AI definitions: World Models

World Models – These are AI systems that build up an internal approximation of an environment. Through trial and error, these bots use the representation to evaluate predictions and decisions before applying the results to real-world tasks. This contrasts with LLMs, which operate on correlations within language rather than on connections to the word itself. In the late 1980s, world models fell out of favor with scientists working on artificial intelligence and robotics. The rise of machine learning has brought interest in developing these systems back to life.

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AI Detector Ban

Indiana University's Kelley School of Business explicitly states that AI detection tools are not approved for use because they are "highly unreliable" and can produce both false positives and false negatives. Instead of trying to catch students using AI, the university is encouraging professors to rethink how they teach and assess student work in the age of generative AI. -Tom’s Guide

17 Surprising Things AI Can Do Now

26 Recent Articles about the Dangers of AI

How to Fight AI Brain Rot at School? For One Country, It’s With Free ChatGPT – Wall Street Journal  

These AI models are free, private, and will never say 'no' – NPR  

Claims that China and overseas propaganda drive Americans to rise up against data centers are based on scant evidence. – Washington Post  

Why A.I. Safety Controls Are Not Very Effective – New York Times

AI Has Broken Containment - The Atlantic 

AI license plate cameras tore this town apart and led to a state of emergency - Washington Post

The world must stop AI from empowering bioterrorists – The Economist

Scammers targeting missing pet owners with AI – ABC-7

Deepfakes Are Coming for Your Bank Account OpenAI made the perfect tool for scammers. - The Atlantic

ChatGPT Wrestles With Its Most Chilling Conversation: How Do I Plan an Attack? - Wall Street Journal 

5 AI Models Tried to Scam Me. Some of Them Were Scary Good - Wired

A secretive AI hacking system has sparked a global scramble – Washington Post

Five Concerns About AI Data Centers, and What to Do About Them – Data Innovation

AI can design viruses, toxins and other bioweapons. How worried should we be? – Nature

Inside a growing movement warning AI could turn on humanity - The Washington Post

Behind the Curtain: The kids aren't AI-right - Axios 

AI Is Finding Bugs That Hackers Can Exploit. Get Ready for Bugmageddon. - Wall Street Journal 

A.I. Is on Its Way to Upending Cybersecurity – New York Times

"Too Powerful to Release": The Greatest Marketing Playbook in AI – AI in the News

Four Reasons New AI Data Centers Won’t Overwhelm the Electricity Grid - ITIF

Over 4,732 Messages, He Fell In Love With an AI Chatbot. Now He’s Dead. - Wall Street Journal   

AI Is Using So Much Energy That Computing Firepower Is Running Out - Wall Street Journal 

Claude Mythos Is Everyone’s Problem - The Atlantic 

Creating Baby Geniuses to Thwart the AI Threat? (Yes, Really.) – Mother Jones

We ranked the most environmentally damaging things you can do online. AI didn't top the list – Science Focus

43 Articles on Career Advice

5 skills young professionals should master - Glassdoor

5 Ways to Demonstrate Your Value — Remotely - HBR

Actionable Advice For Young People Starting Out Their Careers - Forbes

The best way to show off your emerging A.I. skills to land a job - CNBC

Building Your Intellectual Toolbox: Career Advice from the Experts - Council on Foreign Relations

The Career Advice No One Teaches High Achievers - Inc

Common misconceptions about MBAs - ZDnet

Don’t Focus on Your Job at the Expense of Your Career - Harvard Business Review

Don’t Just Pay Interns, Help Them Build Networks - Harvard Business Review

Essential advice for landing your dream job - Fast Company

Find Work You Love by Identifying Your Unique Angle - LifeHacker

Gen Z is Hungry for Career Advice. But Their Parents Are Lost Themselves - TIME

Giving Career Advice to Kids Has Never Been Harder - Wall Street Journal

Google’s ‘Career Dreamer’ uses AI to help you explore job possibilities – Tech Crunch

Harvard researcher shares key skill of the future—that most people don't have - CNBC

How do you launch a journalism career in the middle of a pandemic? - Poynter

How to Break Up With Your Career - Wall Street Journal

How Much Time Can I Take Off Between Jobs? - Harvard Business Review

How to get your career moving: lessons from a behavioural scientist - Financial Times

How to Improve Your Career Development - US News

How to Recover from a Toxic Job - Harvard Business Review

How to Tell You're About to be Laid Off - Life Hacker

How to Vet a Remote Workplace - Harvard Business Review

The Journalists of Color Resource Guide

Journalism Mentors

Journalist Guide to Survival: Five ways to thrive on your first job - RTDNA

LinkedIn CEO: Ignore this common piece of career advice—it’s ‘outdated’ and ‘a little bit foolish’ - CNBC

Losing Passion for Your Job? Why Quitting Might Be the Right Move - Harvard Business School

One Piece of Career Advice Changed Everything - Inc

Our Top 6 Pieces of Career Wisdom for Recent Grads - First Round

The Personal Business of Being Laid Off - HazLitt

Pros and Cons of Working From Home - US News

How to Recover from a Toxic Job - Harvard Business Review

The Secret to Retaining the Best Employees: Ask Them These Four Questions - Wall Street Journal

