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Lex Fridman

Dario Amodei: Anthropic CEO on Claude, AGI & the Future of AI & Humanity | Lex Fridman Podcast #452

By Advanced AI EditorApril 1, 2025No Comments2 Mins Read
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Dario Amodei is the CEO of Anthropic, the company that created Claude. Amanda Askell is an AI researcher working on Claude’s character and personality. Chris Olah is an AI researcher working on mechanistic interpretability.
Thank you for listening ❤ Check out our sponsors:
See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc.

*Transcript:*

*CONTACT LEX:*
*Feedback* – give feedback to Lex:
*AMA* – submit questions, videos or call-in:
*Hiring* – join our team:
*Other* – other ways to get in touch:

*EPISODE LINKS:*
Claude:
Anthropic’s X:
Anthropic’s Website:
Dario’s X:
Dario’s Website:
Machines of Loving Grace (Essay):
Chris’s X:
Chris’s Blog:
Amanda’s X:
Amanda’s Website:

*SPONSORS:*
To support this podcast, check out our sponsors & get discounts:
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*LMNT:* Zero-sugar electrolyte drink mix.
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*OUTLINE:*
0:00 – Introduction
3:14 – Scaling laws
12:20 – Limits of LLM scaling
20:45 – Competition with OpenAI, Google, xAI, Meta
26:08 – Claude
29:44 – Opus 3.5
34:30 – Sonnet 3.5
37:50 – Claude 4.0
42:02 – Criticism of Claude
54:49 – AI Safety Levels
1:05:37 – ASL-3 and ASL-4
1:09:40 – Computer use
1:19:35 – Government regulation of AI
1:38:24 – Hiring a great team
1:47:14 – Post-training
1:52:39 – Constitutional AI
1:58:05 – Machines of Loving Grace
2:17:11 – AGI timeline
2:29:46 – Programming
2:36:46 – Meaning of life
2:42:53 – Amanda Askell – Philosophy
2:45:21 – Programming advice for non-technical people
2:49:09 – Talking to Claude
3:05:41 – Prompt engineering
3:14:15 – Post-training
3:18:54 – Constitutional AI
3:23:48 – System prompts
3:29:54 – Is Claude getting dumber?
3:41:56 – Character training
3:42:56 – Nature of truth
3:47:32 – Optimal rate of failure
3:54:43 – AI consciousness
4:09:14 – AGI
4:17:52 – Chris Olah – Mechanistic Interpretability
4:22:44 – Features, Circuits, Universality
4:40:17 – Superposition
4:51:16 – Monosemanticity
4:58:08 – Scaling Monosemanticity
5:06:56 – Macroscopic behavior of neural networks
5:11:50 – Beauty of neural networks

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