Comment by naishoya

People are ultimately capable of self deception. Believing that one is 'generally ... substantively above average on human benchmarks' may be more indicative of the brittleness of the claimant's human benchmarks.

Your observations expose the brittleness of the benchmarks being used for Fable, where the 'reasonable confident' claimant is working in the problem space of those two benchmarks, and you're demonstrating the failure at depth of the very capability facade for the model.

Sure, both the model and the confident human get the first layer right in some benchmark, but at least the model, and probably the human as well reach a collapsing probability of accuracy quite quickly. They may be completely and unconditionally right that Fable is more intelligent than they are, but that has little relevance at intelligence in depth as measured against your hobbies and the risk of unsafe or false responses.

Being smarter than a select group of people under test conditions is not conclusive regarding AGI. Moving the goalposts to declare AGI via a shallow benchmark, when a model could be proven wrong by almost anyone with basic competency given a few turns of iterative depth is where the 'grift' resides.

We're so far from anything approaching actual AGI, and it is highly speculative to infer that the current approach to Machine Learning as applied in LLM is even on a path that leads to AGI. But sales and promotions teams gotta pose, and we can all hate both the game and the players.