Dynamic Model Switching in Centralized and Decentralized Chatbot Systems by Pearl Bipin

🚀 Dynamic Model Switching: The Future of AI Optimization! 🌐
Exciting new possibilities in AI architecture are emerging, where we can dynamically switch between traditional ML models and cutting-edge LLMs based on real-time context and performance metrics like accuracy, cost, and response time.
Using frameworks like Bayesian Decision Theory and Markov Decision Processes (MDPs), we can intelligently optimize performance, reduce computational cost, and enhance user experience. The future is here, blending AI flexibility and precision like never before! 🤖💡
📖 Curious to dive deeper? Read my research paper here:
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