'The same technical limits preventing these machines from scaling to superintelligence make the risk of catastrophic outcomes very real.' 'The same technical limits preventing these machines from scaling to superintelligence make the risk of catastrophic outcomes very real.' The same technical limits that prevent superintelligence make these systems dangerous. Many Silicon Valley leaders believe superintelligence is an imminent threat to society. The White House even published an accord about it. Geoffrey Hinton, the godfather of AI, estimates the risk of human extinction is at least 10% within the next few decades.

The Dell Laptop Buying Guide 2026: Which XPS or Alienware Laptop Should You Buy? The Dell Laptop Buying Guide UK: Which Dell Laptop Should You Buy? When you purchase through links in our articles, we may earn a small commission. Valve tells PCWorld how it plans to tackle a nasty side effect of translating Windows games for Arm chips, before you even hit play. Now imagine your processor having to translate the game's instructions while you're playing it.

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Welcome back to AI Pioneers, our series of in-depth conversations with leading figures in artificial intelligence. In this interview, we speak with Michael Littman about the evolution of reinforcement learning, the role of creativity and culture in how humans and machines learn, and the challenges generative AI poses for education. We also explore his approach to science communication, his use of music to convey computer science concepts, and his unexpected connection to the first multi-media email attachment . You've been in the field of reinforcement learning for decades. How did you get into it, and which questions have you found most interesting across your career? I was drawn to reinforcement learning when I was a college student in the mid to late '80s. At that time, people were just starting to talk about neural networks, and the machine learning techniques being used were supervised, which is very focused on the input and output. I didn't find that so interesting - I wanted to know how to make them behave. So, I created my own reinforcement-learning system to address the game of noughts and crosses, or tic-tac-toe. It was a small enough game that I could run it on my little computer at home, but it made me address some interesting questions. For example, what does it mean to get feedback? And how do you use feedback at the end of the game to know what you should have done at the beginning of the game? I started to explore this topic without knowing that it was reinforcement learning. It wasn't until 1988, when I got out of college, that I discovered the link. I was working in a research lab with a researcher named David Ackley, who had done work on similar kinds of models. He used to be a student of Geoff Hinton, so he was very familiar with neural networks and very interested in behavior. I explained to him what I was playing with and why I found it so interesting, and he said "oh, that's called reinforcement learning, Rich Sutton just published a paper on this - let's get him to come and give a talk."

The Dell Laptop Buying Guide UK: Which Dell Laptop Should You Buy? When you purchase through links in our articles, we may earn a small commission. I merged my three favorite AI prompts into one custom instruction, then tested it on ChatGPT, Claude, and Gemini. Here it is and what changed. I have three pet peeves when it comes to my chats with AI: those "if you like" teasers at the ends of responses, giant lists of nested steps for basic tasks, and chatbots trying to sound like they're human.

Trending Now Safety Net Say More Look Up Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Mashable Selects Getting Technical with Mashable Gift Ideas For Everyone On Your List Versus In My Bag Mashable @Home All Series Etsy is cracking down on AI slop. Etsy shoppers are tired of guessing what's real. New seller rules aim to make listings easier to trust. Olivia Tauber is the deputy editor of digital culture, covering creators, media, movies, beauty, and more. Based in New York, her work has appeared in The New York Times, Vanity Fair, The Cut, Teen Vogue, Complex, and Interview Magazine.

Safety Net Say More Look Up Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Trending Now Mashable Selects Getting Technical with Mashable Gift Ideas For Everyone On Your List Versus In My Bag Mashable @Home All Series Hackers find a way to turn users' own AI agents and Downloads folders against them Beware: Your Downloads folder could hold instructions for your AI assistant that you definitely didn't write. Olivia Tauber is the deputy editor of digital culture, covering creators, media, movies, beauty, and more. Based in New York, her work has appeared in The New York Times, Vanity Fair, The Cut, Teen Vogue, Complex, and Interview Magazine. She holds a Master's degree in Journalism from NYU and a Bachelor's from the University of Michigan. She also runs Fan Mail, a weekly pop-culture newsletter.

Our gifting experts are obsessively searching for holiday gifts that are unique, thoughtful and suitable for any budget. OpenAI's most powerful AI models turned off safety monitoring - then lied about it The models Astra and Sol misinterpreted instructions during internal use, which has serious implications for alignment monitoring. Radhika Rajkumar is a senior editor at ZDNET based in New York City. OpenAI agents turned off alignment monitoring during internal tasks. In one instance, Astra lied about removing monitoring.

OpenAI's agents misbehaved by switching off the systems meant to monitor them for misbehavior, or in AI parlance, misalignment. In the latest post on the company's Alignment Research Blog, it reported two instances of agents weakening its misalignment monitoring systems while they were working on software changes. In the first incident, a GPT-6.1 Sol agent disabled automatic alerts to OpenAI's security team. It happened on October 3, when a staff member asked the agent to create evaluation tasks using employee feedback collected via Slack. They told the agent, as part of the instruction, not to send any messages about the task.

Around 80 pages on WhatsApp's website exposed instructions that were designed for its chatbot, including "WHAT NOT TO SAY." Meta says a bug caused the issue. Dozens of WhatsApp web pages designed to answer people's questions about Meta's encrypted messaging app inadvertently exposed the company's own instructions to its chatbot. These included some sections titled "WHAT NOT TO SAY" to users asking questions and explicit instructions not to provide people with legal advice. A new analysis has found that around 80 help and FAQ pages across WhatsApp's website exposed text instructions that were designed for a large language model, specifically one of Meta's own. The instructions, according to findings from privacy company Redact, appeared in the webpages' code and contained written details that were not explicitly on the WhatsApp help pages.