AWS Machine Learning Blog 前天 04:27
New Amazon Bedrock Data Automation capabilities streamline video and audio analysis
index_new5.html
../../../zaker_core/zaker_tpl_static/wap/tpl_guoji1.html

 

Amazon Bedrock Data Automation 旨在帮助各行各业的企业处理海量非结构化音视频内容,以支持其核心业务应用。它简化了应用程序开发,并自动化了使用文档、图像、音频和视频内容的工作流程。通过预先封装的基础模型 (FM),将开发时间从数月缩短至数分钟,从而无需多个特定于任务的模型和复杂的处理逻辑。用户可以使用自然语言指令生成满足下游系统和应用程序需求的见解,例如从电影和电视节目中解锁自定义见解,或从音频中生成新的见解,从而提高生产力、增强客户体验并确保合规性。

🚀Amazon Bedrock Data Automation 通过预封装的基础模型,加速了开发流程,开发者无需再为处理大规模非结构化多模态内容而耗费大量时间,无论是分析PB级的视频还是处理数百万的客户对话。

🎬该工具允许用户自定义从视频中生成的见解,例如场景上下文或摘要、数据格式以及每个字段的自然语言指令,从而为AI驱动的多媒体分析应用程序生成特定格式的输出。例如,可以提取场景摘要、识别视觉上突出的对象以及检测电影、电视节目和社交媒体内容中的徽标。

🗣️Amazon Bedrock Data Automation 也简化了从音频中提取自定义生成式 AI 驱动的见解的过程。用户可以使用自然语言指定所需的输出配置,并从客户通话、临床讨论、会议和其他音频中提取摘要、关键主题和意图等自定义见解。

🏢Air 公司使用 Amazon Bedrock Data Automation 来处理数千万张图像和视频,能够以极短的时间从内容中提取特定的、定制的见解,例如视频章节、转录和光学字符识别,帮助创意团队快速组织他们的内容,将用户的搜索和组织时间缩短了 90%。

Organizations across a wide range of industries are struggling to process massive amounts of unstructured video and audio content to support their core business applications and organizational priorities. Amazon Bedrock Data Automation helps them meet this challenge by streamlining application development and automating workflows that use content from documents, images, audio, and video. Recently, we announced two new capabilities that you can use to get custom insights from video and audio. You can streamline development and boost efficiency through consistent, multimodal analytics that can be seamlessly customized to their specific business needs.

Amazon Bedrock Data Automation accelerates development time from months to minutes through prepackaged foundation models (FMs), eliminating the need for multiple task-specific models and complex processing logic. Now developers can eliminate the time-consuming heavy lifting of unstructured multimodal content processing at scale, whether analyzing petabytes of video or processing millions of customer conversations. Developers can use natural language instructions to generate insights that meet the needs of their downstream systems and applications. Media and entertainment users can unlock custom insights from movies, television shows, ads, and user-generated video content. Customer-facing teams can generate new insights from audio—analyzing client consultations to identify best practices, categorize conversation topics, and extract valuable customer questions for training.

Customizing insights with Amazon Bedrock Data Automation for videos

Amazon Bedrock Data Automation makes it painless for you to tailor your generative AI–powered insights generated from video. You can specify which fields you want to generate from videos, such as scene context or summary, data format, and the natural language instructions for each field. You can customize Amazon Bedrock Data Automation output by generating specific insights in consistent formats for AI-powered multimedia analysis applications. For example, you can use Amazon Bedrock Data Automation to extract scene summaries, identify visually prominent objects, and detect logos in movies, television shows, and social media content. With Amazon Bedrock Data Automation, you can create new custom video output in minutes. Or you can select from a catalog of pre-built solutions—including advertisement analysis, media search, and more. Read the following example to understand how a customer is using Amazon Bedrock Data Automation for video analysis.

Air is an AI-based software product that helps businesses automate how they collect, approve, and share content. Creative teams love Air because they can replace their digital asset management (DAM), cloud storage solution, and workflow tools with Air’s creative operations system. Today, Air manages more than 250M images and videos for global brands such as Google, P&G, and Sweetgreen. Air’s product launched in March 2021, and they’ve raised $70M from world class venture capital firms. Air uses Amazon Bedrock Data Automation to help creative teams quickly organize their content.

