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Demis Hassabis

05/26/25

@ Hard Fork

There is a balance between evaluating AI systems internally before public release and obtaining valuable feedback from external critiques, which is crucial for responsible development.

Video

DeepMind CEO Demis Hassabis on How A.I. Is Reshaping Google | Interview

@ Hard Fork

DeepMind CEO Demis Hassabis on How A.I. Is Reshaping Google | Interview

05/26/25

Related Takeaways

Demis Hassabis

05/26/25

@ Hard Fork

AI systems must undergo rigorous internal testing while also engaging with external experts to ensure safety and reliability before public deployment.

Sam Altman

04/12/25

@ TED

The iterative process of deploying AI systems, gathering feedback, and learning is crucial for building safe systems as we advance into more complex AI.

a16z Cast

05/29/25

@ a16z

Expert evaluations are valuable, but they must be complemented by broader community input to avoid bias in AI assessments.

a16z Cast

05/29/25

@ a16z

Expert evaluations are valuable, but they must be complemented by broader community input to avoid bias in AI assessments.

Anthropic Cast

04/28/25

@ Anthropic

We need to share our observations about AI so that the public can have a say in its development and use.

a16z Cast

05/29/25

@ a16z

The diversity of opinions and expertise in the community is crucial for accurately evaluating AI models and their capabilities.

a16z Cast

05/29/25

@ a16z

The diversity of opinions and expertise in the community is crucial for accurately evaluating AI models and their capabilities.

Dwarkesh Patel Cast

04/04/25

@ Dwarkesh Patel

Transparency during the development of AI is crucial to prevent concentration of power and ensure alignment with human values.

Varun Mohan

05/02/25

@ Y Combinator

The complexity of our AI systems is driven by the need for rigorous evaluation, which is critical for making informed investments in our technology.