Congrats! Could you say more about why you decided to add evaluations in particular as a new week?
Do any of your experiments compare the sample efficiency of SFT/DPO/EI/similar to the same number of samples of simple few-shot prompting? Sorry if I missed this, but it wasn't apparent at first skim. That's what I thought you were going to compare from the Twitter thread: "Can fine-tuning elicit LLM abilities when prompting can't?"
What do you think about pausing between AGI and ASI to reap the benefits while limiting the risks and buying more time for safety research? Is this not viable due to economic pressures on whoever is closest to ASI to ignore internal governance, or were you just not conditioning on this case in your timelines and saying that an AGI actor could get to ASI quickly if they wanted?
Thanks! I wouldn't say I assert that interpretability should be a key focus going forward, however--if anything, I think this story shows that coordination, governance, and security are more important in very short timelines.
Good point--maybe something like "Samantha"?
Ah, interesting. I posted this originally in December (e.g. older comments), but then a few days ago I reposted it to my blog and edited this LW version to linkpost the blog.
It seems that editing this post from a non-link post into a link post somehow bumped its post date and pushed it to the front page. Maybe a LW bug?
Related work
Nit having not read your full post: Should you have "Without specific countermeasures, the easiest path to transformative AI likely leads to AI takeover" in the related work? My mind pattern-matched to that exact piece from reading your very similar title, so my first thought was how your piece contributes new arguments.
If true, this would be a big deal: if we could figure out how the model is distinguishing between basic feature directions and other directions, we might be able to use that to find all of the basic feature directions.
Or conversely, and maybe more importantly for interp, we could use this to find the less basic, more complex features. Possibly that would form a better definition for "concepts" if this is possible.
Suppose has a natural interpretation as a feature that the model would want to track and do downstream computation with, e.g. if a = “first name is Michael” and b = “last name is Jordan” then can be naturally interpreted as “is Michael Jordan”. In this case, it wouldn’t be surprising the model computed this AND as and stored the result along some direction independent of and . Assuming the model has done this, we could then linearly extract with the probe
for some appropriate and .[7]
Should the be inside the inner parentheses, like for ?
In the original equation, if AND are both present in , the vectors , , and would all contribute to a positive inner product with , assuming . However, for XOR we want the and inner products to be opposing the inner product such that we can flip the sign inside the sigmoid in the AND case, right?
Traditionally, most people seem to do this through academic means. I.e. take those 1-2 courses at a university, then find fellow students in the course or grad students at the school interested in the same kinds of research as you and ask them to work together. In this digital age, you can also do this over the internet to not be restricted to your local environment.
Nowadays, ML safety in particular has various alternative paths to finding collaborators and mentors: