The Artificial Intelligence Podcast Interview #74 Suman Kanuganti, CEO of Personal AI
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Aug 23, 2025 Suman Kanuganti, Co-founder and CEO of Personal AI, specializes in personal language models and decision-making engines for edge devices. He discusses a shift from large, generic AI models to tailored personal language models that capture unique decision-making patterns. Kanuganti highlights the efficiency of smaller models, emphasizing privacy-by-design and their ability to perform better in specific applications. He also explores the future of distributed AI systems and the challenges faced by the current AI landscape, dominated by resource-heavy solutions.
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LLMs Aren't A Universal Solution
- Large LLMs are not one-size-fits-all and can lose grounding for specialized tasks.
- Small, programmable models can give higher precision, privacy, and scalability for targeted problems.
Ground AI In Company Data And Pipelines
- Build AI solutions around a company's unique data and workflows instead of only calling generic LLMs.
- Invest in memory, access controls, and data pipelines to convert LLM access into real business value.
Personal Models Model People, Not Everything
- Artificial Personal Intelligence focuses on modeling individual decision-making and identity.
- AGI maps to broad, centralized systems while personal models map to distributed client-side compute.