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Code Switching
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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.
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Explore the impact of open-source LLMs like Alibaba's Qwen 2, and how it's driving innovation in AI development.
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FOLLOW ON X:
@8teAPi (Ate)
@JustinLin610 (Junyang)
@picocreator (Eugene)
@TurpentineMedia
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LINKS:
Alibaba Qwen Project:
https://www.alibabacloud.com/en/solutions/generative-ai/qwen?_p_lc=1
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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
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