The user wants a detailed analysis and professional report based on the title “李彦宏说 DeepSeek 幻觉高，是真的吗？-36氪”.
The report should be over 1000 words, in simplified Chinese, follow a specific structure with small headings, avoid jargon, be engaging, incorporate factual information from the source (36氪 article about Li Yanhong and DeepSeek), and end with a strong conclusion.

Plan:

* What exactly did Li Yanhong say?
* In what context was this statement made?
* Does the article provide any evidence or counter-arguments regarding DeepSeek’s hallucination rate?
* Are there other perspectives or data mentioned in the article?

* 开头： Hook the reader by introducing the buzz around large models and the specific controversy involving a tech giant CEO and a seemingly strong competitor. Set the stage – a statement questioning the quality of a rival model.
* 小标题 1：巨头之声：李彦宏的“幻觉论”抛出 – Describe Li Yanhong’s statement as reported by 36氪. What were his exact words or the essence of his claim about DeepSeek’s high hallucination rate? Why might he say this? (Competitive landscape, Baidu’s Ernie Bot).
* 小标题 2：DeepSeek是谁？为何引人关注？ – Briefly introduce DeepSeek AI and its models. Explain why DeepSeek has gained attention (e.g., performance on benchmarks, open-source efforts, rapid progress). This provides context for *why* Li Yanhong’s comment is significant.
* 小标题 3：探寻事实：36氪文章里的证据与视角 – This is the core analysis based on the search results. Does the 36氪 article directly confirm or refute Li Yanhong’s claim? What data, if any, does it present? Does it quote DeepSeek or other parties? What is the article’s overall stance or information presented? *Crucially, the search results need to provide sufficient detail from the article.*
* 小标题 4：大型模型“幻觉”：一个普遍的挑战 – Discuss the concept of “hallucination” in large language models. Explain why it happens (lack of real-world grounding, probabilistic generation) and that it’s a common issue across *all* models, including top-tier ones. This provides technical context and suggests that high hallucination isn’t unique to DeepSeek, but the *degree* is what matters.
* 小标题 5：竞争漩涡下的技术评价 – Frame the statement within the context of intense competition in the AI large model space in China. Companies are vying for market share, talent, and mindshare. Statements about competitors’ weaknesses are part of this landscape. Is Li Yanhong’s statement a purely technical assessment, or does it have strategic/competitive motivations?
* 小标题 6：用户与开发者如何看待？ – While the 36氪 article might not cover this extensively, a good analysis should touch upon how users and developers evaluate models – not just based on one metric or one statement, but on overall performance, reliability, cost, and specific use cases. Real-world application often reveals different strengths and weaknesses than benchmarks or competitor claims.
* 小标题 7：真相，或许在数据与应用之间 – Synthesize the findings. Is the statement “true” based *solely* on the 36氪 article? (Likely, the article reports the statement but doesn’t definitively prove or disprove it, presenting it as a claim in a competitive context). Conclude that evaluating a model’s hallucination rate is complex, requires rigorous testing, and competitor statements should be viewed critically, especially in a heated market. The real test is performance in diverse applications.
* 结尾： Summarize the situation – a prominent figure made a significant claim about a competitor, highlighting a key challenge in AI (hallucination). Emphasize that the pursuit of reducing hallucination is ongoing for *all* players and the market will ultimately judge based on performance and reliability, not just claims. End on a thought-provoking note about the future of reliable AI.

Confidence Score: 5/5 – I am confident I can meet all requirements if the search results provide enough detail from the 36氪 article about Li Yanhong’s claim and any context or counterpoints mentioned in it.

Strategizing complete. I will now proceed with generating the response based on the retrieved search results.