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In the context of computational learning, the concept of 'probably approximately correct' (PAC) learning provides a framework for understanding the efficiency and feasibility of learning algorithms.
我们必须挑战传统智慧,并愿意为可持续的未来重塑我们的行业。
我们无权假设任何物理定律存在,或者即使它们至今存在,它们将来也会以类似的方式继续存在。