Super Data Science: ML & AI Podcast with Jon Krohn 919: Hopes and Fears of AGI, with All-Time Bestselling ML Author Aurélien Géron
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Sep 2, 2025 
Aurélien Géron, author of 'Hands-On Machine Learning,' shares his journey and insights into the fourth edition of his bestselling book. He discusses the pivotal shift from TensorFlow to PyTorch, emphasizing hands-on learning for innovation. Aurélien expresses both hopes and fears regarding AGI, addressing ethical dilemmas and alignment challenges. He also highlights the urgency of aligning AI with human values, reflecting on its potential transformative role in education and society. This engaging conversation balances optimism with caution in AI's rapidly evolving landscape.
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Why He Wrote The Book
- Aurélien wrote Hands-On Machine Learning to teach a practical, code-first path from engineer to production competence.
- He targeted one imaginary software engineer and added exercises that made the book adoptable in classrooms.
Start With Objective And Metric
- Define your objective and metric before modeling and pick the simplest model that meets the goal.
- Remember many problems are solved better by classical methods like random forests than by jumping straight to neural nets.
Researchers Now Drive Framework Choice
- The community shifted from TensorFlow to PyTorch because PyTorch is more Pythonic and better for researcher iteration.
- Researchers now drive framework adoption because fast iteration shapes model development and deployment paths.
