回到家，蓝羽推门时，玄关感应灯应声亮起。
她摘下智能手环随意扔在玄关柜上，金属与玻璃碰撞出清脆声响，惊飞了栖在阳台绿植上的机械蜂鸟——那是她少年时研发的初代作品，如今只剩外壳在月光下泛着陈旧的银灰色。
浴室蒸腾的水雾模糊了镜面，蓝羽将水温调到最高，任滚烫的水流冲刷着后颈。
裴砚琛替刘月切牛排的画面却挥之不去，他握着刀叉的姿势，指节泛白的力度里藏着近乎偏执的温柔。
是她曾经想都不敢想到事。
而此刻，这份温柔隔着红酒杯、隔着林叙白的谈笑，刺得她眼眶发烫。
手机在洗手台震动，是许柏年发来的合作细节补充文件。
蓝羽裹着浴巾点开，全息投影在氤氲水汽中亮起，跳动的数据却逐渐扭曲成刘月腕间的四叶草手链。
她烦躁地挥散投影，水珠顺着发梢滴落在锁骨，突然想起裴砚琛曾这处像盛着月光的盅。
——
裴砚琛、刘月、云熠乾和段绍阳四个人有一个群，有什么趣事或要事，只要是和四个人有关的，他们会在群里分享。
这段绍阳突然甩了一个视频进群。
刘月看到了:“?”
她不明白段绍阳的意思。
段绍阳“视频里是白浅苏10岁的时候做的演讲。”
刘月兴奋地:“真的吗？我先看看。”
Ladies and gentlemen, dear colleagues! 女士们、先生们，亲爱的同行们！
my name is bai qiansu. 我叫白浅苏。
I am very grateful for the opportunity to municate ith you about the development trends of artificial intelligence at harvard University, this academic institution full of an academic atmosphere. 我非常感谢能有机会在哈佛大学，这座充满学术氛围的学府，与大家交流人工智能的发展趋势。
As someone ho has been deeply engaged in the study of technology for many years, I have itnessed the development of artificial intelligence up close and am fascinated by its potential. 作为多年来一直深入研究技术的人，我近距离见证了人工智能的发展，并对其潜力深感着迷。
In recent years, artificial intelligence has made significant progress, especially in the fields of deep learning and machine learning. 近年来，人工智能取得了重大进展，特别是在深度学习和机器学习领域。
Neural netorks such as convolutional neural netorks (cNNs) and recurrent neural netorks (RNNs) have made it possible to identify plex patterns in image, audio data, and text. 像卷积神经网络（cNNs）和循环神经网络（RNNs）这样的神经网络，使识别图像、音频数据和文本中的复杂模式成为可能。
thanks to a special type of RNN algorithm called long short-term memory (LStm), models are able to efficiently handle long-term dependencies in time series data, hich 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 netorks (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 netork consists of a generator that produces artificial data and a discriminator that distinguishes beteen 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 beteen these to 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。
hoever, 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。
hen developing artificial intelligence systems, ethical and responsible issues should alays 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。
e 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, hen artificial intelligence systems process massive amounts of data, e also need to consider ho 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 ill 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。
ith the development of technologies such as edge puting, data processing ill be carried out as close to the source as possible, hich ill 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 ith Internet of things (Iot) devices ill make our lives more convenient and efficient. 人工智能与物联网（Iot）设备的集成，将使我们的生活更加便捷和高效。
I look forard to future developments and ill continue to delve into these fascinating technologies. 我期待未来的发展，并将继续钻研这些迷饶技术。
thank you all for listening, and I am looking forard to having a lively discussion ith you! 感谢大家的聆听，我期待与大家展开热烈的讨论！
台下响起热烈的掌声，然后视频就结束了。
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