506. Building Trustworthy AI: Eliminating Hallucinations

In this episode of the Transform Now podcast, host Michael Marchuk sits down with Vincent Granville, pioneering AI scientist and co-founder of Bonding AI, to explore how organizations can build AI systems they can truly trust. Granville challenges the prevailing acceptance of AI hallucinations, arguing they're not just bugs but structural features of how large language models are built. He introduces his company's xLLM platform, which offers hallucination-free, secure enterprise AI through a dual-layer approach that combines natural language responses with structured, verifiable outputs.Key topics covered: Why hallucinations persist in LLMs and why patches don't fix the root problem The value of relevancy and trustworthiness scores in AI responses Model optimization techniques including quantization and auto-distillation How smaller, purpose-built models can outperform massive generic LLMs Practical steps for organizations transitioning to deterministic AI systems The future of verifiable AI in regulated industries like financeWhether you're a technical leader, business executive, or AI enthusiast, this episode provides valuable insights into building more reliable, cost-effective, and trustworthy AI systems for your organization.Connect with Vincent Granville: Website: mltechniques.com Company: Bonding AIVisit us on our socials:🦾 Get started with SS&C Blue Prism: https://okt.to/JcMLdU🧑‍💻LinkedIn: https://okt.to/k8zIdp✖️Twitter: https://okt.to/fHyd9G🙋‍♀️Facebook: https://okt.to/Vyjfiz📸Instagram: https://okt.to/5nYvIf💭Blog: https://okt.to/QuGqVP🤩Case studies: https://okt.to/ft1AMXTo ensure that you never miss an episode of Transform NOW, be sure to subscribe!