I'll take this one.
There are many different types of precursors. Some are hardware, like data centres or the way to build GPUs into the supply chain and things like this. Some are software, like the types of AI systems that have been built and the type of scaffolding you have on top of them.
A deep thing that is quite important to understand is that this is a moving target. As time passes, it gets easier to build superintelligent systems, and more things get into the category of precursors. This is also why we believe there is an urgency and that we should tackle this as soon as possible.
Right now, we can get away with, for instance, preventing research programs that are aimed at building superintelligent systems. We should also focus on limiting the open-sourcing of models, because once they're there, you cannot take them back. It is the same for data centres. For every data centre, there should be stop buttons and kill switches. There should be clear regimes for what can be done with them and so on. These are the types of regulations that we should have on precursors.
Fundamentally, it is a moving target. As the technology changes and as the way the technology is built changes, the target itself changes. The precursors of 15 years ago were very different than they are now, and it would have been much simpler to tackle the problem 15 years ago.