Success (and failure) in prompting

Practical AI: Machine Learning, Data Science

With the recent proliferation of generative AI models (from OpenAI, co:here, Anthropic, etc.), practitioners are racing to come up with best practices around prompting, grounding, and control of outputs.

Chris and Daniel take a deep dive into the kinds of behavior we are seeing with this latest wave of models (both good and bad) and what leads to that behavior. They also dig into some prompting and integration tips.

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Featuring:

• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

Generative AI model behavior in the news:

• Microsoft’s AI chatbot is going off the rails
• A Conversation With Bing’s Chatbot Left Me Deeply Unsettled
• Sydney’s gaslighting
• ChatGPT political bias
• Stable Diffusion amplification of stereotypes

Useful guides related to prompt engineering:

• co:here prompt engineering guide
• Prompt engineering overview from Elvis Savaria
• 10 Amazing Resources For Prompt Engineering, ChatGPT, and GPT-3
• Image generation prompt engineering guides: see here and here

Something missing or broken? PRs welcome!