This crossover episode from Inference by Turing Post features CEO Dev Rishi of Predibase discussing the shift from static to continuously learning AI systems that can adapt and improve from ongoing user feedback in production.

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This crossover episode from Inference by Turing Post features CEO Dev Rishi of Predibase discussing the shift from static to continuously learning AI systems that can adapt and improve from ongoing user feedback in production. Rishi provides grounded insights from deploying these dynamic models to real enterprise customers in healthcare and finance, exploring both the massive potential upside and significant safety challenges of reinforcement learning at scale. The conversation examines how "practical specialized intelligence" could reshape the AI landscape by filling economic niches efficiently, potentially offering a more stable alternative to AGI development. This discussion bridges theoretical concepts with real-world deployment experience, offering a practical preview of AI systems that "train once and learn forever."

Sponsors:
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The AGNTCY: The AGNTCY is an open-source collective dedicated to building the Internet of Agents, enabling AI agents to communicate and collaborate seamlessly across frameworks. Join a community of engineers focused on high-quality multi-agent software and support the initiative at https://agntcy.org

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CHAPTERS:
(00:00) Sponsor: Google Gemini 2.5 Flash
(00:31) About the Episode
(03:46) Training Models Continuously
(05:03) Reinforcement Fine-Tuning Revolution
(09:31) Agentic Workflows Challenges (Part 1)
(12:51) Sponsors: Labelbox | Oracle Cloud Infrastructure
(15:28) Agentic Workflows Challenges (Part 2)
(15:41) ChatGPT Pivot Moment
(19:59) Planning AI Future
(24:45) Open Source Gaps (Part 1)
(28:35) Sponsors: The AGNTCY | NetSuite by Oracle
(30:50) Open Source Gaps (Part 2)
(30:54) AGI vs Specialized
(35:26) Happiness and Success
(37:04) Outro

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