From a mathematical point of view there are two factors: (1) Initial prior capability of prediction from the human agents and (2) Acceleration in the predicted event. Now we examine the result under such a model and conclude that:
The more prior predictive power of human agents imply the more a posterior acceleration of progress in LLMs (math capability).
Here we are supposing that the increase in training data is not the main explanatory factor.
This example is the gem of a general framework for assessing acceleration in LLM progress, and I think its application to many data points could give us valuable information.
The more prior predictive power of human agents imply the more a posterior acceleration of progress in LLMs (math capability).
Here we are supposing that the increase in training data is not the main explanatory factor.
This example is the gem of a general framework for assessing acceleration in LLM progress, and I think its application to many data points could give us valuable information.