In this episode of Practical AI, Chris and Daniel explore the fascinating world of agentic AI for drone and robotic swarms, which is Chris's passion and professional focus. They unpack how autonomous vehicles (UxV), drones (UaV), and other autonomous multi-agent systems can collaborate without centralized control while exhibiting complex emergent behavior with agency and self-governance to accomplish a mission or shared goals. Chris and Dan delve into the role of AI real-time inference and edge computing to enable complex agentic multi-model autonomy, especially in challenging environments like disaster zones and remote industrial operations.

Featuring:

• Chris Benson – Website, LinkedIn, Bluesky, GitHub, X
• Daniel Whitenack – Website, GitHub, X

Links:

• ROS - Robotic Operating System
• Gazebo
• Hugging Face Agents Course
• Swarm Robotics | Wikipedia

Chris's definition of Swarming:
Swarming occurs when numerous independent fully-autonomous multi-agentic platforms exhibit highly-coordinated locomotive and emergent behaviors with agency and self-governance in any domain (air, ground, sea, undersea, space), functioning as a single independent logical distributed decentralized decisioning entity for purposes of C3 (command, control, communications) with human operators on-the-loop, to implement actions that achieve strategic, tactical, or operational effects in the furtherance of a mission.
© 2025 Chris Benson

Sponsors:

• Outshift by Cisco: AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows.

In the first episode of an "AI in the shadows" theme, Chris and Daniel explore the increasing concerning world of agentic misalignment. Starting out with a reminder about hallucinations and reasoning models, they break down how today’s models only mimic reasoning, which can lead to serious ethical considerations. They unpack a fascinating (and slightly terrifying) new study from Anthropic, where agentic AI models were caught simulating blackmail, deception, and even sabotage — all in the name of goal completion and self-preservation.

Featuring:

• Chris Benson – Website, LinkedIn, Bluesky, GitHub, X
• Daniel Whitenack – Website, GitHub, X

Links:

• Agentic Misalignment: How LLMs could be insider threats
• Hugging Face Agents Course

Register for upcoming webinars here!

In this episode, we sit down with Joey Conway to explore NVIDIA's open source AI, from the reasoning-focused Nemotron models built on top of Llama, to the blazing-fast Parakeet speech model. We chat about what makes open foundation models so valuable, how enterprises can think about deploying multi-model strategies, and why reasoning is becoming the key differentiator in real-world AI applications.

Featuring:

• Joey Conway – LinkedIn
• Chris Benson – Website, LinkedIn, Bluesky, GitHub, X

Links:

• Llama Nemotron Ultra
• NVIDIA Llama Nemotron Ultra Open Model Delivers Groundbreaking Reasoning Accuracy
• Independent analysis of AI
• Parakeet Model
• Parakeet Leaderboard
• Try the Llama-3.1-Nemotron-Ultra-253B-v1 model here and here