AI & Multi-Model Orchestration
Articles on systems that dynamically coordinate multiple foundation models through a single orchestrator, including multi-model synthesis architectures, collective intelligence packaging, and orchestration-based approaches to achieving frontier performance without single-model reliance.
AI multi-model orchestration: C2C lets models talk through KV caches, not text
How Cache-to-Cache (C2C) moves the handoff between language models from text into key-value caches, the benchmark accuracy and latency gains reported at ICLR 2026, and why it is a research result rather than a production architecture for AI multi-model orchestration.
Sakana's Fugu Packs Collective Intelligence Into One Model to Bypass Single-Vendor Risk
Tokyo-based Sakana AI launched Fugu, a foundation model that dynamically orchestrates a pool of frontier LLMs as a single API — matching Anthropic's Fable 5 and OpenAI's GPT-5.5 on benchmarks while hedging against export controls and vendor lock-in.