Markus Walker

ChatGPT: Create a Presentation!

Is ChatGPT just an interactive Stack Overflow? We tested its coding strengths and uncovered its critical, sometimes humorous, weaknesses.

ChatGPT: Create a Presentation!
#1about 2 minutes

From image recognition to modern generative AI

AI has evolved from extracting information, like in image recognition, to creating new content, which is a fundamental shift for technology.

#2about 3 minutes

Understanding ChatGPT's capabilities and limitations

ChatGPT is a large language model that predicts text but cannot perform actual computations, making it a powerful yet fallible tool for developers.

#3about 2 minutes

Analyzing, refactoring, and converting code with AI

ChatGPT can quickly analyze obfuscated code, refactor it for readability, and even convert it from JavaScript to TypeScript.

#4about 4 minutes

Explaining and generating complex regular expressions

The model can deconstruct and explain existing regular expressions and generate new ones for tasks like validating phone numbers, though with varying accuracy.

#5about 6 minutes

Generating algorithms and solving complex logic problems

While ChatGPT can generate standard algorithms like quicksort, it often makes mistakes with implementation details like memory complexity and struggles with novel logic problems.

#6about 2 minutes

Using a test-driven development approach with AI

Providing a unit test as a prompt can guide the AI to generate the correct function implementation, demonstrating a test-driven development workflow.

#7about 5 minutes

Creative prompting for simulation and prompt refinement

Advanced prompting techniques can make the AI act as a prompt engineer to refine your requests or even simulate complex systems like a SQL database server.

#8about 2 minutes

Exploring popular AI tool integrations for developers

AI capabilities are integrated into developer tools like GitHub Copilot for IDE assistance, AIaC for generating Terraform code, and even a new version of Clippy.

#9about 2 minutes

Key takeaways for using AI in software development

To use AI effectively, be specific with prompts, always validate the output for correctness and security, and treat it as a powerful but fallible tool.

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