Published on: 2025-06-19 11:51:39
ive spent the past few months designing a framework for orchestrating multiple large language models in parallel — not to choose the “best,” but to let them argue, mix their outputs, and preserve dissent structurally. It’s called Maestro heres the whitepaper https://github.com/d3fq0n1/maestro-orchestrator (Narrative version here: https://defqon1.substack.com/p/maestro-a-framework-for-coher...) Core ideas: Prompts are dispatched to multiple LLMs (e.g., GPT-4, Claude, open-source models) The s
Keywords: com https maestro multiple outputs
Find related items on AmazonPublished on: 2025-07-26 23:35:00
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Question: What product should use machine learning (ML)? Project manager answer: Yes. Jokes aside, the advent of generative AI has upended our understanding of what use cases lend themselves best to ML. Historically, we have always leveraged ML for repeatable, predictive patterns in customer experiences, but now, it’s possible to leverage a form of ML even without an
Keywords: customer inputs llms ml outputs
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