Baidu AI Cloud Media and Entertainment China Translated from Chinese

People's Daily

People's Daily needed a unified intelligent-media platform that could speed up planning, creation, review and distribution across modern newsroom workflows while handling large video and data volumes.

The platform includes 18 key functions.
Traditional manual review of every 100,000 characters takes 3.3 days, while machine review can finish in seconds.

Reported impact

Business outcome

People's Daily gained an integrated AI newsroom foundation that accelerates multimedia production, review and distribution while making intelligent media tools usable in day-to-day editorial work.

  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

People's Daily and Baidu built 'Creation Brain' as an end-to-end intelligent media-production platform rather than a single feature. Under the hood, Baidu AI Cloud supplies the media cloud foundation for storage, compute, network access and AI chips, while media knowledge, intelligent creation and intelligent video platforms expose language, vision and knowledge-graph capabilities into editorial workflows. Those capabilities are mapped across the full newsroom chain: intelligent planning aggregates creative resources and recommends topics, intelligent collection and editing support article, video and short-form news generation, intelligent review performs multi-dimensional checking of text and media assets, and AI anchors expand reporting timeliness and coverage. The system therefore acts as a newsroom operating platform where large volumes of text, video, graphics and monitoring data are ingested, enriched and then distributed in multiple formats. Rather than only cutting labor, the architecture gives People's Daily a shared media-AI infrastructure layer for news production, analytics and content-governance tasks.

Data flow

Text, video, image and monitoring data flow into the Creation Brain platform, where planning and creation services generate newsroom assets, review services check them, and video and distribution modules publish the outputs across media channels.

Solution architecture

5 components · 4 layers
  1. Compute
    • Language Generation Technology Generates text-first news outputs and supports intelligent editorial assistance.
  2. Serving
    • Intelligent Internet Video Supports video-focused intelligent production workflows inside the newsroom platform.
    • Intelligent Video Platform Automates video editing, clipping and media-processing tasks.
  3. Orchestration
    • Intelligent Creation Platform Handles planning, writing, transformation and asset creation for media content.
  4. Governance
    • Media Knowledge Middle Platform Provides shared knowledge and AI capabilities across newsroom workflows.

Architecture clues

  • AI anchors are part of the same operating environment
  • Media cloud infrastructure is paired with specialized media knowledge, creation and video platforms
  • The platform spans planning, collection, editing, review and distribution

Evidence from the source

Baidu AI Cloud provides the cloud and AI foundation across planning, editing, review and publishing workflows (original: 基于百度智能媒体中台,助力新闻生产的策、采、编、审、发全流程).
People's Daily's 'Creation Brain' contains 18 key functions and serves as a one-stop intelligent-creation platform (original: 人民日报“创作大脑”具备……18项重点功能,是……一站式智能创作平台).
Review that takes 3.3 days per 100,000 characters manually can be completed in seconds by machine algorithms (original: 每十万字内容审校以传统人力方式需要3.3天,机器算法仅需秒级即可完成).
Transparency Evidence & methodology 90/100 reference value · 84% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence84%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Baidu AI Cloud

    People's Daily customer story

    First-party
    https://cloud.baidu.com/customer/case/peoples-daily.html
    Source type
    Vendor-published customer story
    Published
    Apr 9, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Apr 9, 2026 · Baidu AI Cloud · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.