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An anonymous reader shares a report: Costing tens of thousands of dollars each, Nvidia's pioneering AI chips make up a hefty chunk of the $400 billion that Big Tech plans to invest this year -- a bill expected to hit $3 trillion by 2029. But unlike 19th-century railroads, or the Dotcom boom's fiber-optic cables, the GPUs fueling today's AI mania are short-lived assets with a shelf life of perhaps five years. As with your iPhone, this stuff tends to lose value and may need upgrading soon because Nvidia and its rivals aim to keep launching better models. Customers like OpenAI will have to deploy them to stay competitive. So while it's comforting that the companies spending most wildly have mountains of cash to throw around (OpenAI aside), the brief useful life of the chips and the generous accounting assumptions underpinning all of this investment are less consoling. Michael Burry, who made his name betting against US housing and who's recently turned to the AI boom, waded in this week, warning on X that hyperscalers -- industry jargon for the giant companies building gargantuan data centers -- are underestimating depreciation. Far from being a one-off outlay, there's a danger of AI capex becoming a huge recurring expense. That's great for Nvidia and co., but not necessarily for hyperscalers such as Google and Microsoft. Some face a depreciation tsunami that's forcing them to be extra vigilant about controlling other costs. Amazon has plans to eliminate roughly 14,000 jobs. And while Wall Street is used to financing fast-depreciating assets such as aircraft and autos, it's worrying that private credit funds are increasingly using GPUs as collateral to finance loans. This includes lending to more speculative startups known as neoclouds, who offer GPUs for rent. Microsoft alone has signed more than $60 billion of neocloud deals.

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Researchers from four universities have released a study revealing that AI models remain easily detectable in social media conversations despite optimization attempts. The team tested nine language models across Twitter/X, Bluesky and Reddit, developing classifiers that identified AI-generated replies at 70 to 80% accuracy rates. Overly polite emotional tone served as the most persistent indicator. The models consistently produced lower toxicity scores than authentic human posts across all three platforms. Instruction-tuned models performed worse than their base counterparts at mimicking humans, and the 70-billion-parameter Llama 3.1 showed no advantage over smaller 8-billion-parameter versions. The researchers found a fundamental tension: models optimized to avoid detection strayed further from actual human responses semantically.

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An anonymous reader quotes a report from Ars Technica: Ryanair is trying to force users to download its mobile app by eliminating paper boarding passes, starting on November 12. As announced in February and subsequently delayed from earlier start dates, Europe's biggest airline is moving to digital-only boarding passes, meaning customers will no longer be able to print physical ones. In order to access their boarding passes, Ryanair flyers will have to download Ryanair's app. "Almost 100 percent of passengers have smartphones, and we want to move everybody onto that smartphone technology," Ryanair CEO Michael O'Leary said recently on The Independent's daily travel podcast. Customers are encouraged to check in online via Ryanair's website or app before getting to the airport. People who don't check in online before getting to the airport will have to pay the airport a check-in fee. "There'll be some teething problems," O'Leary said of the move.

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According to the Financial Times (paywalled), Meta's Chief AI Scientist Yann LeCun, a deep-learning pioneer and Turing Award winner, is reportedly leaving the company to launch his own startup. Reuters reports: The owner of Facebook and Instagram has significantly increased its investments in artificial intelligence, with CEO Mark Zuckerberg reorganizing the company's AI initiatives under Superintelligence Labs. Zuckerberg hired Alexandr Wang, former CEO of data-labeling startup Scale AI to lead the new AI effort. As a result, LeCun, who had reported to chief product officer Chris Cox, is now reporting to Wang, the report said. The company began investing in AI in 2013 by launching Facebook Artificial Intelligence Research (FAIR) unit and recruiting LeCun, who is a known skeptic of the large language model path to superintelligence. LeCun is also a Silver Professor of data science, computer science, neural science and electrical and computer engineering at New York University, according to his LinkedIn page. He is known for his work in deep learning and the invention of the convolutional neural network, which is widely used for image, video and speech recognition.

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