ajayverma

Keeping GenAI Honest: Monitoring and Evaluating Performance in the Age of Large Language Models Generative AI (GenAI) is rapidly transforming industries, empowering us to create text, images, code, and more with unprecedented ease. But with great power comes great responsibility. As we increasingly rely on GenAI models for critical tasks, it’s imperative to implement robust monitoring and performance evaluation strategies to ensure their accuracy, reliability, and ethical use. This blog explores the key considerations for monitoring and evaluating GenAI models, highlighting the metrics, tools, and techniques necessary to keep these powerful systems honest and effective. Generated by AI The Need for Vigilance: Why Monitor GenAI? Unlike traditional software systems with well-defined inputs and outputs, GenAI models operate in a more probabilistic and nuanced space. Their behavior can be influenced by various factors, including: Training Data:  Biases in the training data can lead to...

AI Skills vs. Degrees: Navigating the Rapidly Evolving Landscape of Artificial Intelligence The world is changing at an unprecedented pace, driven by rapid technological advancements, particularly in Artificial Intelligence (AI). As AI permeates every industry, the question arises: What’s more valuable — a traditional degree or demonstrable AI skills? In a field where new innovations emerge daily, and the shelf life of knowledge is shrinking, the answer may surprise you. Press enter or click to view image in full size Generated by AI The Shifting Sands of Skills The traditional path to a successful career often involved pursuing a degree, mastering a specific body of knowledge, and then applying those skills in the workplace. However, the AI revolution is disrupting this model. The World Economic Forum’s Future of Jobs Report 2025 highlights that 40% of the skills required for current roles are expected to change in the coming years. Moreover, 63% of employers identify the lack of rele...