Eye On A.I.

Will Grannis, CTO of Google Cloud, shares insights on the revolutionary landscape of agentic AI. He discusses how multi-agent systems can streamline tasks like expense automation and enhance operational workflows. Grannis highlights the importance of trust in AI, emphasizing secure agent management and the potential for scientific discovery. He also explains how large organizations can leverage their data for agility, comparing their pace to startups. This conversation redefines our understanding of AI's future, focusing on autonomy and innovation in technology.

Rajat Taneja, President of Technology at Visa, shares insights into the company’s bold $3.3 billion AI strategy. He reveals how Visa stops over $40 billion in fraud annually using deep learning models trained on vast transaction data. Taneja discusses the exciting concept of agentic commerce and Visa's pioneering role in AI since the 1990s. With a focus on behavioral biometrics and real-time decision-making, he explores how AI is reshaping payment security and the future of financial interactions.

Yoav Shoham, co-founder of AI21 Labs, shares his fascinating journey through the evolution of AI, blending traditional methods with modern deep learning. He discusses innovative models like Jamba, which disrupts traditional architectures, and Maestro, designed to improve enterprise AI by enhancing efficiency and reliability. Yoav also delves into the philosophical implications of understanding AI and the future of decentralized computing, revealing how these advancements can tackle real-world challenges in the industry.

Greg Osuri, founder of Akash Network, discusses the transformative power of decentralized cloud computing. He explains how his platform disrupts traditional giants like AWS by unlocking underutilized compute power and slashing costs. The conversation highlights the energy bottlenecks faced in AI training and the pivotal role of blockchain in securing cloud resources. Osuri envisions a future where AI thrives in decentralized infrastructures, ensuring data privacy and fostering a vibrant, community-driven tech ecosystem.

Dylan Arena, Chief Data Science and AI Officer at McGraw Hill, specializes in learning sciences and technology design. He discusses how AI can revolutionize education by enhancing rather than replacing the human touch. Dylan emphasizes the potential of AI-powered tools to personalize learning experiences and assist teachers without creating over-reliance on automation. He raises important questions about maintaining essential human connections in a digitally-driven learning environment and explores the ethical implications of integrating AI into education.

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. NetSuite is offering a one-of-a-kind flexible financing program. Head to  https://netsuite.com/EYEONAI to know more. Can AI learn like humans? In this episode, Patrick Pilarski, Canada CIFAR AI Chair and professor at the University of Alberta, breaks down The Alberta Plan—a bold roadmap for achieving Artificial General Intelligence (AGI) through reinforcement learning and real-time experience-based AI. Unlike large pre-trained models that rely on massive datasets, The Alberta Plan champions continual learning, where AI evolves from raw sensory experience, much like a child learning through trial and error. Could this be the key to unlocking true intelligence? Pilarski also shares insights from his groundbreaking work in bionic medicine, where AI-powered prosthetics are transforming human-machine interaction. From neuroprostheses to reinforcement learning-driven robotics, this conversation explores how AI can enhance—not just replace—human intelligence. What You’ll Learn in This Episode: Why reinforcement learning is a better path to AGI than pre-trained models The four core principles of The Alberta Plan and why they matter How AI-driven bionic prosthetics are revolutionizing human-machine integration The battle between reinforcement learning and traditional control systems in robotics Why continual learning is critical for AI to avoid catastrophic forgetting How reinforcement learning is already powering real-world breakthroughs in plasma control, industrial automation, and beyond The future of AI isn’t just about more data—it’s about AI that thinks, adapts, and learns from experience. If you're curious about the next frontier of AI, the rise of reinforcement learning, and the quest for true intelligence, this episode is a must-watch. Subscribe for more AI deep dives! (00:00) The Alberta Plan: A Roadmap to AGI   (02:22) Introducing Patrick Pilarski (05:49) Breaking Down The Alberta Plan’s Core Principles   (07:46) The Role of Experience-Based Learning in AI   (08:40) Reinforcement Learning vs. Pre-Trained Models   (12:45) The Relationship Between AI, the Environment, and Learning   (16:23) The Power of Reward in AI Decision-Making   (18:26) Continual Learning & Avoiding Catastrophic Forgetting   (21:57) AI in the Real World: Applications in Fusion, Data Centers & Robotics   (27:56) AI Learning Like Humans: The Role of Predictive Models   (31:24) Can AI Learn Without Massive Pre-Trained Models?   (35:19) Control Theory vs. Reinforcement Learning in Robotics   (40:16) The Future of Continual Learning in AI   (44:33) Reinforcement Learning in Prosthetics: AI & Human Interaction   (50:47) The End Goal of The Alberta Plan  

Manos Koukoumidis, CEO of OUMI, champions the open-source AI movement, advocating for a transparent and collaborative approach to AI development. He argues that open-source is the sustainable path forward, contrasting it with the limitations of closed AI systems. The discussion delves into how OUMI empowers innovators to train and deploy AI models effortlessly, potentially leading to a pivotal moment for the industry. Koukoumidis also highlights the importance of shared resources in fostering ethical practices and diversity in AI.

Tuhin Srivatsa is the CEO and Co-founder of Baseten, a company revolutionizing machine learning infrastructure. In this engaging discussion, he tackles the broken nature of AI deployment and how Baseten is streamlining the process for enterprises. Discover the shift towards open-source AI and why it's a game-changer. Tuhin also highlights the hidden costs of AI inference, the reasons many models fail in production, and the exciting future of scalable AI infrastructure. This insightful conversation is a must-listen for those navigating the AI landscape.

Dominic Williams, founder of DFINITY and the visionary behind the Internet Computer (ICP), dives into the flaws of the current internet and proposes a revolutionary decentralized alternative. He elaborates on how ICP challenges giants like AWS and Google Cloud, emphasizing smart contracts to enhance internet security and censorship resistance. Williams also discusses the journey of Internet Computer from concept to reality, alongside its innovative architecture and the reverse gas mechanism that supports efficient decentralized computing. Tune in for a glimpse into the future of Web3!

Pedro Domingos, a leading AI researcher and author of 'The Master Algorithm', explores the Symbolist approach to AI. He discusses how Symbolic AI, dominant from the 1950s to the early 2000s, remains vital today. Domingos explains the Physical Symbol System Hypothesis and inverse deduction, showcasing its applications like decision trees and random forests that often outperform deep learning. He also delves into challenges like the knowledge acquisition bottleneck and the dynamic landscape of AI techniques, emphasizing the need for a diverse toolkit in AI development.