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Weaviate Podcast

Compound AI Systems with Philip Kiely - Weaviate Podcast #105!

Oct 17, 2024
Philip Kiely, the leading developer relations at Baseten, shares insights on compound AI systems and their evolution. He discusses breaking tasks into multiple stages for better AI model performance. The conversation covers advancements in multimodal AI and strategies for deploying these systems efficiently. Kiely emphasizes the benefits of smaller models and constrained generation techniques, alongside architectural tips for Kubernetes deployment. Key comparisons are made between various model serving frameworks, focusing on optimizing AI performance while minimizing costs.
56:50

Episode guests

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Quick takeaways

  • The podcast emphasizes the evolving landscape of AI with the rise of both comprehensive and specialized models, showcasing their unique advantages and challenges.
  • Philip discusses the integration of multimodal capabilities in compound AI systems, highlighting their efficiency in handling complex workflows and diverse tasks.

Deep dives

The Current Landscape of AI Models

The discussion highlights the evolving landscape of AI models, focusing on the emergence of both all-encompassing models and specialized models. Open-source advancements are showcasing models that can integrate multiple modalities, particularly with LLaMA 3.2's capabilities in vision and audio. While generalized models can perform a wide array of tasks, niche models that target specific functions, like math or language tasks, are also gaining traction. This duality indicates that both comprehensive and specialized models have their unique advantages and challenges in real-world applications.

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