Media and Entertainment

Key ways AI is changing the entertainment industry

The entertainment industry is characterised by an inherent unpredictability, where high-value investments do not always guarantee commensurate returns. In recent years, however, the application of AI technologies such as machine learning and deep learning has proven to be valuable in providing insights and optimising business outcomes. Consequently, there is a growing interest in exploring the impact of AI on the entertainment industry.

AI-generated subtitles and synthetic voice

With the advent of social media and OTT platforms, audiences have easy access to content created across the globe. This accessibility will be translated into viewership for a new, expanded audience base only if the content can be understood with subtitles or by dubbing into the local language. The main impediment to achieving this was the cost of hiring native speakers and translating it for multiple geographies. With AI's ASR (Automated Speech Recognition) and language translation technologies, subtitling is a low-cost, low-effort task. Synthetic voice technology takes the localisation to a specific geography many steps further by transforming content into a different language while retaining the quality and the voice of the artist who did the original. It uses AI technologies like TTS (Text to Speech) or STS (Speech to Speech). The algorithm must be trained using audio recordings of the voice in which content is to be generated. And the AI synthetic voice solution automates dubbing into multiple languages in the voice of the cast of the content. These technologies expand audiences for content that is being created, and also for existing content that can be made available in a new avatar in multiple languages.

VFX (visual effects)

VFX ushered in a revolution in the motion picture industry, bringing alive on the screen the boundlessness of human imagination. VFX involves laborious and time-consuming tasks like rotoscoping, compositing, motion capture, performance capture, simulation, and rendering. AI methods like GAN (Generative Adversarial Network) have brought automation to the VFX world. It reduces effort and costs, as only a camera is needed, not sophisticated and expensive 3D software and hardware like a motion capture suit. AI captures actors' performances, lighting, compositing, and other factors from the video footage and creates the required VFX. The efficiency brought in by automation helps artists by minimising the time spent on repetitive tasks, allowing them to focus on creative tasks. Traditional VFX methods take weeks or even months to complete complicated effects, but with AI-enabled solutions, the same effects can be done in a few days. The technology drastically reduces production costs, creating a level playing field for smaller production houses and independent filmmakers. The conventional VFX learning curve is steep, while AI-based solutions are intuitive and easy to learn.

Personalised user experience

OTT platforms, music apps, and reading apps depend on personalised recommendations to engage customers and keep them returning for more. Data is the key to developing a successful personalisation experience. Machine learning and deep learning algorithms unearth insights that enrich personalisation and open up new opportunities. For instance, an intelligent song recommendation that broadens the users' tastes piques their interest, making it more likely that they will try the next suggestion too. The increased engagement will ensure brand loyalty. The challenge is keeping the data private while honing the personalisation. Organisations must stay abreast of the latest technologies and practices to keep the data confidential. Anonymising the data is essential.

Gaming, AR (Augmented Reality), and VR (Virtual Reality)

AI transforms gaming, AR, and VR by making them more immersive and interactive. AI can create conversationally capable intelligent avatars in VR and gaming. AI determines NPC (Non Player Character) behaviour, pathfinding – the creation of landscape as per player movements, decision-making – game progress based on player decisions, data mining for game design, and identification of monetisation opportunities. In AR and VR, AI technologies like computer vision for positional tracking, object recognition to enable filters or identify critical components, and voice-based interaction hold enormous potential. By incorporating AI technologies, mixed reality entertainment experiences in sports, performing arts, visitor attractions, and social media will undergo a significant transformation.

Predictive Analytics

Entertainment, being a high-investment and high-risk sector, everyone, from production companies to streaming platforms, wants to create content that will be a hit with the audience. Using AI-enabled predictive modelling from the beginning of the creative process helps produce low-risk content that will appeal to the audience. Streaming services use real-time AI insights based on diverse data sources, like the weather, to optimise content scheduling. OTT platforms use AI to detect infringements like password sharing.

AI in entertainment has been nothing short of transformational. And further advancements will only lead to more engaging content that keeps consumers hooked at lower costs.

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