Welcome back to the first episode of season 3 of the Talking AI podcast, formerly known as the Built Right podcast!
We’re kicking off with Amir Behbehani, Founder and Chief AI Engineer at Memra, a platform that helps build, deploy, and automate workflow through AI. He and host Matt Paige look at some of the hurdles AI needs to overcome to fully integrate into enterprise, such as lack of proprietary data access and memory.
Amir delves into the science behind these challenges and potential solutions. He introduces the concept of ‘agentic AI’ and the emergent AI stack, made up of five layers, aimed at enhancing AI functionality through memory management, data orchestration, and agentic reasoning.
They also discuss the role of vector and graph databases, the importance of memory and context, and exploring future use cases in a marketplace with agentic AI. Amir also speculates on the transformative potential of AI in the future labor market – hinting at more entrepreneurial endeavors as individuals leverage AI for improved productivity and automation.
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- Introduction to Amir and Memra
- Challenges with current LLMs
- Emergent AI stack overview
- Layer-by-layer breakdown of the AI stack
- Agentic AI and memory management
- Future of work with agentic AI
- The future of Memra
