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  • Writer's pictureChesapeake Group

From Fiction to Fact: How Synthetic Media Is Changing Industries



Overview:



Synthetic media refers to digital content that is generated or manipulated using artificial intelligence (AI) and machine learning algorithms. It encompasses a wide range of media types, including images, videos, audio, and text, created or altered in ways that mimic or augment reality.


This technology enables unprecedented levels of realism and creativity, allowing users to generate lifelike human faces, alter voices, edit videos seamlessly, and even create entirely synthetic personas. The implications of synthetic media are vast and multifaceted. It offers tremendous potential for innovation in entertainment, advertising, and digital content creation.


However, concerns exist about its potential for misuse, like spreading misinformation or creating fake news. As synthetic media becomes more common, critical thinking skills will be essential to navigate the increasingly blurred line between reality and artifice.


A New Frontier in Digital Expression


Synthetic media is created by AI algorithms. Machine learning models recognize and analyze patterns of input data and learn to perform tasks based on these data, without human intervention. From social media to gig economy, after consumer adoption is normalized, often enterprise adoption follows. Same applies to Synthetic media. While consumer applications of synthetic media are more mature in depth and breadth, organizations are catching on to the power of this technology.


Gen AI is the technology behind the production of synthetic media, which is why the two terms are often used interchangeably. Today, many AI applications are enabled by deep learning and generative adversarial networks (GANs) that teach computers to think like humans and make intelligent decisions. GANs let computers generate realistic content. It’s fueled by two neural networks: one that creates false images based on actual photographs and another that serves as a judge to determine whether an image is genuine. GAN outputs often appear natural and indistinguishable from the original images. Therefore, they enable the creation of synthetic media that are difficult to distinguish from real media, particularly in computer vision and image processing applications.


In entertainment and advertising, it allows for cost-effective creation of compelling visual and audio content, reducing dependency on traditional production methods. Filmmakers can now seamlessly integrate CGI characters into live-action scenes, while marketers can personalize advertisements to target specific demographics with tailored messages. In journalism, synthetic media presents both opportunities and challenges. On one hand, it facilitates the creation of interactive and immersive news experiences. On the other hand, the potential for misinformation and fake news poses significant ethical concerns.


Industry examples:


Synthetic media has many players across different spaces such as video creation, text-to-speech, general purpose AI tools and combating deepfakes.


In the video creation space, Synthesia, Tavus, Hour One, D-ID, and Colossyan are at the forefront of AI-powered video solutions. These companies allow creation of videos with digital avatars or AI actors, perfect for scalable marketing materials or training videos. Resemble.ai offers generating realistic speech with their deep learning models. They can even create custom voices, like the recreation of Andy Warhol's voice for Netflix.


Latent Space Labs and RunwayML offer AI-powered creative tools that streamline animation production and video editing, incorporating synthetic media elements. Deeptrace, a cybersecurity company, utilizes deep learning to detect synthetic media being used for malicious purposes. This is crucial in the fight against misinformation.

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