In this episode of the AI Monetisation Podcast, Yao Fehlis, Head of AI at Artificial, Inc., joins Co-founder Binny Mathews to explore how Self-Driving Labs are transforming scientific discovery through automation and AI.Guest Background: With a background spanning neuroscience, biotechnology, and AI, Yao leads the charge at Artificial, Inc. in designing autonomous lab systems that accelerate the pace of experimentation. His work sits at the intersection of robotics, machine learning, and life sciences, thus bringing the vision of automated R&D closer to reality.

What's Inside?

1. What exactly is a Self-Driving Lab, and how does it work?
2. Automating hypothesis generation and experimental design
3. Real-world applications in biotech, pharma, and materials science
4. The AI stack powering lab automation—from simulation to orchestration
5. Ethical implications and the future of autonomous scientific research

Key Takeaways:

1. Self-driving labs can drastically reduce the time and cost of experimentation

2. Combining robotics and AI enables closed-loop scientific workflows

3. Domain expertise remains essential for guiding and validating automated systems

4. Modular, interoperable lab setups are key to scalable automation

5. The future of science will be hybrid, with humans and machines collaborating in real-time

This episode is a must-watch for researchers, technologists, and innovators eager to understand how AI and automation are reshaping the scientific method itself.

For full show notes, visit- https://bit.ly/3Z4w1vn

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