Opportunities & Challenges

Real time, efficient tagging and indexing of huge volumes of stored / archived unstructured video data is a major challenge; as this is currently done manually. Unlike conventional automation processes(which are mostly rule-based) AI algorithms can analyze a massive amount of data, mine patterns, correlate data from various sources and can generate intelligent insights.

However, effective indexing and metadata tagging require advanced search techniques, that aim to discover media content snippets. Traditionally quality checks, subtitle and closed caption creation are done manually. AI has the potential to automate these using techniques like Anomaly detection and Natural Language Understanding (NLU). Further, AI can enhance customer experience by analyzing viewing patterns, social media footprint, demographic details of local communities that result in increased click-throughs and also for dynamic insertion of highly relevant advertisements.

Deep Learning algorithms should be fine-tuned using appropriate cost functions and hyper-parameter tuning. Combination of algorithms like CNN, RNN/LSTM, NLP/NLU should be optimized as per the application use cases to obtain optimum accuracy and efficiency.