Artificial intelligence and machine learning (AI/ML) is one of today’s most widely discussed and anticipated technologies. The promise of automation and intelligent enhancement of functions and operations for both technology and enterprise applications has sparked considerable interest and intrigue for AI/ML.

Still, AI/ML is a powerful tool, but not a panacea. AI/ML cannot be used to solve every problem, but when strategically and effectively applied, it holds the potential to benefit a plethora of operations. As we continue the path of network evolution from 5G today to the 6G networks of the future, we expect the role of AI/ML to grow, especially as research, development, and standardization efforts towards the next generation of wireless products identify new ways to leverage AI/ML to improve device operations, network management for Communication Service Providers (CSPs), end user experience, and more.

This eBook will introduce a short history of AI, outline a few of the current applications of AI/ML within the wireless ecosystem, and dive into the ongoing research exploring new ways to integrate AI/ML as part of wireless evolution beyond 5G Advanced, particularly within the core and radio access network (RAN).

Introduction to AI in Wireless

AI will become an essential part of our lives in the next few years, with the promise of delivering super-intelligent computers that exceed human analytical abilities. This is, however, several years away; indeed, the industry has only just embarked upon understanding what’s possible.

Arguably the hype surrounding AI thus far has meant that the technology is being squeezed into everything: “AI is the answer… now, what was the question?” The situation is changing, as companies begin to understand the beneficial effects of AI and how it maps to specific applications.

Executed with efficacy and respect, AI promises to enable far more efficient solutions to complex problems; certainly, AI techniques will become an intrinsic element in most large systems. Meanwhile, there are ethical questions surrounding AI: there is nervousness over what happens if it works and, conversely, deep-rooted concerns over what transpires if it doesn't work. Machine learning offers plenty of scope for both outcomes, given the challenges of AI bias on one hand and the mysterious nature of machine learned models on the other.

In this white paper, commissioned by InterDigital, Futuresource examines the status of machine learning and artificial intelligence with emphasis on applications across the video supply chain. We investigate the issues surrounding the broad uses of AI across segments of the media industry and highlight several examples of how the discipline is employed today and how it promises to develop in future.

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Introduction to AI in Wireless

AI and Machine Learning in the Video Industry: New opportunities for the entertainment sector