
In The MAD Podcast, Matt Turck interviews Lukasz Kaiser, a key figure in modern AI and one of the inventors of the transformer architecture. They discuss the exponential progress of AI, the shift towards reasoning models, and the misconception that AI development is slowing down. Lukasz explains that while pre-training is still valuable, the new paradigm of reasoning models offers more significant gains for the same investment. He highlights the importance of reinforcement learning in training these models and addresses the challenges and opportunities in multimodal AI. The conversation also covers Lukasz's journey into AI research, the story behind the Transformer paper, the differences between research cultures at Google and OpenAI, and the future of pre-training and generalization in AI. They delve into the specifics of GPT-5.1, the role of post-training, and the balance between model capabilities and real-world applications, including the potential for AI in robotics and the evolving job market.
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