In this episode, Christopher Grainger, founder of Amplified.ai, joins me to discuss the intersection of Elixir and AI, particularly focusing on Lang graph functionality and genetic workflows. Christopher shares his journey from academia to founding a successful patent search platform, and how Elixir's unique characteristics make it particularly well-suited for AI/ML workloads.

We explore how OTP primitives provide natural solutions for agent-based AI systems, discussing how Elixir's actor model aligns perfectly with modern AI architectures. Christopher explains how Amplified.ai transformed their tech stack by moving from Python to Elixir, resulting in significant cost savings and improved system efficiency.

The conversation dives into the challenges of the patent search industry, the importance of semantic search in patent analysis, and how AI is revolutionizing this space. We also discuss the future of Elixir in the AI landscape, examining why its concurrency model and fault tolerance make it an excellent choice for building robust AI systems.

A fascinating discussion about practical applications of Elixir in AI, scaling businesses with small teams, and the future of technology in the patent industry.

Connect with Christopher:Amplified: https://www.amplified.ai/BSky: https://bsky.app/profile/cigrainger.bsky.socialWebsite: https://cigrainger.com/
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