Author of "RL Environments for Agentic AI: Who Will Win the Training & Verification Layer by 2030" in Data Gravity
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Chris Zeoli as author
RL environments for training and verifying agentic AI will become the critical infrastructure bottleneck by 2030, analogous to how EDA transformed chip design and Scale AI transformed ML data.
“Author of "RL Environments for Agentic AI: Who Will Win the Training & Verification Layer by 2030" in Data Gravity”
The AI inference infrastructure market is bifurcating into two durable segments: reserved compute platforms optimized for predictability and control, and inference APIs optimized for utilization efficiency and cost abstraction.
“Author of "Inference Economics 101: Reserved Compute versus Inference APIs"”