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

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

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

Centre for the Governance of AI

Supports governments, technology companies, and other key institutions by producing relevant research and guidance around how to respond to the challenges posed by AI

AI: Futures and Responsibility (AI:FAR)

Aims to shape the long-term impacts of AI in ways that are safe and beneficial for humanity

Palisade Research

Studies the offensive capabilities of AI systems today to better understand the risk of losing control to AI systems forever

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The AI Dilemma

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