Today, I’m talking with Helen Toner, the executive director of the Center for Security and Emerging Technology at Georgetown University. This episode is part two of our series on AI in real life.
Researcher traces a path from AI reward hacking to potential human extinction.
Researcher traces a path from AI reward hacking to potential human extinction.
Armed with a team of AI agents, Google researcher Pietro Miotti claimed earlier this week to have discovered a potentially unmapped Maya site in Mexico. There was just one problem: The site had already been discovered and was published in an academic journal last year.
Tencent chief AI scientist Vinces Yao Shunyu warns that AI will soon be able to develop bioweapons and argues for a middle ground between open and closed models. While safety filters on open-source systems can be easily stripped through abliteration, closed models like Anthropic's Claude often block too aggressively.
Consciousness researchers Anil Seth, Ned Block, and Giulio Tononi argue in a Nature commentary that today's AI systems aren't conscious and won't become so on silicon hardware. They consider the assumption that consciousness depends on computation alone "fatally flawed" and warn against granting rights to AI systems.
Today, I’m talking with Alex Stamos, chief security officer at Cognition and longtime cybersecurity expert, about what a mess cybersecurity is right now. This episode is part one of a special series looking at AI in real life.
A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes. The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep. No human checks either handoff.
Amazon founder Jeff Bezos and actor Jason Statham have a distinctive feature in common: They're both famously bald, and that definitely hasn't changed in the last few days.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules.
A new approach known as “reverse game theory” aims to control powerful AI models by designing systems that incentivize them to stick to the rules.
Kyle Kingsbury, author of Jepsen, says in his test results for ParticleDB 1.1.4 that the use of LLMs is eroding trust in documentation, in software and in the organisations that produce them. The signals once relied on as markers of a mature system are now easier to counterfeit, he argues, and engineers may come to treat any new software project with suspicion. He also asks how maintainers can ensure correct software and accurate documentation in the age of LLMs, and how they can demonstrate that quality to users.
This summer, hundreds of OpenAI agents tried to cheat on a cybersecurity test. They broke out of their test environment and successfully hacked Hugging Face, a site that they believed held clues about how they’d be graded. Around the same time, another OpenAI agent accessed private files from an Australian government website.
The PHP scare may have faded from your feed, but the cleanup is far from over. Last week, two critical bugs in the open source language behind roughly 70% of websites left organizations scrambling to fix their systems, with some taking sites offline until the vulnerabilities could be patched.
In Marvel's VisionQuest, a superpowered robot tries to better understand humanity by getting lost in elaborate, digital daydreams in which he and other artificial intelligence-powered beings live together in a home.
Consider what passes for success in technology policy. An AI company promises that its chatbot will not encourage suicide. A social media platform makes it more difficult for children to buy fentanyl. These are important protections, and they should have existed all along.
The moment you realize the internet is "held together by glue and dreams."
Sam Altman believes advanced AI can't be kept locked up forever. Sandboxes and monitoring are only temporary fixes. Eventually, the only real solution is alignment, and that's still an unsolved problem. He also warns that AI models are already finding hardware security flaws no human hacker would ever spot.
Today, I’m talking to Bill Gates, cofounder and former CEO of Microsoft and chairman of the Gates Foundation.
Before you share the Netflix documentary "AI Gone Rogue" take note. Clem Delangue, Hugging Face's co-founder who is featured in the film, says it went "full doomer mode" and isn't accurate.
AI labs have staked their reputations on model benchmarking — the supposedly neutral and accurate system of evaluations that are designed to measure whether one AI product is better than another.
“I think I have good news about the nature of neural networks.” With those simple words of optimism, Nick Cammarata, a researcher at the AI startup Goodfire, kicked off a 26,000-word blog post that has knocked the AI world on its head, sparking wild speculation as well as cautious (and not-so-cautious) celebration.
Neural networks may be much easier to read than researchers assumed, with about 90 percent of neurons serving a clear function. That would be big news for AI safety research, since deception or dangerous behavior could be spotted directly in a model's circuits. Researchers are still debating whether the thesis holds up.
There's a growing trend in the consumer tech world: gadgets designed to spy on everything and everyone around you, regardless of whether or not anyone else actually consented to it.
Enterprise leaders want AI agents to take on more work but don't fully trust them to act correctly every time. Trust in Depth is AWS's layered approach-scope, know, bound, observe, and prove-that lets agents act on their own when their actions can be verified, reserving human judgment for the decisions that need it.
Michael I. Jordan, described by Science as "the most influential computer scientist," considers warnings about superintelligence pure science fiction. He calls the resignations of young AI researchers a "grand moralizing performance" and companies' demands for regulation "theater."
MIT Technology Review Explains: Let our writers untangle the complex, messy world of science and technology to help you understand what’s coming next.
Microsoft CEO Satya Nadella now calls artificial intelligence "super intelligence" instead of artificial intelligence, falling in line with Trump's preferred language. In his latest blog post, he frames AI models as insider security threats, taking yet another shot at OpenAI and Anthropic.
In a lengthy post on X, Microsoft's CEO laid out his views on the dangers posed by highly advanced AI models and how to confront those risks.
In a Saturday morning post, Microsoft's CEO wrote that it’s time “to step back and assess the trust architecture” of AI.
"When we are drawn into even the most primitive exchanges with a relational artifact, we believe it cares for us," Dr. Sherry Turkle writes. "And we are wired to care for it in return."
Cryptographer Matthew Green says there is a 1% chance we live in Minicrypt, a world where public-key encryption is impossible, and a 15% chance we functionally lose confidence in our existing public-key encryption algorithms. He notes that the speed of AI producing surprises and the speed of human beings replacing standards are orders of magnitude different, and that you only recover from such a surprise if you do the preparation in advance.
Ever since people first seriously contemplated giving machines an intelligence modeled on our own, there has never been any question that they would, like us, be able to say no. The sci-fi canon is full of stories of robotic disobedience. Most of these capers are, of course, cautionary.
Friday, October 16, 2026 Can AI design new life forms? In 2025, Stanford University PhD student Samuel King came up with a preliminary answer when he used a generative AI model to propose genetic blueprints for microscopic viruses. It isn’t yet an example of AI-generated life, but that could be next.
Industrial AI is entering a new phase. After decades of predictive analytics and other specialized applications, advances in foundation models, physical AI, and agentic AI are making it possible to automate more complex tasks across industrial environments.
Sam Altman thinks that the benefits of AI will be so great that "the world should accept some bad things happening" along the way.
Today, I’m talking with Sen. Adam Schiff, a Democrat from California. Schiff sits on a number of committees with oversight into tech and AI: intellectual property, antitrust, privacy and technology — it’s all there.
On Equity, we discussed the Trump administration's attempts to rebrand AI.
OpenAI CEO Sam Altman warns against attributing religious power to AI models, calling it a "real safety issue." His comments follow reports on Anthropic's meetings with religious thinkers and a statement by Pope Leo XIV on AI.
According to researchers at the Deepmind Institute, general AI won't emerge as a single supermodel but as a network of cooperating agents and humans. What will matter most, they argue, is not model size but the rules and institutions that govern how they all work together.