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: https://twitter.com/arthurmensch
Find Anjney on Twitter: https://twitter.com/AnjneyMidha
Learn more about Mistral: https://mistral.ai
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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