A naukri.com initiative
Medium
3w
424
Image Credit: Medium
Beyond Reactive Chatbots
- The article discusses the trade-off between speed and depth in AI-driven chatbots and explores a solution using a tiered reasoning approach inspired by human cognition.
- A practical architectural framework is introduced to create conversational AI systems that think fast, think deep, and evolve over time.
- The dual-process theory, involving fast intuition and slow deliberation, serves as the basis for structuring AI processing into distinct layers.
- System 1 focuses on fast thinking, providing immediate responses based on prompt information and short-term memory, while System 2 handles deeper, asynchronous processing.
- Implementing System 2 involves using tools like Celery for asynchronous task execution to balance responsiveness with deeper analysis.
- System 3 operates offline, processing historical data to enhance future interactions and allowing the AI to learn and evolve over time.
- The tiered reasoning approach is demonstrated through industry-specific challenges in areas like financial analysis, technical diagnostics, and schedule optimization.
- By balancing responsiveness and deep analysis, this architecture creates AI assistants that are both thoughtful and adaptive, inspired by human cognitive processes.
- As AI assistants powered by LLMs become more prevalent, the ability to blend immediate engagement with deeper reasoning will differentiate valuable assistants from reactive chatbots.
- The article encourages sharing of experiences in implementing tiered reasoning approaches for better conversational AI to advance beyond reactive chatbots.
Read Full Article
25 Likes
For uninterrupted reading, download the app