4 posts
Dharma AI's VocabX rebuilds a model's vocabulary around cost per token rather than frequency—and slashes production inference costs by 77% without touching the base model.
Ai2 ships a continent-scale geospatial inference platform that processes dozens of terabytes in ~24 hours. The infrastructure choices reveal hard truths about production ML.
Ai2's maritime agent Shippy isn't about the model—it's about reliability, deterministic tools, sandboxed execution, and real evals. Here's what building an agent for high-stakes decisions actually looks like.
IBM Research tried routing requests across Claude, GPT-4, and Opus in production agentic systems. Token pricing didn't predict actual cost. Task difficulty didn't predict model fit. Here's why.