Alibaba forms AI task force after Qwen lead resigns

Alibaba Group has formed an internal task force led by CEO Eddie Wu Yongming. The group will coordinate company-wide resources for foundational AI model development, Wu said in a letter to the Tongyi AI lab.

The task force includes Zhou Jingren, chief technology officer of Alibaba Cloud, and Wu Zeming, head of the firm’s food delivery business.

The move came after Lin Junyang resigned as technical lead for Alibaba’s flagship Qwen foundational models and announced his departure on X.

Wu wrote that Alibaba would “uphold our open-source model strategy”, scale up investment in AI research and development, and continue to recruit top talent.

A source familiar with Tongyi’s “emergency” meeting said executives promised more computing power and a larger research team.

🔗 Source: South China Morning Post

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Alibaba forms a new task force to steady leadership on foundational AI models

Alibaba created an executive task force to pull together company-wide staff, computing, and funding for foundational AI model development after Lin Junyang resigned as technical lead for the Qwen foundational models 1.
CEO Eddie Wu Yongming leads the group with Zhou Jingren, chief technology officer of Alibaba Cloud, plus Wu Zeming, head of the company’s food delivery business 1.
Wu told Alibaba’s Tongyi AI lab that the company would keep its open-source model strategy, increase spending on AI research and development, and keep hiring top talent 1.
A source familiar with Tongyi’s Wednesday afternoon emergency meeting said executives also committed to more computing power plus a bigger research team 1.

Executive oversight keeps work moving as AI talent changes

Wu’s direct oversight puts continuity and pace for Alibaba’s foundational model work high on the company agenda 1.
The leadership change followed Lin Junyang’s public post on X (formerly Twitter) that he was leaving 1.
Alibaba also hired Zhou Hao, a former Google DeepMind senior research scientist, to lead AI model post-training research, the work that refines and improves a model after its initial training 1.
In his letter, Wu thanked Lin for his contributions 1.