know in a comment!
Some Experiments I’d Like Someone To Try With An Amnestic
Do you know what the drug was which did this?
Nitpick: you’re talking about the discovery of the structure of DNA; it was already known at that time to be the particle which mediates inheritance IIRC.
I buy this argument.
I buy this argument.
I don’t buy mathematical equivalence as an argument against, in this case, since the whole point of the path integral formulation is that it’s mathematically equivalent but far simpler conceptually and computationally.
Should be fixed now, thanks for flagging.