Your Undivided Attention

The Promise and Peril of Open Source AI with Elizabeth Seger and Jeffrey Ladish

Episode Summary

As AI development races forward, a fierce debate has emerged over open source AI models. So what does it mean to open-source AI? Are we opening Pandora’s box of catastrophic risks? Or is open-sourcing AI the only way we can democratize its benefits and dilute the power of big tech?

Episode Notes

As AI development races forward, a fierce debate has emerged over open source AI models. So what does it mean to open-source AI? Are we opening Pandora’s box of catastrophic risks? Or is open-sourcing AI the only way we can democratize its benefits and dilute the power of big tech? 

Correction: When discussing the large language model Bloom, Elizabeth said it functions in 26 different languages. Bloom is actually able to generate text in 46 natural languages and 13 programming languages - and more are in the works.

 

RECOMMENDED MEDIA 

Open-Sourcing Highly Capable Foundation Models

This report, co-authored by Elizabeth Seger, attempts to clarify open-source terminology and to offer a thorough analysis of risks and benefits from open-sourcing AI

BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B

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Centre for the Governance of AI

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AI: Futures and Responsibility (AI:FAR)

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Palisade Research

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