GPT-4o is an updated version of the ChatGPT model, an improved take on GPT-4 with higher accuracy and performance. It can handle tasks of any complexity effectively, from creative assignments to deep analytical research.
Technical characteristics of ChatGPT 4o
- Speed: Faster request handling than previous versions.
- Optimisation: Thanks to a better architecture, it can process large volumes of data and multitask more efficiently.
- Multimodality: The ability to work with different data types, including text and images.
Prompting tips for ChatGPT 4o
Advanced Chain-of-Thought prompting:
- Use it for complex analytical tasks that require deep reasoning.
- Ask the model not just to explain the steps, but to weigh alternative approaches.
Example:
Analyse the impact of artificial intelligence on the labour market over the next 10 years. At every stage of the analysis, consider different scenarios, assess how likely they are and what the consequences could be. Justify each of your judgements and point out possible counterarguments.
Multimodal prompts:
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Combine text requests with image analysis for complex tasks.
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Use visual elements to supplement or clarify text instructions.
Example:
Analyse this image of a cityscape. Describe the architectural styles visible in the photo and propose three innovative ideas for sustainable urban development that would fit the existing architecture.
Prompts for deep data analysis:
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Combine text requests with analysis of complex data to support decisions.
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Use the models to analyse large volumes of information and derive key metrics.
Example:
Here is monthly sales data for a coffee shop you can use for analysis:**
- Latte**: 500 units sold, average price — $3.50, review rating — 4.5**
- Cappuccino**: 400 units sold, average price — $4.00, review rating — 4.7**
- Espresso**: 350 units sold, average price — $3.00, review rating — 4.2**
- Americano**: 300 units sold, average price — $3.00, review rating — 4.3**
- Muffin**: 200 units sold, average price — $2.50, review rating — 4.0Analyse this data. Propose three recommendations for increasing revenue next month.
Prompts for generating code and technical documentation:
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Use detailed specifications and usage scenarios.
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Ask the model to comment on and explain the generated code.
Example:
Write a Python script that analyses network traffic and detects potential security threats. Include exception handling, logging and the option to configure it through an external file. Comment on every important block of code and explain how it works.
Prompts for building complex narratives:
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Set out complex scenarios with many characters and story lines.
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Use historical or futuristic contexts to build rich worlds.
Example:
Create a short plot for a science fiction novel set in the year 2250. Include three intertwining story lines: one on Earth, one on Mars and one on a space station between them. Describe the key characters, their motivations and how their actions shape a growing conflict between the planets.