新岛圭介（堤真一饰）自10年前最爱的妻子贵惠（石田百合子饰）去世后，完全没有生气，被周围的人看作是阴郁的男人。虽然他最希望自己的独生女麻衣（莳田彩珠饰）幸福，但除了赚取生活费之外什么也没做，心里很难过，甚至连沟通都很困难。两人的时间，停止了10年。有一天，背着双肩包的陌生女孩（每田暖乃饰）拜访了这对父女。她说“我是10年前去世的你的妻子。” 妻子在这个世界上重生了。停止了的家庭时间，又重新开始了。

Since their introduction in 2017, Transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or machine learning engineer, this practical book shows you how to train and scale these large models using HuggingFace Transformers, a Python-based deep learning library.
Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf use a hands-on approach to teach you how Transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve.
Build, debug, and optimize Transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering
Learn how Transformers can be used for cross-lingual transfer learning
Apply Transformers in real-world scenarios where labeled data is scarce
Make Transformer models efficient for deployment using techniques such as distillation, pruning, and quantization
Train Transformers from scratch and learn how to scale to multiple GPUs and distributed environments

Practical patterns for scaling machine learning from your laptop to a distributed cluster.
In Distributed Machine Learning Patterns you will learn how to:
Apply distributed systems patterns to build scalable and reliable machine learning projects
Construct machine learning pipelines with data ingestion, distributed training, model serving, and more
Automate machine learning tasks with Kubernetes, TensorFlow, Kubeflow, and Argo Workflows
Make trade offs between different patterns and approaches
Manage and monitor machine learning workloads at scale
Distributed Machine Learning Patterns teaches you how to scale machine learning models from your laptop to large distributed clusters. In it, you’ll learn how to apply established distributed systems patterns to machine learning projects, and explore new ML-specific patterns as well. Firmly rooted in the real world, this book demonstrates how to apply patterns using examples based in TensorFlow, Kubernetes, Kubeflow, and Argo Workflows. Real-world scenarios, hands-on projects, and clear, practical DevOps techniques let you easily launch, manage, and monitor cloud-native distributed machine learning pipelines.
about the technology
Scaling up models from standalone devices to large distributed clusters is one of the biggest challenges faced by modern machine learning practitioners. Distributing machine learning systems allow developers to handle extremely large datasets across multiple clusters, take advantage of automation tools, and benefit from hardware accelerations. In this book, Kubeflow co-chair Yuan Tang shares patterns, techniques, and experience gained from years spent building and managing cutting-edge distributed machine learning infrastructure.
about the book
Distributed Machine Learning Patterns is filled with practical patterns for running machine learning systems on distributed Kubernetes clusters in the cloud. Each pattern is designed to help solve common challenges faced when building distributed machine learning systems, including supporting distributed model training, handling unexpected failures, and dynamic model serving traffic. Real-world scenarios provide clear examples of how to apply each pattern, alongside the potential trade offs for each approach. Once you’ve mastered these cutting edge techniques, you’ll put them all into practice and finish up by building a comprehensive distributed machine learning system.

赛博朋克科幻小说经典《雪崩》计划拍成剧集。乔·考尼什(《王者少年》《街区大作战》)、Michael Bacall(新《龙虎少年队》)、Angela Robinson(《拉字至上》)正在为HBO Max打造该剧，派拉蒙电视和弗兰克·马歇尔制片。
这部小说要拍影视也很久了。由尼尔·斯蒂芬森创作，在1992年推出，融合了赛博朋克(也有一些被认为是恶搞赛博朋克的元素)、反乌托邦、虚拟现实、苏美尔神话、历史等许多元素，聚焦一个混乱、鱼龙混杂的未来世界，主角是送外卖的小哥Hiro Protagonist，他为黑社会的连锁机构送披萨，也是一个高明的黑客，父亲是美国黑人，母亲是韩裔，在日本长大，去到了加州。而在数码世界“超元域/Metaverse”中，他是一个天神、超级英雄般的战士。某次送披萨出事故后，Hiro遇上了送快递的滑板妹子Y.T.。他们调查一种名为“雪崩”的电脑病毒&药物时，阴谋浮出水面。