The Missing Layer in Your AI Stack Why the hardest problem in enterprise AI isn’t building agents — it’s proving they’re governed. • • • The technology part works.
AI is no longer a research experiment. It is embedded in credit decisions, clinical pathways, hiring pipelines, and public services. The ethical question has shifted from whether to govern
The industry is moving fast on capability. It is moving slowly — dangerously slowly — on the one thing that determines whether that capability can be trusted. There is
A Systematic Process for Feature Selection, Feature Dropping, and Algorithmic Self-Selection in Iterative Machine Learning Development Feature selection is the most consequential and least disciplined step in the machine
Healthcare’s AI crisis isn’t what you think. While the pandemic unleashed hundreds of COVID-19 prediction models promising diagnostic breakthroughs, zero reached successful clinical deployment. A 2020 BMJ systematic review
Overlooking the Arabian Sea from Taj Lands End, as I wrapped up a journey through Mumbai and the Maldives, a simple yet profound realization resurfaced: human connection and relationships
Artificial intelligence (AI) is often expected to outperform humans in healthcare because the stakes are high. A more rational approach is to evaluate AI against the real‑world performance of
For all the amazing innovators, leaders, founders, entrepreneurs, and students—undergrad, grad, and beyond—tasked with building AI strategy, many of you whom I’ve had the privilege of mentoring and coaching
Prompt engineering – the crafting of effective inputs for generative AI – is emerging as a critical skill in healthcare. This article provides a comprehensive overview of six key
Neo’s Legacy – Predicting Congenital Risk in Dogs with AI Neo’s Legacy – Predicting Congenital Risk in Dogs with AI Neo came into our lives as a surprise birthday
