What Dario Amodei thinks about measuring intelligence

@dario-amodei · 43 positions · On ppll ↗

Co-founder and CEO of Anthropic; previously VP of research at OpenAI.

Dario Amodei did not write this page.

We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.

Filter measuring intelligence · Newest first

Topic

All 43LLMs 10AI and jobs 7AI alignment 5data centers 4scaling laws 4AGI 3measuring intelligence 3code generation 2government 2

14 more topics

Silicon Valley 2the cloud 2AI and science 1America 1Anthropic 1benchmarks 1chat interfaces 1China 1coding agents 1democracy 1happiness 1JavaScript 1reinforcement learning 1robotics 1

Sort

NewestOldest

Only Dario Amodei on measuring intelligence. See everyone on measuring intelligence

3 dated positions, 2020 to 2026, in their own words. Our reading of what Dario Amodei has said — not written or endorsed by them.

3 positions so far — this page is not yet offered to search engines.

1. 13 Feb 2026

   Our readingThe one genuine uncertainty left about AI capability is tasks nobody can verify — planning a Mars mission, discovering CRISPR, writing a novel.

   Their wordsMy one little bit, the one little bit of of fundamental uncertainty even on long time scales is this thing about tasks that aren't verifiable. Like, planning a mission to Mars, like, uh you know, doing some fundamental scientific discovery like like CRISPR, like, you know, writing a writing a novel. Hard to hard to verify those tasks.

   ↗Dario Amodei — “We are near the end of the exponential”youtube.com 5th of 29 in this recording

2. 6 years earlier

3. 28 May 2020

   Our readingHumans can generally perform new language tasks from few examples or simple instructions, while current NLP systems largely cannot.

   Their wordsBy contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do.

   ↗Language models are few-shot learners (with 30 co-authors)arxiv.org All 3 from this paper

5. 28 May 2020

   Our readingOne-shot or zero-shot settings are the fairest comparisons to human performance and important targets for future work.

   Their wordsUltimately, however, one-shot, or even sometimes zero-shot, seem like the fairest comparisons to human performance, and are important targets for future work.

   ↗Language models are few-shot learners (with 30 co-authors)arxiv.org All 3 from this paper