Sara Hooker is VP of Research at Cohere and leader of Cohere for AI. We discuss her recent paper critiquing the use of compute thresholds, measured in FLOPs (floating point operations), as an AI governance strategy.
We explore why this approach, recently adopted in both US and EU AI policies, may be problematic and oversimplified. Sara explains the limitations of using raw computational power as a measure of AI capability or risk, and discusses the complex relationship between compute, data, and model architecture.
Equally important, we go into Sara's work on "The AI Language Gap." This research highlights the challenges and inequalities in developing AI systems that work across multiple languages. Sara discusses how current AI models, predominantly trained on English and a handful of high-resource languages, fail to serve the linguistic diversity of our global population. We explore the technical, ethical, and societal implications of this gap, and discuss potential solutions for creating more inclusive and representative AI systems.
We broadly discuss the relationship between language, culture, and AI capabilities, as well as the ethical considerations in AI development and deployment.
TOC: [00:00:00] Intro [00:02:12] FLOPS paper [00:26:42] Hardware lottery [00:30:22] The Language gap [00:33:25] Safety [00:38:31] Emergent [00:41:23] Creativity [00:43:40] Long tail [00:44:26] LLMs and society [00:45:36] Model bias [00:48:51] Language and capabilities [00:52:27] Ethical frameworks and RLHF
Disclaimer: This is the third video from our Cohere partnership. We were not told what to say in the interview, and didn't edit anything out from the interview.
