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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@8teAPi (Ate)

@JustinLin610 (Junyang)

@picocreator (Eugene)

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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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