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“Tencent Yao Shunyu’s latest interview transcript: I don’t believe that ChatGPT and Claude Code are the only Super Apps”

2026-09-04 08:00 Models 🔥 42.2 heat score
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On September 4, 2026, at the Tencent Cloud AI Industry Application Conference, Yao Shunyu, Chief AI Scientist of Tencent, and Tang Daosheng, Senior Executive Vice President, held a discussion on “The Second Half of AI”. Both parties noted that current AI methodologies are mature, and ChatGPT and Claude Code are not the only super applications. In the future, numerous new opportunities will emerge. Facing the requirements for generalization and composite capabilities in the LLM era, Tencent emphasized that long-term organizations based on AGI need to balance basic research and cutting-edge exploration. The core view is that Co-Design is the key path, achieving deep integration of models and products through pre-training, post-training, and real-world evaluation.

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ChatGPTClaude CodeGanzhi Light YearsOpenAITencent

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ChatGPT × Claude Code1ChatGPT × Ganzhi Light …1ChatGPT × OpenAI1ChatGPT × Tencent1Claude Code × Ganzhi Li…1Claude Code × OpenAI1

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Keyword heat
  • Tencent1
  • ChatGPT1
  • Claude Code1
  • OpenAI1
  • Ganzhi Light Years1

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甲子光年 zh 2026-09-04 08:00

“Tencent Yao Shunyu’s latest interview transcript: I don’t believe that ChatGPT and Claude Code are the only ‘Super Apps’”

Yao Shunyu, Chief AI Scientist at Tencent, stated at the Tencent Cloud AI Industry Application Conference on June 5 that he does not believe ChatGPT and Claude Code are the only “Super Apps”; there will surely be continuous new opportunities. Tang Muyu, Senior Executive Vice President of Tencent Group, and Yao Shunyu discussed the “second half of AI” in their conversation, pointing out that current methodologies have matured, and finding good questions has become more difficult. They emphasized that building long-term organizations based on AGI requires balancing fundamentals, products, and cutting-edge exploration. Both agreed that Co-Design is key, achieving deep integration of models and products through pre-training, post-training, and real-world evaluation to meet the requirements of the LLM era for generalization and composite capabilities.