This response video has put Siliconversations onto my radar. They were only mentioned briefly as one of the multiple people claiming that AGI is possible, and this response was so bad that it caused me to go digging for a few minutes into their backers.

Control AI, stylized as “CONTROL/AI” or “control”, is now interesting as well. They appear to have funded at least some of these videos, was definitely credited in one Hank Green video, and got a footbath from Siliconversations in the linked video. We also already know some stuff about Future of Life Institute, who funded Siliconversations’ prior doomer video and is run by ethnonationalist Max Tegmark. @[email protected] might know more about how the money is moving.

I’ve finished grading all of the entries so far. I don’t think that we’ll get any more, so here’s a preview of the upcoming blog post.

The tier listings are as follows:

• B tier: Corbin S. (Task 1), Corbin S. (Task 2), Corbin S. (Task 3)
• C tier: Piper M. (Task 1)

Admittedly, we didn’t get a whole lot of players, but that’s it. That’s the entire tier listing. I had three things I wanted to do in my spare time. I did them and got an average ranking based on my average predictions of the future; I met expectations. Piper also placed and I greatly appreciate her sportsmanship here.

My solutions are available as notes and source code. For Task 1, I have three main commits: one, two, three, and a bugfix. For Task 2, the commits are internal to my homelab, but I do have notes and source code. Finally, for Task 3, I put the entire repository into a flat gist including notes, source code, and Nix flake.

It occurs to me that this audience might not immediately understand how hard the chosen tasks are. I was fairly adversarial with my task selection.

Two of them are in RPython, an old dialect of Python 2.7 that chatbots will have trouble emitting because they’re trained on the incompatible Python 3.x lineage. The odd task out asks for the bot to read Raku, which is as tough as its legendary predecessor Perl 5, and to write low-level code that is very prone to crashing. All three tasks must be done relative to a Nix flake, which is easy for folks who are used to it but not typical for bots. The third task is an open-ended optimization problem where a top score will require full-stack knowledge and a strong sense of performance heuristics; I gave two examples of how to do it, but by construction neither example can result in an S-tier score if literally copied.

This test is meant to shame and embarrass those who attempt it. It also happens to be a slice of the stuff that I do in my spare time.

The author also proposes a framework for analyzing claims about generative AI. I don’t know if I endorse it fully, but I agree that each of the four talking points represents a massive failure of understanding. Their LIES model is:

• Lethality: the bots will kill us all
• Inevitability: the bots are unstoppable and will definitely be created in the future
• Exceptionalism: the bots are wholly unlike any past technology and we are unprepared to understand them
• Superintelligent: the bots are better than people at thinking

I would add to this a Plausibility or Personhood or Personality: the incorrect claim that the bots are people. Maybe call it PILES.