Topic
Gemini 4 Argon
2 episodes
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Overview: Long Horizon training
We slow down on long-horizon training: what it means to train a model for the whole arc of a task instead of the next shiny step. We use the repo-fix mental model, then walk through rewards, credit assignment, curricula, decomposition, and why this is still very much live in agent work.
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Gemini 4 Argon: our next era of frontier intelligence
Onyx and Echo dig into Google’s Gemini 4 Argon announcement and land on the same uneasy place: the real story is not “bigger model,” it’s a model being shaped into a controlled workflow engine for expensive, long-horizon work. They focus on the 1 million token output cap, the aggressive introductory pricing, the internal Google use cases, and the cybersecurity-first rollout, while pushing on where benchmark claims still need real-world proof.