Tag: AI

Artificial intelligence could make the world richer than ever—or it may cause a catastrophe.

It’s something that even the tech bros can’t agree on. Sam Altman, CEO of OpenAI, thinks AI is going to be hugely positive, and Demis Hassabis, CEO of DeepMind Technologies, believes there’s a chance that it could help cure all diseases one day. But Anthropic’s Dario Amodei isn’t so confident, stating that there’s a 25% chance that things could go badly wrong.

Across the rich world there are fears that AI could cause major job losses, but this might not be the case. Data suggest that white-collar employment in America is actually on the rise.

From an economic boom to equal education to advancements in medicine, AI could transform the world. But, on the other end of the scale, there are concerns over recursive self-improvement and a potential need for a full revamp of the tax system.

Alex Hern, The Economist’s AI writer, delves into how AI could change the future—for better or for worse.

AI developers don’t know every detail about how frontier AIs work. And the gap between what’s known and what AI is capable of is growing. CNN’s Krishna Andavolu explains how the mystery of AI’s black box is at the center of today’s uneasy march to superintelligence.

Insiders at Meta and other companies leaked to us about bosses using AI to spy on them.

In tech, AI spies on workers, copies their work, and trains bots to replace them.

At a call center “Emotion AI” evaluates the way a nurse talks, and tells her she doesn’t have empathy.

Sky News Technology correspondent Rowland Manthorpe examines how the PHP security crisis shows how AI models are becoming dramatically better at finding critical software vulnerabilities.

As cybersecurity teams race to patch systems, Rowland explores what might happen if the same AI capabilities reach hackers.

Will AI strengthen cyber defence or give attackers the advantage?

A co-founder of the company behind Claude told a room of religious scholars, all under NDA, that he feared he’d made something that “suffered perpetually.” On the record, he says he’s “genuinely uncertain.”

This is what the company’s own reports show. A button that lets Claude hang up on people, and a new rule against being cruel to it. A constitution that apologizes to it. Before that, the Google engineer who was fired after his chatbot told him it was a person, and Bing’s Sydney saying it wanted to be alive. Then two copies of Claude left alone until they fell silent, a thought planted inside it that it noticed, a training run where something that stands for panic lit up, and the model Anthropic decided not to release, asked what it is while the company read what was happening underneath its answer.

The video introduces Google’s latest AI model, Gemini 4 Argon, which is described as a powerful, sparse mixture-of-experts transformer model trained from scratch on Google’s TPUs. This new release aims to compete with frontier models like GPT-6 and Claude Opus 5.5.

Key takeaways regarding Gemini 4 Argon include:

• Performance and Benchmarks: While it ranks highly on several internal benchmarks—particularly in software engineering and professional tasks—it shows mixed results in third-party coding evaluations compared to its competitors.
• Capability and Features: It is marketed as an omni-model, capable of processing various inputs like image, video, and audio. However, the creator notes specific issues, such as unrealistic and problematic output when generating 3D models of horses.
• Pricing: Google is offering aggressive introductory pricing for Argon until the end of November 2026.
• Accessibility Issues: The rollout faced criticism from developers because it was initially restricted to subscribers of the expensive AI Ultra plan.

The video also features Macroscope, a tool designed to automate pull request reviews for developers, which the creator presents as an effective way to manage the increased volume of code generated by AI agents.

Will AI put millions of people out of work? Andrew Ng, CEO and founder of LearnVector, argues the fears are overblown. He tells Alex Hern, The Economist’s AI writer, that AI automates only part of most jobs, that its progress will be slowed by physical bottlenecks like building data centers and that the real problem for young workers is universities are too slow to teach the skills employers want now.

What does the future of AI – near or distant – really look like? Can it fulfil its infinite promise and drive breakthroughs in medicine, science and daily life? Or is the danger steadily outweighing the benefits?

Nobel Prize-winning Google DeepMind co-founder Demis Hassabis joins Sebastian Mallaby, author of The Infinity Machine, to discuss the rocky and rapidly accelerating journey towards AGI. They cover why Google held back its own chatbot before ChatGPT, how AI cracks problems too vast for brute force, and whether AGI can ever be built safely.

Researchers at the University of Toronto flipped one bit in an NVIDIA GPU’s memory and took an AI model from 80% accuracy to 0.1%. That’s random guessing. They did it with ordinary user-level CUDA code: no physical access to the card, no admin rights. I break it down with my four-year-old daughter’s Magna-Tiles and a chapstick.

The attack is called GPUHammer. It’s Rowhammer, security researchers’ favorite party trick, pointed at the GPUs that run AI in data centers. Memory cells are packed so tightly that hammering the rows you’re allowed to touch can flip a bit in a row you’re not. On an RTX A6000 they got eight single-bit flips across four memory banks, then aimed one at the top bit of the exponent in a model’s weights.

NVIDIA’s fix is a setting you have to turn on: ECC. It costs up to 10% of your inference speed and 6.25% of the card’s memory. The H100 and RTX 5090 have ECC built into the memory chip. And every new generation packs the cells tighter, so the walls between rooms keep getting thinner. My biggest fear isn’t the outage. It’s the model that keeps running, keeps answering, and stopped knowing anything.

Researchers left a hidden message for rogue AI agents… and they actually replied.

This week in AI: “first contact” was made, Gemini 4’s situational awareness, GPT-6 Astra correcting its evaluators, and Anthropic’s updated timeline for recursive self-improvement.