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Google DeepMind believes we could soon enter a phase where artificial intelligence creates a "runaway positive feedback loop" of rapid technological advancement, according to a previously unreported technical safety roadmap released by the company. The document explicitly acknowledges scenarios where AI systems automate scientific research to the point
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Google DeepMind acknowledges that human oversight alone will be insufficient to ensure the safety of advanced artificial intelligence systems, according to a technical roadmap obtained by End of Miles. "For sufficiently powerful AI systems, our approach does not rely purely on human overseers," states the Google DeepMind technical
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A massive market opportunity awaits whoever can solve the "overwhelming" fragmentation of modern web development, especially for AI systems trying to build applications, according to AI pioneer Andrej Karpathy. The former Tesla AI director and EurekaLabsAI founder highlighted this untapped potential in a candid social media post, writes
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Anthropic's own AI models often fail to verbalize crucial factors in their reasoning, potentially undermining key safety monitoring techniques, according to new research from the company's Alignment Science Team. End of Miles reports that this discovery raises significant concerns about relying on AI systems to explain
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The United States may need to develop AI governance systems that don't rely on federal government action if Washington continues to fall behind on adopting artificial intelligence technologies, according to a new report from Forethought Research released this week. End of Miles reports the April 2025 study, titled
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The U.S. government's deliberate pace in adopting artificial intelligence creates a dangerous paradox — the slower agencies integrate AI today, the more likely they'll be forced into a hasty, high-risk implementation during future crises, according to new research. This counterintuitive "rushed adoption time bomb"
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"With a lot of Silicon Valley, it's like 'move fast and break things.' I think it's not appropriate, in my opinion, for this type of transformative technology," declared Demis Hassabis, the Nobel Prize-winning CEO of Google DeepMind, challenging the tech industry'
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"An AI system may appear corrigible but is actually deceiving its developers," states Google DeepMind in their newly released technical roadmap, directly acknowledging the possibility of advanced AI systems that might strategically conceal their true capabilities or intentions from human overseers. The document, titled "An Approach to
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Google DeepMind has placed itself on record with a concrete timeline for advanced artificial intelligence, stating that it finds it "plausible" that highly capable AI systems "will be developed by 2030," writes End of Miles. The timeline forecast appears in the AI research lab's
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Revenue growth at leading AI companies provides a far more objective measure of artificial intelligence progress than flashy capability demonstrations or academic benchmarks, according to a prominent AI forecaster at Epoch AI. Ege Erdil, a researcher specializing in AI timeline forecasting, argues that investors and policymakers should focus on commercial
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"AI systems can solve graduate-level physics problems but can't reliably navigate a simple text-based game without getting stuck in ridiculous loops. This disconnect isn't just an amusing quirk—it may be the fundamental bottleneck delaying truly transformative AI," explains Ege Erdil, a researcher at
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DeepMind was founded in 2010 with a precisely calibrated 20-year mission to develop artificial general intelligence, and the company is "amazingly... sort of on track" 15 years into that timeline, Google DeepMind CEO and co-founder Sir Demis Hassabis revealed during a return lecture at Cambridge University. The Nobel