Tagged: AI

Practical AI Security. A Hands-on Guide to Attacking, Defending, and Securing Modern AI Systems.

by Harriet Farlow June 2026, 392 pp. ISBN-13:  9781718504660 No Starch Press If you’re a security practitioner learning to operate in AI environments, or an ML engineer who needs to understand what adversaries actually...

22 Chapters, One Question: Barry Solaiman on What the World’s Legal Systems Get Right and Wrong About AI in Healthcare

Q1. You and your co-editor I. Glenn Cohen brought together a genuinely international collection of legal experts spanning Asia, Europe, and the US, examining both major religious and secular ethical traditions alongside legal frameworks....

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...

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...

The Hybrid Mind: Joseph X. Ng on Human-AI Convergence, the OODA-F Loop, and Why Responsible AI Must Be Structurally Designed — Not Declared

Q1. What failure occurs when AI-assisted decision-making operates without an explicit Feedback layer? The specific failure mode is what I call loop erosion: the system continues to optimize under the assumption that real-world consequences...

AI data infrastructure that survives under pressure

By Paul Speciale. Most enterprise GenAI initiatives focus on the model, but the projects that stall do so for a different reason entirely: the underlying data infrastructure simply can’t support what AI actually demands....