"Vibe Coding is a Slot Machine" - Jeremy Howard

About this episode

Jeremy Howard discusses the implications of AI on software engineering and the importance of maintaining technical intuition.

Dive into the realities of AI-assisted coding, the origins of modern fine-tuning, and the cognitive science behind machine learning with fast.ai founder Jeremy Howard. In this episode, we unpack why AI might be turning software engineering into a slot machine and how to maintain true technical intuition in the age of large language models. GTC is coming, the premier AI conference, great opportunity to learn about AI. NVIDIA and partners will showcase breakthroughs in physical AI, AI factories, agentic AI, and inference, exploring the next wave of AI innovation for developers and researchers. Register for virtual GTC for free, using my link and win NVIDIA DGX Spark (https://nvda.ws/4qQ0LMg) Jeremy Howard is a renowned data scientist, researcher, entrepreneur, and educator. As the co-founder of fast.ai, former President of Kaggle, and the creator of ULMFiT, Jeremy has spent decades democratizing deep learning. His pioneering work laid the foundation for modern transfer learning and the pre-training and fine-tuning paradigm that powers today's language models. Key Topics and Main Insights Discussed: - The Origins of ULMFiT and Fine-Tuning - The Vibe Coding Illusion and Software…

People in this episode

Guest: Jeremy Howard

Topics covered

• AI-assisted coding
• fine-tuning
• cognitive science
• software engineering
• large language models
• AI innovation

Keywords

• AI
• fine-tuning
• software engineering
• cognitive science
• large language models
• transfer learning
• GTC

Sponsors

NVIDIA

Mentioned in this episode

Organizations: fast.ai, Kaggle, NVIDIA

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