Welcome to the heart of AI innovation, where we unravel the transformative possibilities for media, entertainment, and communication companies. This page on AI use cases is your gateway to a world of real-world applications, exploring how artificial intelligence reshapes the very fabric of our industry. From optimizing production workflows and unlocking new realms of monetization to fortifying data strategies and streamlining distribution and delivery, we’re uncovering the extraordinary ways AI revolutionizes the core elements of our field.
These are more than a collection of use cases; it’s a roadmap for media, entertainment, and communication professionals venturing into the AI landscape. Let’s explore together, pushing boundaries and discovering how AI can propel our industry into a future defined by efficiency, creativity, and unparalleled possibilities.
Production
AI-driven ‘Magic Moments’ Extraction
Tata Elxsi Use Case
Use Case: Generate “magic moments” that captivate and engage audiences by analysing viewer preferences, content attributes, and narrative structures.
Intuitive ML models extract emotive clips and generate catchup TV content, enhancing the entertainment value and viewer satisfaction by strategically placing these moments within the content.
How it Works: Deep Learning models analyse viewer data, including reactions, sentiment, and engagement, to identify resonating moments in content.
Tech Stack
- Deep Learning models
Automated Content Generation
Tata Elxsi Use Case
Use Case: Content creators can deploy AI to automatically generate news articles, reports, and other content types.
This automation reduces the time and effort required for routine reporting tasks and can also be used by news organisations.
How it Works: Natural language generation (NLG) algorithms analyse structured data sources and convert them into coherent, human-readable narratives.
Tech Stack
- Natural Language Processing (NLP):
- GPT-like Models
- Language Models
- Generative Adversarial Networks(GANs):
- Image and Video Generation
- Style Transfer
- Diffusion Models
Automated Content Generation
Tata Elxsi Use Case
Use Case: Content creators can deploy AI to automatically generate news articles, reports, and other content types.
This automation reduces the time and effort required for routine reporting tasks and can also be used by news organisations.
How it Works: Natural language generation (NLG) algorithms analyse structured data sources and convert them into coherent, human-readable narratives.
Tech Stack
- Natural Language Processing (NLP):
- GPT-like Models
- Language Models
- Generative Adversarial Networks(GANs):
- Image and Video Generation
- Style Transfer
- Diffusion Models
Virtual Performers and Characters
Use Case: In the entertainment industry, AI is used to create virtual performers and characters for various purposes, including music concerts, live performances, animated movies, and interactive video games.
How it Works: AI-driven character animation and voice synthesis technologies allow for the creation of lifelike virtual performers.
Tech Stack
- 3D Modeling and Animation
- AI Character Behavior:
- Generative AI
- AI Mocap generation
- StyleGAN
- UNET
AI-Enhanced Visual Effects (VFX)
Use Case: AI is increasingly employed in tasks such as motion tracking, green screen keying, and the generation of realistic CGI (Computer-Generated Imagery), resulting in more immersive and visually stunning entertainment content.
How it Works: Machine learning algorithms and computer vision techniques are used to automate and optimise various aspects of VFX production.
Tech Stack
- Computer Vision:
- Object Tracking
- Image Segmentation
- Machine Learning:
- Physics-based model
Monetisation
Ad slot Forecasting for Maximising Commercial Break Performance
Tata Elxsi Use Case
Use Case: Television broadcasters aim to maximise ad revenue while ensuring a seamless viewer experience.
AI can be employed for forecasting ad sl ot performance to optimise ad placement and content scheduling during commercial breaks.
How it Works: Implemented on AWS, this is Tata Elxsi’s AI / ML model that factors in content type, time, demographics, and external events to predict program and channel ratings to optimise ad placement, and elevate viewer engagement and ad performance.
Tech Stack
- Combinatorial Optimisation
Data
AI-Powered Metadata Extraction and Management for Media Assets
Tata Elxsi Use Case
Use Case: Media organisations and content libraries manage vast amounts of media assets with associated metadata.
AI can be employed to automate the extraction and management of metadata, making content discoverable and enhancing its organisation and accessibility. Metadata analysis enables content recommendation, aiding content curation and discovery.
How it Works: AI algorithms analyse media files, extracting metadata like keywords, timestamps, and sentiment. ML models recognise objects, faces, and scenes, enriching metadata.
Tech Stack
- AutoML
- Data Augmentation for improved accuracy
Real-time Sports Analytics
Use Case: Provides real-time analytics during live sports events, including player performance statistics, game predictions, and highlight reel generation.
AI algorithms process live sports footage, identifying players and tracking their movements. They generate statistics, insights, and highlights in real time, offering viewers with a more immersive and informative sports-watching experience.
Tech Stack
- Data Collection:
- Sensors and Cameras
- Data Integration
- Machine Learning and AI:
- Computer Vision
- Predictive Analytics
- Real-time Processing:
- Streaming Analytics Platforms
AI-Enhanced Audience Research and Personalized Content Recommendations
Tata Elxsi Use Case
Use Case: Media platforms and streaming services aim to understand their audience better.
