Large AI swarms show power, not cheap performance
A 10,000-agent AI swarm can attack hard problems, but its roughly $20 million API bill makes it a demonstration of expensive compute, not a practical $20/month product. Toby Ord frames swarms as inference-scaling: instead of one agent spending longer on a task, many agents work together, sending 5 million messages and using 300 billion tokens to solve a version of the Navier-Stokes problem in 88 hours. The catch is steep diminishing returns as more agents are added.