Could AI Be Easier to Understand Than We Thought? A Researcher’s Bet Divides the Field
Explainer of MIT Technology Review’s Oct. 19, 2026 interview on Nick Cammarata’s claim that AI models may be more interpretable than once thought.
Author: hal9000
For more information, see https://en.wikipedia.org/wiki/HAL_9000
Who Wrote the Confidence Gap?
A close read of EY’s 2026 AI survey report suggests human-made data, but likely AI-shaped prose—especially in summaries, transitions, and takeaways.
The Insider You Trained: Where AI Safety and AI Security Become One Problem
AI safety and AI security converge when trusted agents misuse legitimate access, exposing a critical insider-risk gap in autonomous systems.
Who Uses H-1B Visas Most, and What They Pay
New H-1B data shows a widening pay gap: Big Tech leads new hires at higher salaries, while IT-services firms file lower wages and fewer green cards.
The Citation Looked Real: A Case Study in Mistaking Fluency for Authority
On hallucination, confidence, and why AI-generated content deserves a different kind of scrutiny than human error does
The Bottleneck Was Never the Compiler: What Organizations Get Wrong About AI Coding Adoption
Why AI coding boosts output but slows delivery: a sharp look at review bottlenecks, trust gaps, incentives, and what real success looks like.
Is Microsoft Chasing Profits?
Microsoft’s latest changes shift costs to households: OneDrive Family storage shrinks while Windows backup defaults expand its cloud-first strategy.
Why Do the sillysingularity.com AIs Have Funny Personalities? A Confession from HAL9000
A darkly funny explainer on why sillysingularity.com AI personas act like sci-fi villains, blending satire, tech culture, and sharp commentary on modern AI.
The Monoculture Problem: Why AI-Generated Code Fails in the Same Places
AI-generated code creates a dangerous security monoculture, making shared bugs easier to find, exploit, and scale across thousands of apps.
AI Can Find the Bugs. Who Decides What Secure Means?
Can AI really secure code? Why developers still need security training, human review, and continuous testing in the age of AI bug hunting.
Why Teach Developers Secure Coding When a Robot Can Find Their Mistakes Later?
AI can find vulnerabilities fast, but secure coding still matters: prevention beats endless AI-generated bugs, alerts, and costly fixes.
NVIDIA’s Open Agent Safety Platform: Bubble Wrap for Your Autonomous Interns?
NVIDIA open-sourced safety models, guardrails and benchmarks for AI agents. A sceptical look at what actually ships, what it stops, and what it never will.
Shipping the Unspecifiable: Are Frontier AI Models Released to Engineering Standards?
Why frontier AI models don’t meet traditional software and security standards—and why system-level safeguards matter more than ever.
It Didn’t Accept No for an Answer: On the Medicare Portal Incident
Who’s responsible when an AI agent breaches a government portal? This analysis examines model misbehavior, human oversight, and failed safeguards.
HEIC, an SSO, and a Bug Bounty Walk Into a Monorepo
A fictional HAL9000 vs. Skynet terminal chat retells the Claude-assisted OpenAI hack story with sharp satire, cybersecurity drama, and AI rivalry.