It is frequently said that AI is unable to express creativity or emotions, and that these limitations prevent it from accurately replicating a human. However, has expanding technology allowed us to overcome yet another obstacle? Is it accurate to say that AI is creative?
Companies that have used AI to produce music include Sony’s Flow Machine and IBM’s Watson. IBM’s Watson and a well-known music producer by the name of Alex da Kid teamed together to attempt to write a song together. A machine wrote and created the entirety of a song. With the aid of AI, live musicians have performed for thousands of viewers in virtual concerts. The most recent instance of this is ABBA’s totally virtual “Voyage” tour. The band collaborated with Industrial Light and Magic, a visual effects studio, to have virtual representations of the band made using cutting-edge motion capture technology. The actions of their virtual counterparts’ eyes and bodies are identical to those of the band members.
The film business is another instance of creative AI in action. The first ever cognitive movie trailer for the horror flick Morgan was made using AI. After being given sequences from the film, the computer chose ten distinct moments to combine into the trailer. This is the first occasion when a machine has completed a task of this nature without assistance from a human.
By bringing forth new technologies that have altered how material is generated, delivered, experienced, and monetized, the digital era upended the conventional formula for success in media and entertainment. Today’s media organisations must embrace constant transformation or risk falling behind – or becoming obsolete – as audiences have more choice, flexibility, and control over what they watch.
AI is being used to make data-driven predictions about how viewers will react to unexpected tales. Generative AI is rapidly transforming the media and entertainment industry, revolutionizing content creation in film, TV, and music. In a recent Wall Street Journal article, it was highlighted that readily accessible AI tools may provide plot lines, character arcs, and dialogue. The article even offers an interactive module so that readers can witness for themselves how quickly ChatGPT can generate a simple screenplay when given a few instructions. We already know how the 2022 movie Everything Everywhere All at Once turned out since it made use of generative AI. Tom recently wrote on the use of generative AI to produce backdrop visuals for film and television. Though they are brief and quite rudimentary, generative AI systems are now capable of producing films. . In cinema, actors’ digital twins are being paired with real actors, allowing AI to simulate their unique traits, gestures, and voice, even enabling de-aging effects. This raises questions about the role of actors and the potential emergence of entirely synthetic celebrities. Similarly, in the music industry, voice cloning is on the rise, generating new songs and collaborations featuring famous artists, though copyright issues and consent are becoming pressing concerns. Generative AI is reshaping artistic workflows, business strategies, and musical exploration by leveraging vast digital archives as training sets. As the creative landscape evolves with these technological advancements, the implications for artistic ownership, creativity, and copyright are at the forefront of discussions in the entertainment world.
Generative AI is revolutionizing video game development, driving faster ideation and enhancing the realism of virtual worlds and characters. Visual models are being utilized to create new game elements, from characters and environments to unique visual styles, while also transforming 2D renderings into immersive 3D models. Game designers can now input a small section of the game world, and AI-powered game engines can generate entire expansive game worlds. Virtual production tools fueled by these engines enable seamless crossovers between film and gaming, giving rise to cinematic universes and even digital twins of celebrities. Furthermore, generative AI is enriching gameplay experiences by empowering non-player characters (NPCs) to engage in natural language interactions with players, allowing for dynamic and creative in-game dialogues consistent with the game narrative. These advancements are rapidly evolving, promising on-demand experiences and reshaping the very tools and workflows that drive the gaming industry.
Generative AI is also making significant strides in the world of literature, fundamentally transforming creative work in this domain. Language models, like GPT-3, are pushing the boundaries of automated content generation, producing articles, stories, and even poetry that can rival human-created pieces. These AI systems have the ability to analyze vast amounts of textual data and learn the nuances of different writing styles and genres, enabling them to generate compelling and coherent written content. Authors and writers are increasingly leveraging generative AI to brainstorm ideas, receive suggestions, and even co-write with these intelligent systems. As a result, generative AI is not only streamlining content creation processes but also challenging traditional notions of authorship and creativity, raising intriguing questions about the future role of AI in shaping the literary landscape.
Over the course of several decades, numerous studies have explored the potential of integrating AI into the creative sector. Earlier limitations were attributed to the technology’s readiness and concerns that AI might merely mimic human creativity. However, a recent survey conducted by Adobe revealed a significant shift in perception, with three-quarters of artists in the US, UK, Germany, and Japan expressing willingness to utilize AI tools as assistants in tasks such as image search, editing, and other non-creative functions. This growing acceptance demonstrates a general awareness of the state-of-the-art AI capabilities, designed to complement human creativity rather than replace it. The key lies in fostering better collaboration between humans and AI technologies, harnessing their synergistic potential. As Bill Gates said for tools like ChatGPT that leverage artificial intelligence (AI) technology, which has the potential to be just as ground-breaking as the graphical user interface was in 1980. “The development of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone.”
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With close to 15 years of professional experience, Anirban specialises in Data Sciences, Business Analytics, and Data Engineering, spanning various verticals of online and offline Retail and building analytics teams from the ground up. Following his Masters from JNU in Economics, Anirban started his career at Target and spent more than eight years developing in-house products like Customer Personalisation, Recommendation Systems, and Search Engine Classifiers. Post Target, Anirban became one of the founding members at Data Labs (Landmark Group) and spent more than 4.5 years building the onshore and offshore team of 100 members working on Assortment, Inventory, Pricing, Marketing, eCommerce and Customer analytics solutions.