How to address concept drift in machine learning
Because of concept drift in machine learning, models built for forecasting will almost always experience drops in performance and accuracy over time. Can artificial intel...
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Critical Decision Making for Enterprise AI
Interview with Vincent Koc, MIT Program Mentor Introduction: Bridging AI and Enterprise On this episode of the AI Think Tank podcast, I had the pleasure of sitting down w...
How generative AI can enhance customer operations, sales, marketing, and software engineering
The arrival of Generative AI has triggered widespread attention, prompting every organization to prioritize it, with many transitioning from the “what” to the...
Deep Reflections on Mycelium, Neural Networks, & AGI
Interview with Jeanette Small, MA, PhD In this recent AI Think Tank Podcast episode, we took a close look into the complexities of intelligence, neural networks, and the ...
(Trying to) Quantify the Economic Impact of GenAI
How can we quantify GenAI’s performance impact on employees with below-average to average performance compared to high-performance employees? I have had the privile...
30 Features that Dramatically Improve LLM Performance – Part 3
This is the third and final article in this series, featuring some of the most powerful features to improve RAG/LLM performance. In particular: speed, latency, relevancy ...