Podknife - Success (and failure) in prompting by Practical AI: Machine Learning, Data Science

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Success (and failure) in prompting

Podcast |: Practical AI: Machine Learning, Data Science
Publisher |: Changelog Media
Media Type |: audio
Podknife tags |: Artificial Intelligence,; Business,; Data Science,; Interview,; Machine Learning,; Tech News,; Technology
Categories Via RSS |: Software How-To,; Tech News,; Technology
Publication Date |: Feb 28, 2023
Episode Duration |: 00:43:52

Description
Content Encoded

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.

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
chatbot-microsoft-chatgpt.html">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 thought.com/how-to-create-effective-prompts-for-ai-image-generation/">here

Something missing or broken? ai-213.md">PRs welcome!

Timestamps:

(00:00) - Welcome to Practical AI(00:43) - Best time for an AI podcast?(05:19) - What makes output good or bad?(15:36) - Sponsor: Changelog++(16:36) - Behind the behavior(19:23) - What can we reliably expect?(29:14) - Prompt Engineering(35:11) - Tips on engineering prompts(43:05) - Outro

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