Filip Sondej

github.com/filyp

# Wiki Contributions

Filip SondejΩ110

What if we constrain v to be in some subspace that is actually used by the MLP? (We can get it from PCA over activations on many inputs.)

This way v won't have any dormant component, so the MLP output after patching also cannot use that dormant pathway.

I wanna link to my favorite one: consciousness vs replicators. It doesn't really fit into this grid, but I think it really is the ultimate conflict.

(You can definitely skip the first 14 min of this video, as it's just ranking people's stages of development. Maybe even first 33 min if you wanna go straight to the point.)

I wonder what would happen if we run the simple version of that algorithm on LW comments. So that votes would have "polarity", and so each comment would have two vote-counts, let's say orange count and blue count. (Of course that would be only optionally enabled.)

Then we could sort the comments by the minimum of these counts, descending.

(I think it makes more sense to train it per post than globally. But then it would be useful only on very popular posts with lots of comments.)

Thanks, that's terrifying.

I hope we invent mindmelding before we invent all this. Maybe if people can feel those states themselves, they won't let the worst of them happen.

Unfortunately I didn't have any particular tasks in mind when I wrote it. I was vaguely thinking about settings as in:

Now that I though about it, for this particular transformers vs mamba experiment, I'd go with something even simpler. I want a task that is very easy sequentially, but hard to answer immediately. So for example a task like:

x = 5
x += 2
x *= 3
x **= 2
x -= 3
...


and then have a CoT:

after x = 5
5
after x += 2
7
...


And then we intervene on CoT to introduce some error in one operation, but still ask of the model to give the correct answer at the end. (Despite all steps after the error being irrelevant.) We can go even further and train the models to give the correct answer after inadequate CoT. And have a curriculum where at first it only needs to do one hidden operation, later two, and so on.

(It's an unrealistic setting, but the point is rather to check if the model is able at all to learn hidden sequential reasoning.)

Now, my hypothesis is that transformers will have some limited sequence length for which they can do it (probably smaller than their number of layers), but mamba won't have a limit.

I was working on this for six months

Can you say what you tried in these six months and how did it go?

Yeah, true. But it's also easier to do early, when no one is that invested in the hidden-recurrence architectures, and so there's less resistance, it doesn't break anyone's plans.

Maybe a strong experiment would be to compare mamba-3b and some SOTA 3b transformer, trained similarly, on several tasks where we can evaluate CoT faithfulness. (Although maybe at 3b capability level we won't see clear differences yet.) The hard part would be finding the right tasks.

the natural language bottleneck is itself a temporary stage in the evolution of AI capabilities. It is unlikely to be an optimal mind design; already many people are working on architectures that don't have a natural language bottleneck

This one looks fatal. (I think the rest of the reasons could be dealt with somehow.)

What existing alternative architectures do you have in mind? I guess mamba would be one?

Do you think it's realistic to regulate this? F.e. requiring that above certain size, models can't have recurrence that uses a hidden state, but recurrence that uses natural language (or images) is fine. (Or maybe some softer version of this, if alignment tax proves too high.)

I like initiatives like these. But they have a major problem, that at the beginning no users will use it because there's no content, and no content is created because there are no users.

To have a real shot at adoption, you need to either initially populate the new system with content from existing system (here LLMs could help solve compatibility issues), or have some bridge that mirrors (some) activity between these systems.

(There are examples of systems that kicked off from zero, but you need to be lucky or put huge effort in sparking adoption.)

Yeah, those star trajectories definitely wouldn't be stable enough.

I guess even with that simpler maneuver (powered flyby near a black hole), you still need to monitor all the stuff orbiting there and plan ahead, otherwise there's a fair chance you'll crash into something.

I wanted to give it a shot and made GPT4 to deceive the user: link.

When you delete that system prompt it stops deceiving.

But GPT had to be explicitly instructed to disobey the Party. I wonder if it could be done more subtly.