How it Works: ULike- Content Discovery and Recommendation engine analyses user data to build audience profiles, segment viewers based on interests. Continuous learning from user interactions refines recommendation algorithms, suggesting personalised content.
Tech Stack
- Graph Databases:
- Utilising graph databases to model complex user relationships
- Explainable AI (XAI):
- Incorporating XAI to provide transparent recommendations
Distribution and Delivery
Data Center Anomaly Detection
Tata Elxsi Use Case
Use Case: Analyse operational patterns to differentiate between genuine anomalies and normal fluctuations. Threshold-based alerts are reduced, enhancing data center monitoring.
How it Works: A data center anomaly detection system utilises a GCP-based data lake. Tata Elxsi’s Advanced anomaly detection algorithms minimises false alarms by focusing on read-write operations, improving operational efficiency.
Tech Stack
- Data Lake:
- Google Cloud Storage
- Anomaly Detection:
- TensorFlow
- Scikit-learn
- Data Ingestion:
- Apache Beam
- Data Processing:
- Apache Spark
- Scalability:
- Google Kubernetes Engine (GKE)
Correlation Engine for Ticket Reduction
Tata Elxsi Use Case
Use Case: Tata Elxsi’s AI and ML-driven correlation engine reduces ticket volume and resolution time in communications which helps in a quicker issue resolution.
How it Works:
- Data Collection: Gather CMTS network data from various sources.
- AI Analysis: Utilise AI and ML algorithms to analyse and identify trending issues.
- Correlation: Correlate issues to pinpoint the originating node responsible.
- Dimension Reduction: Apply techniques to reduce data dimensions for efficient analysis.
- Ticket Reduction: Automate ticket generation and reduce the overall ticket volume
Tech Stack
- AI/ML Framework:
- TensorFlow, PyTorch
- Data Processing:
- Apache Spark
- Correlation Engine:
- Elasticsearch
- Data Visualization:
- Kibana
Security
Infrastructure Monitoring using AIOps
Tata Elxsi Use Case
Use Case: Tata Elxsi’s AIOps-based infrastructure monitoring employs network element agents to gather data.
How it Works: Agents are deployed on network elements, continuously collecting data. This data is transmitted and consolidated on a central server. Utilising MLOps, we track data drift and identify anomalies. Detected anomalies trigger automatic alert generation, enabling proactive issue resolution to improve network stability.
Tech Stack
- Data Collection:
- Agent-based data collection
- Data Analysis:
- MLOps with TensorFlow, Scikit-learn
AI-powered Anomaly Detection for Set-Top Box Security
Use Case: Set-top boxes are vulnerable to various security threats, including unauthorised access and tampering. AI-powered anomaly detection can be implemented to identify unusual user behavior and potential security breaches.
How it Works: If there is a spike in network traffic suggesting a potential attack, the AI system can trigger alerts or take preventive actions, such as locking down the set-top box or notifying administrators. This helps protect the set-top box ecosystem from security threats and unauthorised access.
Tech Stack
- Data Collection and Storage:
- Log Data Storage
- Database
- Machine Learning and AI:
- Anomaly Detection Algorithms
- Pattern Recognition
- Real-time Processing:
- Stream Processing Framework
- Real-time Alerts
Compliance
AI-Powered Certification Support
Tata Elxsi Use Case
Use Case: Regulatory bodies, content platforms, and media companies need efficient and reliable methods to certify content safety and compliance with industry standards.
In the MENA region, AI-driven content moderation helps platforms enforce policies while respecting diverse perspectives and sensitivities. It identifies and removes harmful or offensive content related to LGBT issues, fostering a safer online environment and promoting inclusion and tolerance.
How it Works: Tata Elxsi’s AI algorithms analyse audio, video, and textual content to identify potentially unsafe or non-compliant elements, such as hate speech, violence, explicit imagery, or copyright violations. Natural Language Processing (NLP) and computer vision techniques enable AI to detect and classify these elements. A rich dashboard is provided for showing status and key metrics for further action.
Tech Stack
- Blockchain:
- Implementing blockchain for tamper-proof certification records
- Implementing blockchain for tamper-proof certification records
- Natural Language Understanding:
- Enhancing compliance checks using NLU models
Video and Image Analysis for Content Moderation
Tata Elxsi Use Case
Use Case: Social media platforms, streaming services, and news websites use AI to automatically detect and moderate content that violates community guidelines, such as hate speech, violence, and explicit imagery.
How it Works: Tata Elxsi’s AIVA, an Intelligent Video Analytics platform for Content Curation and moderation uses AI algorithms, including computer vision and natural language processing, to analyse images, audio, videos, and text in real time. It flags content that may be inappropriate or harmful, helping maintain a safe and compliant online environment.
Tech Stack
- Computer Vision:
- Convolutional Neural Networks (CNNs)
- OpenCV
- Content Analysis:
- Image Recognition
- NLP for Text Analysis
- Real-time Processing:
- Video Streaming Infrastructure
- Real-time Analysis
