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“What’s really interesting about neural networks is the way that they think or the way that they operate is a lot like human intuition”
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What if we could use automation not just as a tool, but as a mirror for our own human behaviors?
From the limits of rationalism to the rise of neural networks, Dan Shipper, CEO and co-founder of Every, traces a history of knowledge that spans Socrates, the Enlightenment, and modern machine learning.
Shipper explains why “if/then” rules break in messy reality, and how large language models actually see the world through context and pattern. He explores how AI can work with our own creativity and why these tools are unlikely to steal our humanity.
0:00 Neural networks and human intuition
1:13 The limits of rationalism, from Socrates to neural networks
1:23 Rationalism
2:42 Socrates, the father of Rationalism
5:47 The Age of Enlightenment
7:36 The structure of social sciences
8:51 Defining AI
9:47 The origins of AI
10:39 The General Problem Solver
15:09 Neural networks
18:22 Metaphors for the mind
23:00 Seeing the world like a large language model
30:25 Should we stop looking for general theories?
32:22 Training neural networks
39:32 Will AI steal our humanity?
43:43 AI and rational explanation
47:17 Could LLMs be dangerous?
51:12 Knowledge economies and allocation economies
Read the video transcript ► https://bigthink.com/series/full-interview/human-intuition-ai/?utm_source=youtube&utm_medium=video&utm_campaign=youtube_description
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About Dan Shipper:
Dan Shipper is the CEO and cofounder of Every, where he explores the frontiers of AI in his column, Chain of Thought, and on his podcast, ‘AI & I.’
