Introduction: 基于ai的编解码器开发的基础
While many companies leverage AI to enhance the performance of existing codecs like H.264, HEVC和AV1，总部设在英国 深刻的呈现 正在开发一个完全基于人工智能的编解码器. To promote the understanding of AI codec development, 深刻的呈现's CTO and Co-founder, Arsalan征服者，推出了一个名为“基于ai的编解码器开发的基础: An Introductory Course." In a recent interview with 流媒体杂志, Zafar提供了对课程内容的见解, 目标受众, 以及预期结果.
Zafar began by explaining that 深刻的呈现's mission is "to pioneer the next generation of image and video codecs utilizing machine learning." Then he shared that in the five years since its inception, 深刻的呈现 developed the 世界上第一个AI编解码器, which he claimed delivered up to an 80% bandwidth savings over H.264.
扎法尔为什么要制作这个 课程? In his words, "Have you ever wondered how AI-based codecs work?“深度渲染一直沉浸在这一追求中, and Zafar wants to demystify it for the wider codec community. 要做到这一点, the 课程 explores the historical evolution of AI and machine learning, highlighting key milestones and recent advancements.
The 课程 starts with the fundamental principles of machine learning—architecture, 损失函数, and training—which are crucial for comprehending the underlying concepts of AI-based codecs. It then explores the architecture of AI-based codecs, demonstrating how neural network layers and machine learning primitives are configured to optimize compression efficiency. 制定目标函数, 哪一个定义了汇率扭曲的权衡, 是基于人工智能的压缩的一个关键方面. Zafar also explains how rate and distortion are defined in a differentiable manner, enabling efficient optimization through backpropagation.
Zafar then guides learners through the encoding and decoding process, highlighting the shift from traditional methods to a machine learning-driven approach. This practical approach to learning ensures that learners can apply the knowledge gained from the 课程 to real-world scenarios.
The 课程 later provides an overview of the production aspects of AI-based codecs, detailing the transition from training to inference regimes and the utilization of neural processing units for efficient execution. Then it explores the unique features and advantages of AI-based codecs, like adaptability to domain-specific content and scalability with hardware advancements. Zafar underscores the potential for rapid innovation and updates in the AI-based codec ecosystem, facilitating faster rollout and adaptation to evolving industry needs.
除了理论讨论, the 课程 offers practical demonstrations and examples of AI-based compression, showcasing both successful outcomes and potential challenges. Arsalan invites learners to engage with 深刻的呈现's demos and resources to further explore the capabilities of AI-based codecs.
The 课程 is designed for a highly technical audience, primarily video codec engineers who are looking to integrate AI-based codecs into their pipelines, though it's also useful to other technologists who simply want to explore the application of AI to video codec development. Zafar describes it as a primer on AI-based compression, exploring detailed algorithms while addressing real-world production considerations like the required 回放 platforms for distribution. 尽管时长只有16分钟, the 课程 provides a comprehensive overview of AI-video codec development, making it a valuable resource for anyone interested in this field.
这个免费的百家乐软件可以在YouTube上找到 http://bit.ly/AI_codec_course.
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