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  "text": "We asked the CEO of HuggingFace @ClementDelangue what the risks of releasing powerful open source models are.\n\nHe says restricting AI creates more risk than openness.\n\n\"Six, seven years ago, at the time it was GPT-2, and there was already a lot of people saying that it was too dangerous to release in open source.\"\n\n\"Mythos, when it was announced was crazy dangerous... In a few weeks or a few months, everyone is gonna be using Mythos, and not destroy the world as a result.\"\n\n\"For cybersecurity, the biggest risk is that a few players have capabilities that other people don't have... If you make it more open, it's usually easier for defenders to react and make the whole system safer.\"\n\n\"The idea of restricting a technology like AI based on risks is like saying, 'Some people can punch other people, so let's tie down everybody's hands.'\"\n\n\"Otherwise you slow down progress, you create massive gaps in terms of controls, in terms of capabilities, and you create actually additional risks.\"",
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    "text": "Weird how some people always target open-source in AI!\n \nFirst it was:\n“Open-source AI will destroy the world” (spoiler: it didn't and it won't)\nNow:\n“Open-source is a cybersecurity threat because of AI”\n\nBoth narratives are far too simplistic.\n\nThe truth is that the exact same risks exist in closed-source systems, often even more so. For example, in practice, APIs can create much bigger data and security vulnerabilities than open systems you can inspect, self-host, and secure yourself.\n\nAnd as with software more broadly, open-source often ends up more secure because it benefits from far more scrutiny than private internal systems.\n\nThe reality is not “open vs closed.”\n\nThe reality is that AI is raising cybersecurity stakes across the board, and we need to tackle that seriously together.",
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