As everyone tries out DeepSeek, the Shenyang team from Tsinghua University’s School of Journalism and Communication and the School of Artificial Intelligence, led by Professor Shen Yang and postdoctoral researcher Yu Menglong, has released version 1.0 of “DeepSeek: From Beginner to Pro”.
Recently, this practical manual for DeepSeek has been highly popular on social media.
• What is DeepSeek?
• What can DeepSeek do?
• How to use DeepSeek?
This 103-page report details the core functionalities and application scenarios of DeepSeek, emphasizing its advantages in text creation, natural language understanding, programming assistance, etc. It also compares the performance characteristics of reasoning models and general models, providing users with precise criteria for model selection.
The report further explores how to fully leverage DeepSeek’s reasoning and generation capabilities through carefully designed prompt strategies, including task decomposition, logical chain construction, and advanced techniques for multimodal information processing.The report also highlights the four core capabilities of human-AI symbiosis—AI thinking, guidance, integration, and judgment, helping users build a unique competitive advantage in the AI era.By mastering these skills, you will progress from being an “AI user” to an “innovator,” opening a new chapter in intelligent collaboration.
Summary of “DeepSeek: From Beginner to Pro”
1. Basic Concepts and Core Functions
- What is DeepSeek?
- A domestic open-source general artificial intelligence (AGI) company focused on the development and application of large models.
- Core product: DeepSeek-R1 (open-source reasoning model, excels in complex tasks, free for commercial use).
- Text Generation: Articles, marketing copy, code comments, structured data generation, etc.
- Semantic Understanding: Sentiment analysis, intent recognition, knowledge reasoning, multilingual translation.
- Programming Support: Code generation, debugging optimization, technical document processing.
- Data Analysis: Business analysis, resource optimization, data visualization, modeling predictions.
- Multimodal Processing: Supports file uploads, image text recognition, chart generation.
2. Usage Tips and Model Selection
- Model Classification
- Reasoning models (like DeepSeek-R1): Specialize in logical analysis, mathematical derivation, code generation.
- General models (like GPT-4): Excel in text generation, multi-turn dialogue, creative writing.
- Concise instructions (for reasoning models) vs structured guidance (for general models).
- Key elements: Task instructions, context, output format, quality control.
- Avoid pitfalls: Overly directive instructions, vague requirements, ethical boundaries, hallucination generation.
- Use the SPECTRA model: Split tasks, prioritize, and adjust dynamically.
- Combine logical chains, knowledge chains, and creative chains (three-chain integration model) to enhance content quality.
3. Advanced Applications and Innovative Design
- Cross-domain Thinking
- Concept grafting (e.g., designing a knowledge platform combining “social media + traditional libraries”).
- Extreme hypothesis strategies: Subvert conventional assumptions and explore innovative possibilities.
- Meta-narrative frameworks: Embedded reflexive prompts, recursive meta-narratives, multiple personality interactions.
- Emotional integration: Enhance emotional impact through sensory descriptions and emotional curve design.
- Rhetoric and style simulation: Precisely match platform tone (e.g., Shakespearean style).
- WeChat Official Account: In-depth reading structure, topic planning, interactive node design.
- Weibo: Trend capturing, topic guidance, quick dissemination.
- Xiaohongshu: Grass-planting copy, scenario-based expression, visual and textual synergy.
- Douyin: 3-second attention-grabbing openings, tightly paced plots, emotional interactions.
4. Human-AI Symbiosis and Core Competencies
- Four Core Competencies
- AI Thinking: Understanding model boundaries, establishing collaboration frameworks.
- Guidance: Designing effective prompts to control output quality.
- Integration: Merging human and AI advantages to create cross-domain value.
- Judgment: Assessing content reliability and avoiding AI hallucination risks.
- From “user” to “innovator”: Building a personal prompt system and designing a bespoke workflow.
- Knowledge awakening and integration: Activating implicit experiences through AI to form systematic cognition.
5. Key Conclusions
Generation quality: 70% depends on human prompt design and iterative optimization. Future competitiveness: Mastering prompt engineering, cross-domain integration, and creative thinking to create irreplaceable human-AI collaboration advantages.
“DeepSeek: From Beginner to Pro”
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This article is reprinted from the WeChat public account “All Media Exploration”
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21 February 2025
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