AI Confidential

As GenAI tools have become more intelligent and robust, the reliability of their output has decreased. Enter Galileo: an AI reliability platform designed for GenAI applications. Atin Sanyal — the Co-founder and CTO of Galileo — has a background building machine learning tech at Uber and Apple. One innovative technique that sets Galileo apart is ChainPoll — their hallucination detection methodology that uses consensus scoring and prompts the LLM to outline its step-by-step reasoning process.  In this episode, hosts Aaron Fulkerson and Mark Hinkle talk to Atin about: What evaluation agents are, and why they get smarter over time How Galileo helps enterprises evolve their own AI quality metrics Why data quality and confidential computing will become increasingly important to enterprises building AI systems If you want to learn more about AI and how to benefit from it responsibly, visit opaque.co

João Moura built the agentic AI open source framework, CrewAI, with a central vision: to make agent creation feel borderline magical. Inspired by the Ruby on Rails philosophy of “convention over configuration,” CrewAI is designed for speed, clarity, and ease of use. What we love about João’s approach to agentic AI is that he’s not just disrupting the market. He’s shifting the way enterprise leaders think about long-term workflows and processes, too. In this episode, hosts Aaron Fulkerson and Mark Hinkle talk to João about: Why interoperability across your stack is essential for scaling AI The importance of building secure AI systems How managers are uniquely equipped to build effective agents The dangers of “agent washing" and how to see through the hype If you want to learn more about AI and how to benefit from it responsibly, visit opaque.co

James Kaplan has been consulting enterprise clients on how to adopt and extract value from cutting-edge technologies for over 25 years. His dual role as Partner at McKinsey and CTO at McKinsey Technology gives him a unique vantage point into how CIOs and CTOs can harness AI to drive automation, increase productivity, and enhance data security. In this episode, host Aaron Fulkerson talks to James about: How AI is changing the enterprise technology landscape What enterprises should be thinking about as they’re adopting and building AI systems How to avoid the “IT doom loop" If you want to learn more about AI and how to benefit from it responsibly, visit opaque.co

Hosts Aaron Fulkerson and Mark Hinkle sit down with Sriram Raghavan, Vice President of IBM Research AI, at the AllThingsOpen.ai conference. As an experienced industry expert, Sriram leads a global team of over 750 research scientists and engineers focused on advancing AI.  Sriram and IBM believe that the future of AI is open source. That’s why IBM recently contributed three AI projects — Docling, Data Prep Kit, and BeeAI — to the Linux Foundation. And while there is a lot of hype around LLMs right now, IBM is leaning into smaller “fit-for-purpose” models that give developers choice. In the episode, Sriram also digs into: IBM’s approach to open-source models What innovations he sees coming for enterprise AI How his team is approaching responsible, secure AI

From cloud computing to infrastructure-as-a-service, Reuven Cohen (AKA rUv) has been on the cutting edge of every major technology supercycle — and he’s now one of the most influential people in the agentic AI space. With the help of agents, rUv produced 10 million lines of usable code last year. That’s 33,000 years of output from one human. rUv’s approach proves one of two things: he’s either an outlier or a leading indicator of what’s to come. In this episode, we talk to rUv about:  His approach to training autonomous agents The rapid advancements in agentic code development  Why LLMs are vulnerable to data poisoning Why Python is bad for agentic development

What does it take to ensure AI is safe, ethical, and resilient? In this season finale, Anthropic’s CISO joins Aaron to discuss the critical intersection of innovation, data privacy, and sovereignty, offering an optimistic perspective on what lies ahead for the future of confidential AI.   

AI is full of potential, but what does it really take to make it work in complex environments? Will Grannis, CTO and VP at Google Cloud, shares his perspective on bridging AI innovation with practical application, including insights into the real challenges and rewards of implementing AI in today’s top enterprises.

Can AI be both innovative and private? NVIDIA VP of Software Security Daniel Rohrer and Opaque Co-Founder and President Raluca Ada Popa discuss the advancements in privacy-preserving technology that enable organizations to push AI forward without compromising data sovereignty.

Generative AI is transforming industries—but how do we ensure it’s safe? Teresa Tung, Senior Managing Director & Global Data Capability Lead at Accenture, dives into what companies need to make generative AI both impactful and secure, exploring the frameworks that bring safety to scale.

Join Mark Papermaster, CTO at AMD with a rich background at IBM and Apple, and Mark Russinovich, CTO at Microsoft Azure and tech pioneer, as they delve into the world of confidential computing. They discuss how this technology enhances security in AI applications, making them trustworthy and easy to adopt. The duo highlights the importance of partnerships in driving innovation and share insights on multi-party computation's role in safeguarding privacy across industries. Discover how these advancements are reshaping data management and business strategies.