The Claude plays pokemon discourse makes me feel out of touch because I don't understand how this is not an update people had with chess playing LLMs. If anything, I think the data contamination is worse for pokemon because of gamefaq and other guides online.
I think people are mistaking benchmarks and trailheads. Maths benchmarks are important because they theoretically speed up AI research and benchmark to useful intelligence. Claude playing pokemon doesn't tell you much because it's not a map on intelligence nor of generalisation.
It's a good unhobbling eval, because it's a task that should be easy for current frontier LLMs at System 1 level, and they only fail because some basic memory/adaptation faculties that humans have are outright missing for AIs right now. No longer failing will be a milestone in no longer obviously missing such features (assuming the improvements are to general management of very long context, and not something overly eval-specific).
Sorry, but why did you connect apathy and lying-flat [sic] with fast-follower culture. Lying flat or tang ping is about youth apathy and nihilism about the job market and existential angst about life in the 21st century. It's not about corporate or industrial culture from the top end or specific technological political economy strategies.
I don't know if this is helpful but as someone who was quite good at competitive Pokemon during their teenage years and also still keeps up with nuzlocking type things for fun, I would note that Pokemon's game design is made to be a low context intensity RPG especially in early generations where the linearity is pushed to allow kids to do it.
If your point holds true on agency, I think the more important pinch points will be Lavender Town and Sabrina because those require backtracking through the storyline to get things.
I think mid-late game GSC would also be important to try because there are huge level gaps and transitions in the storyline that would make it hard to progress.
Sorry but aren't we in a fast takeoff world at the point of WBE. What's the disjunctive world of no recursive self-improvement and WBE?
Yeah, re-reading I realise I was unclear. Given your claim: "by the time we get to 2000 in that, such AGIs will be automating huge portions of AI R&D,". I'm asking the following:
Sorry for a slightly dumb question but in your part of the table you set 2000 as the year before singularity and your explanation is that 2000-second tasks jump to singularity. Is your model of fast take-off then contingent on there being more special sauce for intelligence being somewhat redundant as a crux because recursive self-improvement is just much more effective. I'm having trouble envisioning a 2000-second task + more scaling and tuning --> singularity.
Additional question is what your model of falsification is for let's say 25-second task...
Can you share the difference between the times it is aware (I know 33% is the floor) and the times where Claude is not aware/sandbagging?