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


 


RECOMMENDED YUA EPISODES


A First Step Toward AI Regulation with Tom Wheeler


No One is Immune to AI Harms with Dr. Joy Buolamwini


Mustafa Suleyman Says We Need to Contain AI. How Do We Do It?


The AI Dilemma


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