The Promise and Peril of Open Source AI with Elizabeth Seger and Jeffrey Ladish
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 Published On Jan 26, 2024

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 (https://elizabethseger.com/open-sourc...)


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 (https://arxiv.org/abs/2311.00117)


This paper, co-authored by Jeffrey Ladish, demonstrates that it’s possible to effectively undo the safety fine-tuning from Llama 2-Chat 13B with less than $200 while retaining its general capabilities


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Palisade Research (https://palisaderesearch.org/)


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Your Undivided Attention is produced by the Center for Humane Technology (https://www.humanetech.com/) . Follow us on Twitter: @HumaneTech_ (  / humanetech_  )

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