Often considered a ‘solution for everything’, AI will expand its impact as the video entertainment industry realises its benefits to a variety of applications, according to a report commissioned by mobile and video technology developer InterDigital and written by market research firm Futuresource Consulting, which examines the industry influence of artificial intelligence (AI) and machine learning (ML) on applications across the video supply chain.
The report, AI and Machine Learning in the Video Industry: New Opportunities for the Entertainment Sector, investigates the emerging uses of AI across segments of the media industry and highlights key examples of how AI is employed today and might develop in the future
Valued at roughly $84 billion, the global video entertainment industry is fuelled by a five-stage supply chain comprised of media creation, preparation, distribution, playout and delivery, and consumption. AI can be incorporated within several applications across the ecosystem, from encoding to transmission to decoding to post-processing. With a wide variety of applications, including auto tagging metadata, creating transcripts, conducting quality control, flagging inappropriate content, or even service personalization, AI’s strength is extracting patterns from ‘big data’ where traditional algorithms might fail.
The report identifies cost reduction and efficiency as the primary drivers to use AI in broadcast and media. In a data-heavy industry such as multimedia broadcast, the more granular insights that can be extracted from data, the more benefit it will deliver in efficiencies to adopters of the technology.
“We have long known that AI and machine learning will deliver significant improvements to operations throughout the video ecosystem, and this research delivers a nuanced perspective on what these critical technologies have accomplished and have yet to improve,” suggests Henry Tirri, CTO, InterDigital. “To develop cutting-edge solutions for the video industry’s most critical needs, it is imperative to understand the benefits, and limitations, of AI and ML in their current stage.”
AI and ML offer the potential to augment existing video encoding methods to reduce file sizes and bit rates whilst maintaining visual quality. The report also suggests ML techniques are beginning to influence new solutions for the video industry, though its benefits are not always universal or immediately tangible. Research shows machine learning will play a role in defining advanced video coding mechanisms, even though the significant complexity in encode and decode operations make traditional tools more efficient than AI-based alternatives. For instance, the state-of-the-art Versatile Video Coding (VVC) standard offers a roughly 40 % compression improvement over HEVC but carries a tenfold increase in encoding complexity.
“As AI-based methods evolve, the technology will become even more entrenched in video encoding and decoding solutions,” predicts Simon Forrest, Principal Technology Analyst, Futuresource. “AI and machine learning are likely to become vital elements that enable a commercially viable 8K streaming or broadcast TV service, and even support the proliferation of video conferencing beyond the application of traditional coding schemes.”