The Constellation approach promises reliability by chaining AI models—but in practice it multiplies errors, latency, cost, and operational risk.
The current generation of applications built on general-purpose AI models may look solid at first glance but lean on them in the real world and they wobble.
We present a method for encoding tree-structured data (like you might get from conversation rollouts while doing RL training for conversational agents) using a standard transformer. This method gives us training speedups of up to 70x over standard training.
Today, we’re excited to announce a new partnership with Genesys®, a global cloud leader in AI-Powered Experience Orchestration.
Today, Scaled Cognition is launching with the world’s first model and system designed and trained for agentic applications.
