In this episode of Emergent Behavior, @8teapi talks with Justin Junyang Lin, Chief Evangelist Officer of Alibaba Qwen Project. Joined by guest host Eugene Cheah, CEO of Recursal.AI, they talk about how Alibaba's Qwen 2 tackles multilingual challenges, including code-switching and the unique complexities of Chinese data. 🔥 Apply to join over 400 founders and Execs in the Turpentine Network: https://hmplogxqz0y.typeform.com/to/JCkphVqj Explore the impact of open-source LLMs like Alibaba's Qwen 2, and how it's driving innovation in AI development. – FOLLOW ON X: @8teAPi (Ate) @JustinLin610 (Junyang) @picocreator (Eugene) @TurpentineMedia -- LINKS: Alibaba Qwen Project: https://www.alibabacloud.com/en/solutions/generative-ai/qwen?_p_lc=1 -- TIMESTAMPS: (00:00) Introduction (04:36) Qwen's Development Journey (08:00) Data Curation & Coding Capabilities (11:00) The Role of Evaluation (14:00) Evolution of Pre-training and Evaluation (17:00) Open Source vs. Commercial Groups (22:00) Data Contamination (24:00) Model Sizing and Computational Constraints (28:00) Multi-lingual Capabilities (31:00) Tokenizers and Language-Specific Considerations (34:00) Code Switching and Data Filtering (38:00) Code Switching, Dialects, and Model Size (42:00) User Feedback and Model Development (46:00) Challenges with Chinese Datasets (52:00) Language Variation and Team Development (58:00) Hiring and Team Dynamics (1:03:00) Diversity and Production Considerations (1:07:00) Production Impact and Collaboration (1:13:00) Wrap