Harnessing Collaborative Language Models for Reliable AI Systems

This chapter explores the integration of multiple large language models to improve reliability in crucial applications. It underscores the need for orchestrating logic, human oversight, and validation to enhance the efficacy of these models.

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In this episode of AI Basics, Jason sits down with Yoav Shoham — Stanford professor emeritus and co-founder of AI21 Labs, creators of Jurassic-2, Wordtune, and the new orchestration system Maestro.

They unpack:

Why enterprise AI struggles with reliability
What orchestration really means (and why LLMs alone aren't enough)
The pitfalls of “agent-washing”
Small vs large models, agent-to-agent protocols, and where real opportunities lie

This one is for founders building with AI — if you're navigating hallucinations, chasing automation, or exploring multi-agent workflows, this episode is a must.

Timestamps:

(0:00) Yoav Shoham joins Jason to discuss AI Basics.

(1:05) What AI21 Labs is building — from Jurassic-2 to Maestro

(5:49) The overuse and confusion of the seductive term “agent”

(8:22) Small models vs large models: what's best for enterprise?

(10:53) The verticalization of AI: legal, accounting, and beyond

(12:17) The challenge of agent-to-agent communication and shared semantics

(17:08) What’s overhyped vs underhyped in AI — Yoav’s advice for founders

Uncover more valuable insights from AI leaders in Google Cloud's 'Future of AI: Perspectives for Startups' report.

https://goo.gle/futureofai

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Google Cloud’s Report: The Future of AI