Safety in Numbers: Keeping AI Open

Arthur Mensch, co-founder of Mistral and co-author of Deepmind's 2022 "Chinchilla" paper, recently released Mistral-7B, a popular open-source language model.

Their latest offering, Mixtral, a mixture of experts model, is attracting attention in the AI community. Join Arthur and a16z General Partner Anjney Midha in a discussion about the nuances of open source, the comparative performance of open and closed models, and the innovations needed for scaling large language models (LLMs) effectively.

Topics covered:
00:00 - Introduction to scaling laws and their impact
02:14 - Arthur Mensch and the Founding of Mistral
07:57 - Mistral 7b and the launch of Mixtral
13:27 - Misconceptions about open source, the state of open vs. closed models, and future requirements for scaling LLMs
18:41 - Open Source in AI: Scaling laws, Industry Impact, data efficiency, and new model architectures
22:56 - Safety concerns of open source models.
25:17 - Recommendations for policymakers in regulating AI technologies.
33:17 - Predictions on how advancements in LLMs will change user interactions with technology
36:36 - Potential applications in various fields like gaming and enterprise.
38:53 - Call to action for builders, researchers, and developers

Resources:
Find Arthur on Twitter:   / arthurmensch  
Find Anjney on Twitter:   / anjneymidha  
Learn more about Mistral: https://mistral.ai

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