AI at Scale for Media Workflows: Mining Insights from Media to Produce Great Content

Bloomberg

Today’s media companies take in massive amounts of information in real-time and must quickly turn it into meaningful content or stories. That means screening all that information and making quick decisions about what to publish. It is a significant business challenge. And it gets even more complicated when the content cycle fluctuates, causing resources to be overextended at some times and underutilized at others

Artificial intelligence and machine learning present an opportunity to accelerate the screening process. But how do you harness the power of AI? How do you scale it in an organization? How do you seamlessly integrate it with existing workflows? Those are the barriers to adoption that many organizations have encountered.

Transcription solutions from Digital Nirvana are a highly effective way to overcome those barriers. Digital Nirvana’s cloud-based infrastructure makes it possible to scale to a large volume, and volumes can go up or down at a moment’s notice. Also, using AI and machine learning, we can create a speech-to-text (STT) engine that is specific to any industry. The STT engine produces highly accurate transcripts that yield metadata media companies can use to mine insights from massive amounts of incoming data. And the solutions can be integrated into any workflow.

Several media companies have implemented Digital Nirvana transcription solutions for highvolume scenarios.

AI at Scale for Media Workflows: Mining Insights from Media to Produce Great Content

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