This episode is brought to you by Extreme Networks, the company radically improving customer experiences with AI-powered automation for networking. Extreme is driving the convergence of AI, networking, and security to transform the way businesses connect and protect their networks, delivering faster performance, stronger security, and a seamless user experience.

Visit extremenetworks.com to learn more.

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The Role of AI in Education | Dylan Arena on Learning, AI Tutoring & The Future of Teaching How can AI enhance education without replacing the human touch?

In this episode, Dylan Arena, Chief Data Science and AI Officer at McGraw Hill, shares his insights on the intersection of AI and learning. Dylan’s background in learning sciences and technology design has shaped his approach to AI-powered tools that help students and teachers—not replace them.

He discusses how AI can augment human relationships in education, improve personalized learning, and assist teachers with real-time insights while avoiding the pitfalls of over-reliance on automation.

With AI playing an increasingly central role in education, are we at risk of losing the essential human connections that define great learning experiences?

What You’ll Learn in This Episode:
- Why AI should be used to enhance not replace teachers
- The risks and rewards of AI-powered tutoring
- How AI-driven assessments can improve personalized learning
- Why AI chatbots in education need careful ethical considerations
- The future of gamification and AI-driven engagement in classrooms
- How McGraw Hill is integrating AI into its learning platforms

If you care about the future of education, AI, and ethical tech development, this episode is a must-watch.

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This episode is sponsored by Oracle.

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Chapters:
(00:00) The Role of AI in Augmenting Human Learning
(02:10) Dylan’s Background in Learning Sciences & AI
(08:23) The Risks of AI-Powered Education Tools
(11:08) AI Tutoring: Can It Replace Human Teachers?
(16:28) AI’s Role in Personalized Learning & Adaptive Assessments
(22:47) How AI Can Assist, Not Replace, Teachers
(29:36) The Future of AI-Driven Gamification in Education
(36:41) Ethical Concerns Around AI Chatbots & Student Relationships
(45:02) The Impact of AI on Student Learning & Memory Retention
(50:19) How McGraw Hill is Innovating with AI in Education
(54:44) Final Thoughts: AI’s Role in Shaping the Future of Learning

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.

• 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

This episode is brought to you by Sonar, the creators of SonarQube Server, Cloud, IDE, and the open source Community Build.

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The Future of AI is Open-Source | Manos Koukoumidis on UMI & The AI Revolution

Is closed AI holding back innovation? In this episode, Manos Koukoumidis, CEO of Oumi, makes the case for why the future of AI must be open-source. OUMI (Open Universal Machine Intelligence) is redefining how AI is built—offering fully open models, open data, and open collaboration to make AI development more transparent, accessible, and community-driven.

Big Tech has dominated AI, but UMI is challenging the status quo by creating a platform where anyone can train, fine-tune, and deploy AI models with just a few commands. Could this be the Linux moment for AI?

• Why open-source AI is the only sustainable path forward

• The difference between “open-source” AI and true open AI

• How OUMI enables researchers and enterprises to build better AI models

• Why Big Tech’s closed AI systems are losing their competitive edge

• The impact of open AI on healthcare, science, and enterprise innovation

• The future of AI models—will proprietary AI survive?

The AI revolution is happening—and it’s open-source. If you care about the future of AI, innovation, and ethical tech development, this episode is a must-watch.

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This episode is sponsored by Thuma.

Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.

To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai

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(00:00) The True Meaning of Open-Source AI

(02:15) The Open vs. Closed AI Debate

(07:54) Why Open AI Models Are Safer

(10:34) Defining Open Data

(13:21)Beating GPT-4-O with an Open AI Model

(16:36) Open AI in Healthcare

(19:31) Why Open Models Will Dominate

(23:07) How OUMI Makes AI Training Fully Accessible & Reproducible

(28:44) UMI’s Collaboration with Universities

(32:29) The Shift Toward Open A

(36:41) Can We Build Truly Open AI Models from Scratch?

(40:20) The Role of Open AI in Eliminating Bias

(45:02) Will Open AI Replace Proprietary AI Models?

(50:19) How OUMI Works

(54:44) The Open AI Revolution Has Begun