I explore why black-box prompts are risky in healthcare and how AI graphs offer a clearer path to safe and reliable medical support.
The ideas come from the systems we’ve been developing at MedWrite to make clinical AI easier to trace and verify.
This PyData tutorial walks through building multi-agent AI systems using directed acyclic graphs to orchestrate NLP, vision, recommendation models, and any model.
Key sections:
- When to use multi-agent systems (6:37)
- IntelliNode framework demo (9:35)
- Hands-on labs with nutrition assistant (19:42)
- MCP integration patterns (34:30)
create a virtual character in JavaScript that give identity to your AI project.
Key Features:
- Manual Mode: Control the character through on-screen buttons.
- AI-Controlled: Connect with an AI assistant to enable automatic actions.
- AI Characters: Customizable visual expressions and animations.
Thank you for the suggestion! I’ll add an example in the README.
The character is rendered with JavaScript (no images), this enable the AI assistant to manipulate the animation directly.
Another approach is to use the pre-set button with different reactions, it can be given directly to the AI model through its tool functionality. commonly available in models like ChatGPT and Claude.
