Bankless LIMITLESS - Dwarkesh Patel: The Scaling Era of AI is Here
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Jul 29, 2025 
Dwarkesh Patel, a prominent voice in the AI space and author of "The Scaling Era," delves into the transformative power of artificial intelligence. He discusses the critical scaling laws driving AI advancements and the ongoing quest for artificial general intelligence. Patel offers insight into AI's limitations, particularly its inability to learn in real-time, and emphasizes the moral implications of AI development. He highlights the potential socioeconomic shifts brought by AI and the pressing need for robust governance to ensure ethical alignment with human values.
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The AI Scaling Era Origins
- The scaling era in AI started around 2012 with neural networks trained on internet text using scalable transformer architectures.
- Exponentially increasing compute and data enabled large models to learn diverse skills, though energy and compute limits may cap growth by 2028-2030.
Scaling Laws and Brain Analogies
- Intelligence from compute plus data is not fully understood; AI scaling mirrors biological scaling where architecture and evolutionary niche matter.
- Humans evolved a scalable brain architecture rewarded by incremental intelligence benefits, enabling AI scaling parallels in transformers.
Why AI Excels at Coding
- AI excels at coding because humans are poor at coding and there is vast, high-quality code data available.
- Moravec's paradox explains AI improving fastest at tasks humans find hardest or less evolved to perform, like reasoning and coding.
