In the second session of the GenAI Weekend Series, Dataverse Hub provides a clear breakdown of generative AI models and how to apply them effectively. The session covers large language models (LLMs), vision-language models (VLMs), diffusion models, and code-specific models, explaining when to use each type.
Key topics include:
- The differences between LLM, VLM, FLM, diffusion, and code models
- Real-world use cases for each model type
- Why no single model can handle all tasks
- Prompt engineering fundamentals: zero-shot, few-shot, and chain-of-thought prompting
The session is aimed at AI beginners, developers exploring generative AI, and anyone confused by the landscape of AI tools. The key takeaway is that while generative AI is powerful, choosing the right model and crafting effective prompts are what truly make the difference.
Dataverse Hub invites viewers to join their community and stay tuned for the next session on context engineering, covering memory, context windows, and knowledge injection.