nerd

10 Jan 2026

10 Jan 2026 4:35am GMT

An anonymous reader quotes a report from Wired: [P]erhaps AI can, in fact, learn in a more human way -- by figuring out interesting questions to ask itself and attempting to find the right answer. A project from Tsinghua University, the Beijing Institute for General Artificial Intelligence (BIGAI), and Pennsylvania State University shows that AI can learn to reason in this way by playing with computer code. The researchers devised a system called Absolute Zero Reasoner (AZR) that first uses a large language model to generate challenging but solvable Python coding problems. It then uses the same model to solve those problems before checking its work by trying to run the code. And finally, the AZR system uses successes and failures as a signal to refine the original model, augmenting its ability to both pose better problems and solve them. The team found that their approach significantly improved the coding and reasoning skills of both 7 billion and 14 billion parameter versions of the open source language model Qwen. Impressively, the model even outperformed some models that had received human-curated data. [...] A key challenge is that for now the system only works on problems that can easily be checked, like those that involve math or coding. As the project progresses, it might be possible to use it on agentic AI tasks like browsing the web or doing office chores. This might involve having the AI model try to judge whether an agent's actions are correct. One fascinating possibility of an approach like Absolute Zero is that it could, in theory, allow models to go beyond human teaching. "Once we have that it's kind of a way to reach superintelligence," [said Zilong Zheng, a researcher at BIGAI who worked on the project].

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10 Jan 2026 2:56am GMT

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AI Is Intensifying a 'Collapse' of Trust Online, Experts Say

Experts interviewed by NBC News warn that the rapid spread of AI-generated images and videos is accelerating an online trust breakdown, especially during fast-moving news events where context is scarce. From the report: President Donald Trump's Venezuela operation almost immediately spurred the spread of AI-generated images, old videos and altered photos across social media. On Wednesday, after an Immigration and Customs Enforcement officer fatally shot a woman in her car, many online circulated a fake, most likely AI-edited image of the scene that appears to be based on real video. Others used AI in attempts to digitally remove the mask of the ICE officer who shot her. The confusion around AI content comes as many social media platforms, which pay creators for engagement, have given users incentives to recycle old photos and videos to ramp up emotion around viral news moments. The amalgam of misinformation, experts say, is creating a heightened erosion of trust online -- especially when it mixes with authentic evidence. "As we start to worry about AI, it will likely, at least in the short term, undermine our trust default -- that is, that we believe communication until we have some reason to disbelieve," said Jeff Hancock, founding director of the Stanford Social Media Lab. "That's going to be the big challenge, is that for a while people are really going to not trust things they see in digital spaces." Though AI is the latest technology to spark concern about surging misinformation, similar trust breakdowns have cycled through history, from election misinformation in 2016 to the mass production of propaganda after the printing press was invented in the 1400s. Before AI, there was Photoshop, and before Photoshop, there were analog image manipulation techniques. Fast-moving news events are where manipulated media have the biggest effect, because they fill in for the broad lack of information, Hancock said. "In terms of just looking at an image or a video, it will essentially become impossible to detect if it's fake. I think that we're getting close to that point, if we're not already there," said Hancock. "The old sort of AI literacy ideas of 'let's just look at the number of fingers' and things like that are likely to go away." Renee Hobbs, a professor of communication studies at the University of Rhode Island, added: "If constant doubt and anxiety about what to trust is the norm, then actually, disengagement is a logical response. It's a coping mechanism. And then when people stop caring about whether something's true or not, then the danger is not just deception, but actually it's worse than that. It's the whole collapse of even being motivated to seek truth."

Intel Is 'Going Big Time Into 14A,' Says CEO Lip-Bu Tan

Intel CEO Lip-Bu Tan says the company is "going big time" into its 14A (1.4nm-class) process, signaling confidence in yields and hinting at at least one external foundry customer. Tom's Hardware reports: Intel's 14A is expected to be production-ready in 2027, with early versions of process design kit (PDK) coming to external customers early this year. To that end, it is good to hear Intel's upbeat comments about 14A. Also, Tan's phrasing 'the customer' could indicate that Intel has at least one external client for 14A, implying that Intel Foundry will produce 14A chips for Intel Products and at least one more buyer. The 14A production node will introduce Intel's 2nd Generation RibbonFET GAA transistors; 2nd Gen BSPDN called PowerDirect that will connect power directly to source and drain of transistors, enabling better power delivery (e.g., reducing transient voltage droop or clock stretching) and refined power controls; and Turbo Cells that optimize critical timing paths using high-drive, double-height cells within dense standard cell libraries, which boost speed without major area or power compromises. Yet, there is another aspect of Intel's 14A manufacturing process that is particularly important for the chipmaker: its usage by external customers. With 18A, the company has not managed to land a single major external client that demands decent volumes. While 18A will be used by Intel itself as well as by Microsoft and the U.S. Department of Defense, only Intel will consume significant volumes. For 14A, Intel hopes to land at least one more external customer with substantial volume requirements, as this will ensure that Intel will recoup its investments in the development of such an advanced node.