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 Stay Updated: Find a16z on Twitter: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Subscribe on your favorite podcast app: https://a16z.simplecast.com/ Follow our host: https://twitter.com/stephsmithio 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.