Making artificial intelligence practical, productive & accessible to everyone.
As AI reshapes the workplace, employees and leaders face questions about meaningful work, automation, and human impact. In this episode, Jason Beutler, CEO of RoboSource, shares how companies can rethink workflows, integrate AI in accessible ways, and empower employees without fear. The discussion covers leveraging AI to handle routine tasks (SOPs or "plays") and reimagining work for smarter, more human-centered outcomes.
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Chris and Daniel talk with returning guest, Ramin Mohammadi, about how those seeking to get into AI Engineer/ Data Science jobs are expected to come in a mid level engineers (not entry level). They explore this growing gap along with what should (or could) be done in academia to focus on real world skills vs. theoretical knowledge.
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Chris and Daniel unpack how AI-driven document processing has rapidly evolved well beyond traditional OCR with many technical advances that fly under the radar. They explore the progression from document structure models to language-vision models, all the way to the newest innovations like Deepseek-OCR. The discussion highlights the pros and cons of these various approaches focusing on practical implementation and usage.
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This episode is a special crossover between the Practical AI podcast and The Changelog podcast. Chris was recently invited by longtime friends Jerod Santo and Adam Stacoviak, cohosts of The Changelog, to join them on the show. They discuss AI, drones, robotics, swarming technology, and the rise of high-performance edge computing with Rust. Chris points out that open source software, small AI models, and affordable hardware are making home automation and local AI accessible to everyone. From automating household functions to experimenting with drones and single-board computers, Chris describes how hands-on maker projects are shaping a bright future for physical AI, on small budgets and right from the comfort of your own home.
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This week we have extended show notes below from Chris!
Swarming & Fully Autonomous Multi-Agent UxV Systems
Chris’s Definition of Swarming (anchor link in show notes)
Chris’s definition of SwarmingConceptual Foundations
Open Research & Multi-Robot Resources (Stepping-Stones Toward True Swarms)
Getting Hands-On: Consumer Robotics, ROS 2 & Gazebo
ROS 2 (Robot Operating System 2)
Gazebo Simulation
micro-ROS (ROS 2 on Microcontrollers)
Fireflies CEO, Krish Ramineni shares how the company is transforming AI-powered note-taking into a deeper layer of knowledge automation. He breaks down the technology behind real-time functionality like Live Assist, the user behavior patterns driving product evolution, and how Fireflies is innovating far beyond meetings. Krish also shares insights on future trends in AI and the potential for hardware integration, emphasizing the ongoing evolution of AI in knowledge work.
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Waymo’s VP of Research, Drago Anguelov, joins Practical AI to explore how advances in autonomy, vision models, and large-scale testing are shaping the future of driverless technology. The conversation dives into the dual challenges of building an onboard driver and testing that driver (via large scale simulation). Drago also gives us an update on what Waymo is doing to achieve intelligent, real-time performance while ensuring proven safety and reliability.
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Dan and Chris unpack whether today’s surge in AI deployment across enterprise workflows, manufacturing, healthcare, and scientific research signals a lasting transformation or an overhyped bubble. Drawing parallels to the dot-com era, they explore how technology integration is reshaping industries, affecting jobs, and even influencing human cognition, ultimately asking: is this a bubble, or just a fizzy new phase of innovation?
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Dan and Chris sit down (again) with Jared Zoneraich, co-founder and CEO of PromptLayer, to discuss how prompt engineering has evolved into context engineering (and while loops with tool calls). Jared shares insights on building flexible AI applications, managing tool calls, testing and versioning prompts, and empowering both technical and non-technical users in AI development. Along the way, they dive into coding agents and the “crawl-walk-run” approach to AI deployment.
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In this fully connected episode, Daniel and Chris explore the emerging concept of tiny recursive networks introduced by Samsung AI, contrasting them with large transformer based models. They explore how these small models tackle reasoning tasks with fewer parameters, less data, and iterative refinement, matching the giants on specific problems. They also discuss the ethical challenges of emotional manipulation in chatbots.
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As AI systems move from simple chatbots to complex agentic workflows, new security risks emerge. In this episode, Donato Capitella unpacks how increasingly complicated architectures are making agents fragile and vulnerable. These agents can be exploited through prompt injection, data exfiltration, and tool misuse. Donato shares stories from real-world penetration tests, the design patterns for building LLM agents and explains how his open-source toolkit Spikee (Simple Prompt Injection Kit for Evaluation and Exploitation) is helping red teams probe AI systems.
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Daniel sits down with Chelsea Linder, VP of Innovation and Entrepreneurship at TechPoint, to explore the what AI innovation and impact look like on the ground. They discuss Chelsea's journey from the VC world into economic development/ innovation, the growth of an AI innovation network in Indiana (funded by the SBA), lessons learned from fostering AI communities, and how businesses are actually adapting to AI. Chelsea also shares insights from Techpoints AI workforce impact study, which explored AI related job creation and levels of AI adoption among other things.
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