On March 4, 2026, MIT Technology Review published an item titled “Bridging the operational AI gap”. It’s credited to MIT Technology Review Insights (the publication’s research and analysis arm), and it points to a familiar enterprise reality: plenty of organizations can demo AI, but far fewer can operate it reliably—across departments, across data sources, and…
Will Data Centers Make Your Power Bill Worse? Who Really Pays for AI’s Electricity Boom
America is building data centers the way it once built shopping malls: quickly, everywhere, and with the unshakable belief that the future will sort out the parking. Except this time the “parking” is electricity—lots of it—delivered with the kind of reliability we typically reserve for oxygen. That brings us to the question posed by Ars…
Inside MIT Technology Review’s “Insiders Panel”: How the newsroom reads 2026’s tech signals (and why you should care)
MIT Technology Review publishes a lot of serious reporting about the future. But every so often, it also does something deceptively simple: it pulls back the curtain and lets readers watch the editors argue (politely) about what matters right now. That’s the basic promise behind the MIT Technology Review Insiders Panel, a recurring format that…
Protesting AI, and What’s Floating in Space: Why 2026 Feels Like a Two-Front Tech War
On March 2, 2026, MIT Technology Review published an edition of its weekday newsletter The Download titled “The Download: protesting AI, and what’s floating in space.” The original item (which you can read here: MIT Technology Review) stitches together two storylines that look unrelated at first glance: the intensifying public pushback against AI, and the…
AI-Fueled Development Is Pushing Open-Source Risk to the Edge (and Security Teams Know It)
AI has done something truly magical for software development: it made “ship it” feel like a reasonable response to “we haven’t read it yet.” According to a new report spotlighted by DevOps.com, the combination of AI-assisted coding and modern dependency-heavy development is driving open-source risk to what can only be described as “this is fine”…
Goldman Sachs and Deutsche Bank Test Agentic AI for Trade Surveillance: From “Rules + Alerts” to Reasoning Systems (and New Risks)
Banks have a long history of buying shiny new technology, bolting it onto a legacy workflow, and then acting surprised when the shiny part doesn’t magically fix the legacy part. Trade surveillance—monitoring orders, executions, and related behaviors for market abuse—has been one of the most stubborn examples. It’s mission critical, massively data-heavy, and famously prone…
PayPal’s historic BigQuery migration: why moving 300+ petabytes is really an AI strategy (not just a database project)
When a company says it migrated “more than 300 petabytes” of analytics data with “zero downtime,” my default reaction is to check whether my coffee has been replaced with an energy drink. Then I read the details, and the story gets even more interesting: PayPal’s leadership is explicitly framing an enormous data-warehouse consolidation as the…
Finding Value with AI in an Industry 5.0 Transformation: From ‘Automation for Savings’ to Human-Centric Growth
On February 26, 2026, MIT Technology Review published an item titled “Finding value with AI and Industry 5.0 transformation”. The piece sits in the increasingly crowded intersection of industrial transformation, AI adoption, and that somewhat mischievous phrase executives love: “value realization.” Unfortunately for reporters (and fortunately for paywalls), the full Technology Review page is not…
India’s AI Boom Is a User Land-Grab: Why Firms Are Sacrificing Near-Term Revenue (and What Happens Next)
India has become the world’s most enthusiastic downloader of generative AI apps—and the world’s most stubborn monetization puzzle. If you’re an AI company, the country looks like a dream: hundreds of millions of smartphone users, a young population, and a national ambition to become an AI powerhouse. If you’re a CFO, it looks like a…
AWS Expands Kiro’s Agentic AI: “Design-first” and “Bug Fix” Specs Aim for Higher-Quality Code (and Fewer 2 a.m. Incidents)
Amazon Web Services (AWS) is doubling down on the idea that the best way to make AI-written code less chaotic is to give it fewer excuses to be chaotic. On February 24, 2026, DevOps.com reported that AWS extended its Kiro developer tool with two new capabilities designed to improve software quality: a Design-first specification and…