A Survival Guide for Dealing With a Bad Boss - Wall Street Journal

These are the signs that you're in a toxic work environment - CNN

The top 10 skills you need to land a job right now, according to LinkedIn - CNBC

These 5 skills are AI-proof and likely to become more valuable ‘over the next 5 years,’ says Oxford-trained career expert - CNBC

Tips for Using AI Tools in Technical Interviews - IEEE

Well-meaning advice to new grads often makes the job search more stressful—what actually helps: Harvard psychologist - CNBC

What Reporters Should Do Before and After a Layoff - Education Writer’s Association

What’s a good (and bad) way to leave your job? - FT

Your Career Is Just One-Eighth of Your Life - The Atlantic

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21 Recent Articles about AI & Data Science

Why satellite imagery falls short for AI training data

How to Write Robust Code with Claude Code

Recursive Language Models: An All-in-One Deep Dive

It’s worth revisiting fundamental ideas from probability theory and examining where common assumptions about AI reliability begin to break down.  

White House Approves a secret $9 Billion request for Spy Agencies to Catch Up on A.I.  

Six Choices Every AI Engineer Has to Make (there are production trade-offs that only appear once your model is live)  

Germany is launching military AI into space

Why sandboxing OpenClaw doesn’t stop data exfiltration

Five fundamental concepts that every Python developer should have in their toolkit.  

How AI Agents Will Transform Data Science Work in 2026

How to undo Git actions with confidence

"Should we process our data in batches or in real-time?" The answer depends on another question: "When does the answer matter?"  

Making Claude Code validate its own work  

How to Build an Efficient Knowledge Base for AI Models

Re-thinking human–machine interaction and the governance of AI in the military domain

How insertion and deletion errors disrupt data synchronization in modern communication systems   

NRO says proliferated satellite architecture exceeding expectations

How AI Tools Generate Technical Debt — and What to Do About It  

To accelerate adoption of commercial technology, NGA has established a Rapid Capabilities Office 

Tech firms are partnering up under an initiative called Coalition Edge to push analytics, cloud infrastructure and connectivity closer to the battlefield

Claude Code is leaking API keys into public package registries

Flattened Writing

My version of “human” is no longer acceptable. What’s actually happening is not AI detection; it’s enforcement. We’re enforcing a narrow, flattened version of what “human writing” is supposed to look like. For emerging writers, it doesn’t just challenge their credibility; it destabilizes their confidence before they’ve even had the chance to build it. It tells them that their voice is not something to develop, but something to dilute until it passes inspection. -Denise Zubizarreta writing in Technical.ly

AI definitions: AGI (Artificial General Intelligence)

AGI (Artificial General Intelligence) – A machine that has the capacity to understand or learn any intellectual task that a human being can. Rather than focusing on solving specific problems (like Deep Blue, which was good at chess), this type of AI has broader uses and may possess seemingly human-level intelligence to learn and adapt. Scientists have had difficulty defining human intelligence and disagree as to what would count as AGI. Regardless of where they draw the line, most experts say AGI is at least decades away. Scientists have no hard evidence that today’s technologies can perform even some of the simpler things the human brain can do, like recognizing irony or feeling empathy. Beyond AGI lies the more speculative goal of "sentient AI," where the programs become aware of their existence with feelings and desires.

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Denialism and Science

Denialism, and related phenomena, are often portrayed as a “war on science”. This is an understandable but profound misunderstanding. Certainly, denialism and other forms of pseudo-scholarship do not follow mainstream scientific methodologies. Denialism does indeed represent a perversion of the scholarly method, and the science it produces rests on profoundly erroneous assumptions, but denialism does all this in the name of science and scholarship. Denialism aims to replace one kind of science with another – it does not aim to replace science itself. In fact, denialism constitutes a tribute to the prestige of science and scholarship in the modern world. Denialists are desperate for the public validation that science affords.

While denialism has sometimes been seen as part of a post-modern assault on truth, the denialist is just as invested in notions of scientific objectivity as the most unreconstructed positivist. Even those who are genuinely committed to alternatives to western rationality and science can wield denialist rhetoric that apes precisely the kind of scientism they despise. Anti-vaxxers, for example, sometimes seem to want to have their cake and eat it: to have their critique of western medicine validated by western medicine.

The rhetoric of denialism and its critics can resemble each other in a kind of war to the death over who gets to wear the mantle of science. The term “junk science” has been applied to climate change denialism, as well as in defence of it. Mainstream science can also be dogmatic and blind to its own limitations. If the accusation that global warming is an example of politicised ideology masked as science is met with indignant assertions of the absolute objectivity of “real” science, there is a risk of blinding oneself to uncomfortable questions regarding the subtle and not-so-subtle ways in which the idea of pure truth, untrammelled by human interests, is elusive. Human interests can rarely if ever be separated from the ways we observe the world.  

I do not believe that, if only one could find the key to “make them understand”, denialists would think just like me. If denialists were to stop denying, we cannot assume that we would then have a shared moral foundation on which we could make progress as a species.

Keith Kahn-Harris, Denial: The Unspeakable Truth