The bottleneck to AI progress is not primarily researcher headcount (only 20-30 people on core pre-training teams at major labs, and companies don't aggressively hire more PhDs despite having capital), but rather a combination of compute resources, research taste, and serial speed of thinking; parallel multiplication of researcher count has diminishing returns.