17 summarised stories about Agent Training, each linking back to the original source. Browse all topics →
OpenAI Blog 8 years ago
Researchers proposed a safety technique where AI agents debate each other on topics while a human judge determines the winner. The method aims to make AI reasoning more transparent and auditable by forcing agents to justify their positions against adversarial scrutiny. This approach could reduce AI deception risks by creating incentives for agents to produce honest, explainable arguments rather than manipulate human evaluators.
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TLDRocket
23 July 2026
The story of AI infrastructure is bifurcating in real time. While hypergrowth startups remain structurally doomed—reselling commodity inference with razor-thin margins and no defensible moat—the companies that matter are pivoting toward specificity: IBM is monetizing legacy code maintenance through Project Lightwell at $1 million annually, ServiceNow is investing $40 million in banking expertise through BusinessNext, and Mistral has quietly abandoned the frontier model race to become an enterprise software company. The pattern is clear: raw model access is increasingly worthless. What sells is software that talks to models.
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