China behind in LLM race but it can still win in AI, ex-Tencent AI lead says
China is currently lagging behind in the race for large language models (LLMs) but still has the potential to excel in artificial intelligence (AI). A former AI lead at Tencent emphasized that with the right strategies, China can catch up and even lead in AI advancements. The insights suggest that while challenges exist, opportunities remain for growth and innovation in the sector.
- ▪China is behind in the development of large language models.
- ▪The former Tencent AI lead believes China can still succeed in the AI field.
- ▪Strategic planning and innovation could help China catch up in AI technology.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,011 of its stories.
Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | South China Morning Post |
| Canonical URL | https://www.scmp.com/tech/big-tech/article/3354394/china-losing-llm-race-it-can-still-win-ai-ex-tencent-ai-lead-says |
| Publication time | Sun, 24 May 2026 07:38:51 +0000 |
| Retrieval time | 2026-05-24T07:52:31.181Z |
| Last seen | 2026-05-24T07:52:31.181Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | -EXro0KjC0gu |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
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Excerpt limited to ~120 words for fair-use compliance. The full article is at South China Morning Post.