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第78章 白浅苏的演讲

series data, which is crucial for applications such as language translation and time series prediction. 得益于长短期记忆网络(lstm)这种特殊类型的rnn算法,模型能够高效处理时间序列数据中的长期依赖关系,这在语言翻译和时间序列预测等应用中至关重要。

the development of generative adversarial works (gans) has also sparked a revolution in the field of artificial intelligence. 生成对抗网络(gans)的发展也在人工智能领域引发了一场革命。

a generative adversarial work consists of a generator that produces artificial data and a discriminator that distinguishes between real and artificial data. 一个生成对抗网络由一个生成人工数据的生成器和一个区分真实数据与人工数据的判别器组成。

through the mutual learning and petition between these two ponents, highly realistic images, videos, and even music can be generated. 通过这两个组件的相互学习和竞争,可以生成高度逼真的图像、视频,甚至音乐。

however, artificial intelligence not only brings about technological progress but also poses challenges. 然而,人工智能不仅带来了技术进步,也带来了挑战。

when developing artificial intelligence systems, ethical and responsible issues should always be taken seriously by us. 在开发人工智能系统时,伦理和责任问题始终应被我们重视。

we must ensure that algorithms are fair and do not cause discrimination. 我们必须确保算法是公平的,不会造成歧视。

in addition, when artificial intelligence systems process massive amounts of data, we also need to consider how to protect privacy. 此外,当人工智能系统处理海量数据时,我们也需要思考如何保护隐私。

i firmly believe that artificial intelligence will achieve even greater things in the future. 我坚信,人工智能在未来还将有更大的作为。

with the development of technologies such as edge puting, data processing will be carried out as close to the source as possible, which will significantly improve the response speed of artificial intelligence applications. 随着边缘计算等技术的发展,数据处理将尽可能在源头进行,这将显着提高人工智能应用的响应速度。

the integration of artificial intelligence with inter of things (iot) devices will make our lives mo

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