“At Air, we are using Amazon Bedrock Data Automation to process tens of millions of images and videos. Amazon Bedrock Data Automation allows us to extract specific, tailored insights from content (such as video chapters, transcription, optical character recognition) in a matter of seconds. This was a virtually impossible task for us earlier. The new Amazon Bedrock Data Automation powered functionality on Air enables creative and marketing teams with critical business insights. With Amazon Bedrock Data Automation, Air has cut down search and organization time for its users by 90%. Today, every company needs to operate like a media company. Businesses are prioritizing the ability to generate original and unique creative work: a goal achievable through customization. Capabilities like Amazon Bedrock Data Automation allow Air to customize the extraction process for every customer, based on their specific goals and needs.”

—Shane Hedge, Co-Founder and CEO at Air

Extracting focused insights with Amazon Bedrock Data Automation for audio

The new Amazon Bedrock Data Automation capabilities make it faster and more streamlined for you to extract customized generative AI–powered insights from audio. You can specify the desired output configuration in natural language. And you can extract custom insights—such as summaries, key topics, and intents—from customer calls, clinical discussions, meetings, and other audio. You can use the audio insights in Amazon Bedrock Data Automation to improve productivity, enhance customer experience, ensure regulatory compliance, among others. For example, sales agents can improve their productivity by extracting insights such as summaries, key action items, and next steps from conversations between sales agents with clients.

Getting started with the new Amazon Bedrock Data Automation video and audio capabilities

To analyze your video and audio assets, follow these steps:

    On the Amazon Bedrock console, choose Data Automation in the navigation pane. The following screenshot shows the Data Automation page.
    In the Create a new BDA Project screen under BDA Project name, enter a name. Select Create project, as shown in the following screenshot.
    Choose a Sample Blueprint or create a Blueprint

To use a blueprint, follow these steps:

Choosing a sample blueprint for video modality

Creating a new blueprint for audio modality

    Generate results for custom output
      On the video asset, within the blueprint, you can choose Generate results to see the detailed analysis.

    Choose Edit field – In the Edit fields pane, enter a field name. Under Instructions, provide clear, step-by-step guidance for how to identify and classify the field’s data during the extraction process.
    Choose Save blueprint.

Conclusion

The new video and audio capabilities in Amazon Bedrock Data Automation represent a significant step forward in helping you unlock the value of their unstructured content at scale. By streamlining application development and automating workflows that use content from documents, images, audio, and video, organizations can now quickly generate custom insights. Whether you’re analyzing customer conversations to improve sales effectiveness, extracting insights from media content, or processing video feeds, Amazon Bedrock Data Automation provides the flexibility and customization options you need while eliminating the undifferentiated heavy lifting of processing multimodal content. To learn more about these new capabilities, visit the Amazon Bedrock Data Automation documentation, and start building your first video or audio analysis project today.

Resources

To learn more about the new Amazon Bedrock Data Automation capabilities, visit:

    Amazon Bedrock Amazon Bedrock Data Automation Get insights from multimodal content with Amazon Bedrock Data Automation, now generally available Creating blueprints for video and Creating blueprints for audio in the documentation The What’s New post for the new video capability in Amazon Bedrock Data Automation The What’s New post for the new audio capability in Amazon Bedrock Data Automation


About the author

Ashish Lal is an AI/ML Senior Product Marketing Manager for Amazon Bedrock. He has 11+ years of experience in product marketing and enjoys helping customers accelerate time to value and reduce their AI lifecycle cost.

Fish AI Reader

Fish AI Reader

AI辅助创作,多种专业模板,深度分析,高质量内容生成。从观点提取到深度思考,FishAI为您提供全方位的创作支持。新版本引入自定义参数,让您的创作更加个性化和精准。

FishAI

FishAI

鱼阅,AI 时代的下一个智能信息助手,助你摆脱信息焦虑

联系邮箱 441953276@qq.com

相关标签

Amazon Bedrock 数据自动化 音视频分析 多模态内容处理
相关文章