Why Moving AI to the Edge is Key to Enhancing Personalization and Performance in OTT Systems

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  2. Why Moving AI to the Edge is Key to Enhancing Personalization and Performance in OTT Systems

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Moving AI to the Edge is Key to Enhance Media Personalization and increase Performance of OTT Systems
OTT Business Podcast

Traditional broadcast and streaming TV media processing methods are struggling to keep up with the increasing demand for real-time content delivery and personalization. During my interview with Ananda Roy, Sr. Product Line Manager, Wireless Connectivity and Siddarth Chandrasekar, Sr. Director of Marketing from Synaptics at the IBC show, they explained that moving AI-driven media processing to the network edge can drastically reduce latency and bandwidth consumption by over 48%. This shift solves critical challenges like network congestion, high data transmission costs, and delayed content streaming—especially in OTT and streaming TV services. To solve this challenge, Synaptics has created chips and support processes that move AI-powered media processing into network edge or consumer devices that transforms media workflows, offering faster, smarter, and more efficient content delivery systems.

The top reasons why moving AI to the network edge and into consumer devices is important for OTT and Streaming TV systems and service providers include transmission delay (high latency), high bandwidth use and cost and the need for content personalization.

  1. Reduced Latency: By processing data closer to the user, AI at the edge enables faster responses and real-time adjustments, improving video quality and user experiences without the delays typically associated with cloud-based processing.
  2. Bandwidth Optimization: Edge AI helps reduce the amount of data sent back and forth to the cloud by handling tasks like content recommendations, personalization, and data analysis locally, freeing up network bandwidth for better streaming performance.
  3. Enhanced Personalization: AI at the edge allows for more immediate and accurate user behavior analysis, enabling OTT platforms to deliver highly tailored content recommendations, advertisements, and viewing experiences, which drives user engagement and satisfaction.
  4. User Privacy: Using AI processors at the edge helps to protect customers personal data and limits what is being sent to the cloud.

Synaptics.com provides to help move AI to the edge for OTT and Streaming TV systems are:

  1. Edge AI SoCs (System-on-Chip): Synaptics offers advanced AI-powered SoCs designed for low-power, high-performance edge processing, enabling devices to handle tasks like video optimization, facial recognition, and content personalization without relying on cloud infrastructure.
  2. Neural Processing Units (NPUs): Synaptics integrates dedicated NPUs into its hardware solutions, which accelerate AI computations at the edge, ensuring efficient real-time data analysis and decision-making for improved streaming performance and user engagement.
  3. Voice and Video AI Capabilities: Synaptics provides edge-based voice and video AI solutions that enhance user interactions, such as voice command recognition and real-time video enhancement, creating a more seamless and immersive experience for OTT viewers.
  4. Data Security: Synaptics ensures secure processing of private user information while enforcing DRM rules to provide authorized access to protected content. 

For more information on how to move AI media to the edge, go to Synaptics Accelerating AI Enabled Content.

Category: Video AI
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