Why Small Language Models Are the Future of AI

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🎙️ FULL SHOW NOTES
https://www.microsoftinnovationpodcast.com/702

What if the future of AI isn’t bigger—but smaller, smarter, and more specialized? In this episode, Microsoft’s Ilya Venger pulls back the curtain on the rise of small language models (SLMs), the evolution of intelligent agents, and why clean, governed data is the real fuel behind AI success. From industry-specific copilots to the power of Microsoft Fabric, this conversation is packed with practical insights for business and tech leaders navigating the AI revolution. 

🔑 KEY TAKEAWAYS
SLMs vs. LLMs: Small language models are leaner, more efficient, and better suited for domain-specific tasks—offering lower hallucination rates and higher cost-performance ratios.
Data Quality Matters: AI is only as good as the data it’s trained on. Microsoft Fabric and Purview help unify, clean, and govern enterprise data for more reliable AI outcomes. 
Industry Agents Are Coming: Microsoft is enabling partners to build industry-specific agents—like healthcare assistants or retail copilots—using modular skills and tools.
Copilot Studio’s Role: This low-code platform empowers teams to build, test, and deploy AI agents across Teams, Slack, and custom environments.
The Future of AI Interfaces: Expect dynamic, on-the-fly UI generation tailored to user intent—blending visual and conversational interfaces for seamless interaction. 

🧰 RESOURCES MENTIONED
👉Microsoft Fabric – Unified data platform for analytics and governance
https://www.microsoft.com/fabric\
👉 Microsoft Purview – Data governance and cataloguing solution
https://www.microsoft.com/purview
👉Azure Marketplace – Access to industry-specific AI skills like financial document analysis
https://azuremarketplace.microsoft.com
👉 Copilot Studio – Low-code platform for building and deploying AI agents
https://aka.ms/CopilotStudio 

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Thanks for listening 🚀 - Mark Smith