Category: AI, GenAI, Big Data, Analytical Data Platforms, Data Science-Blog Posts

The Airplane Doesn’t Flap Its Wings: Maharaj Mukherjee on Redefining Intelligence for the Age of AI

Q1. You and Dr. Monideepa Roy argue for a mechanism-agnostic definition of intelligence — one based not on how a system is built, but on what it demonstrably does: perceive, predict, learn, adapt, collaborate, and...

Everyone Has Access to a Personal Jarvis: Kartik Paramasivam on Agentic Engineering, GPU Procurement, and What Actually Breaks at Scale

Q1.  Kartik, you have built massive data infrastructures at both LinkedIn and Pinterest. As we transition from traditional software engineering to “Agentic Engineering,” how do the core competencies of a top-tier engineer change when...

The Good, the Bad, and the Ugly: Kätlin Pulk on What Generative AI Is Really Doing to Higher Education — and What Educators Should Do About It

Q1. You and Riina Koris chose the title The Good, the Bad, and the Ugly deliberately — a framing that signals a refusal to take either the optimistic or the catastrophist position that dominates most public discourse...

AI for Smarties: A Conversation with Bertrand Meyer

Q1. You open AI for Smarties by acknowledging that you kept meeting highly educated people who were fascinated by AI but, in your words, “had no clue of what’s inside” — unable to answer what a neuron...

When Freedom and Authenticity Diverge: James Brusseau on What Philosophy Sees in GenAI That No Other Discipline Does

Q1.  You have written about “acceleration AI ethics” — an approach that argues for using ethics to enable and accelerate GenAI innovation rather than primarily to constrain it, in contrast to the precautionary approach that...