Artificial intelligence and robotics are not the same tool, and understanding the difference changes how you plan, budget, and deploy technology in poultry science. In this episode, host Andy Vance talks with Georgia Tech’s Walker Bynes about where fixed automation ends and flexible robotics begins, and how AI fits in as the decision layer rather than the machine itself. Walker explains why most plants still rely on purpose-built machines for single tasks, and how the next wave aims for adaptable systems that can be reprogrammed to handle new jobs as conditions change in the house, the lab, or the plant.
The conversation breaks down embodied AI in plain language. Listeners hear how vision and language models help robots perceive space, generate action plans, and learn from complex sensor data, and why the quality of inputs, clear guardrails, and human oversight are essential for safety and reliability. In the lab, AI and automation act as a force multiplier by removing repetitive work and surfacing better experiment plans, while researchers stay in control of the science. Looking ahead, Walker sketches a practical roadmap that includes domain-specific models trained on poultry data, flexible robots that can be upskilled with software, and interdisciplinary teams that pair engineers with poultry experts to turn promising ideas into daily routines that save time and improve outcomes.
