Synthetic media is a name for digital content (images, videos, audio, or text) that is artificially created or manipulated using AI and machine learning technologies, rather than recorded from real-world events.
This includes deepfakes, AI-generated art, synthetic voices, and computer-generated imagery.
A simple form would be using a photo filter that ages your face or swaps your gender on social media apps. More complex examples include AI tools like DALL-E that can create entirely new images from text descriptions, or deepfake technology like AKOOL that can make it appear as if a public figure is saying something they never actually said.
Truth battles artifice as synthetic media reshapes our world. Creators build AI tools to generate fake images, videos, and voices. Critics fear deception, while artists see liberation.
The market demands innovation, yet society craves authenticity. Teams clash over ethical limits, while individual creators feel pressure to keep pace. Who controls these tools? When does creativity become manipulation?
In this article, we will cover it all.
How Does Synthetic Media Work
Synthetic media works by using advanced AI algorithms, such as deep learning and neural networks, to analyze vast amounts of data and generate new content based on patterns and characteristics of the original input.
The process typically involves the following steps:
- Data collection: Large datasets of images, videos, audio, or text are gathered to train the AI models.
- Data processing: The collected data is cleaned, formatted, and labeled to ensure optimal performance during the training process.
- Model training: The AI algorithms are exposed to the preprocessed data, to learn and recognize patterns, styles, and features specific to the content type.
- Content generation: Once trained, the AI models can generate new content by combining and manipulating the learned patterns and characteristics. This can involve creating entirely new content or modifying existing content.
- Refinement and optimization: The generated content is fine-tuned and optimized based on user feedback, additional data inputs, and specific goals or constraints.
Non-synthetic media is content captured directly from reality, like a photo taken on your phone or a video recorded at an event. Synthetic media is artificially created or manipulated using AI and machine learning, but based on patterns data from non-synthetic media.
Examples of synthetic media include:
Here are some real world success stories:
How Synthetic Media Connects to Deepfakes
One of the most well-known, modern applications of synthetic media is deepfake technology. Deepfakes use advanced AI techniques to create convincing videos of people saying or doing things they never actually said or did.
The process involves training an AI model on a large dataset of images or videos of a specific person, allowing it to learn and replicate their facial features, expressions, and movements with a high degree of accuracy.
Today, they are called AI avatars more often.
To create a deepfake, the target person's face is extracted from the training data using computer vision techniques. The extracted faces are then aligned and encoded into a compact representation that captures the essential characteristics of the person's appearance.
The encoded facial features are superimposed onto a destination video, replacing the original person's face with the target person's face. Complex blending techniques ensure the end result is top-notch.
Deepfakes have gained significant attention in recent years due to misuse, such as spreading disinformation, engaging in fraud, or harassing individuals. In 2024 the biggest deepfake misuse was with Taylor Swift's images.
As the technology behind deepfakes continues to improve, it becomes increasingly difficult for viewers to distinguish between authentic and fabricated content.
At the same time, deepfakes can also be used for positive purposes, such as creating entertaining content, improving educational experiences, or even assisting in medical research.
Types of Synthetic Media
Synthetic media covers a wide range of AI-generated content, including text, audio, video, and images. Let’s see the list so far:
- Text-based synthetic media
Text-based synthetic media involves the use of AI algorithms, such as GPT (Generative Pre-trained Transformer), to generate human-like text. These algorithms are trained on vast amounts of textual data, to understand and replicate patterns, styles, and semantics. The use cases for text-based synthetic media are:
- AI-powered chatbots and virtual assistants
- Automated content creation for news articles, product descriptions, and social media posts
- Language translation and summarization
Top positive applications of text-based synthetic media are:
- Assisting people with disabilities in writing by helping them express their thoughts more fluently through AI-powered text completion and refinement
- Rapid translation and localization of content across languages while maintaining natural-sounding text
- Helping students and researchers brainstorm ideas and generate initial drafts to overcome writer's block
Audio-based synthetic mediaAudio-based synthetic media is a term for generating or manipulating speech and other sounds using AI. By training on large datasets of human speech and audio recordings, AI models can create realistic and convincing audio content. Some examples of audio-based synthetic media include:
- Text-to-speech systems that generate human-like speech from written text
- Voice cloning and voice deepfakes to replicate a person's voice
- AI-generated music and sound effects
Top positive applications of audio-based synthetic media are:
- Enables efficient production of audiobooks and educational content in multiple languages without re-recording
- Helps companies create consistent customer service voices across different languages and platforms
Video-based synthetic mediaVideo-based synthetic media involves the creation and manipulation of video content using AI algorithms. This type of synthetic media has gained significant attention due to the rise of deepfakes, which are highly realistic videos that depict people saying or doing things they never actually said or did. Other applications of video-based synthetic media include:
- Virtual avatars and digital humans for entertainment, education, and customer service
- Video synthesis and animation, that enable the creation of realistic video content without the need for physical actors or sets
- Video enhancement and restoration, improving the quality of existing video footage
Top positive applications of video-based synthetic media are:
- Educational content showing historical events or scientific concepts that would be impossible to film
- Generating background scenes and special effects digitally for movies to cut down costs
- Accessible training videos in multiple languages by synchronizing lip movements with translated audio
Image-based synthetic media
Image-based synthetic media focuses on generating, manipulating, and enhancing images using AI algorithms. By training on large datasets of images, AI models can create highly realistic and detailed images that mimic real-world content. Some examples of image-based synthetic media include:
- AI-generated art and designs, such as those created by DALL-E, Midjourney, or Stable Diffusion
- Synthetic images of people, objects, and scenes that are indistinguishable from real photographs
- Image manipulation and editing, such as removing objects, changing backgrounds, or adjusting facial features
Top positive applications of image-based synthetic media are:
- Helps architects and designers visualize projects before construction by generating photorealistic renderings
- Enables artists to quickly prototype different creative concepts before committing to final artwork
- Assists law enforcement in aging missing person photos or generating suspect composites based on descriptions
Synthetic vs. Non-Synthetic Media: Here are the Differences
The distinction between authentic and AI-generated content is becoming increasingly important., so let’s lay out the differences.
Content Creation
Synthetic Media:
- Sophisticated AI systems
- Producing images and videos without source material
- Reliance on NLP models to recreate real-world material
Traditional Media:
- Raw footage from cameras and smartphones
- Unedited photographs
- Natural audio recordings
- Live streaming content
These formats maintain their original integrity throughout the creation process, making them valuable for documentation and authenticity.
Practical Applications
Synthetic Media:
- Creative projects
- Entertainment
- Marketing campaigns
- Virtual experiences
Medios tradicionales:
- Periodismo y documentación
- Evidencia legal
- Comunicaciones empresariales
- Material educativo
Ventajas de los medios sintéticos
Exploremos algunas de las principales ventajas de los medios sintéticos:
Creación de contenido más rápida
Los medios sintéticos permiten la creación rápida y rentable de contenido de alta calidad. Con los algoritmos de inteligencia artificial para generar texto, audio, vídeo e imágenes, las empresas y las personas pueden ahorrar tiempo y recursos en comparación con los métodos tradicionales de producción de contenido.
Esto es particularmente útil para industrias como la publicidad, el marketing y el entretenimiento, donde la demanda de contenido fresco y atractivo es constante.
Accesibilidad y localización
Los medios sintéticos pueden ayudar a que el contenido sea más accesible para un público más amplio. Los sistemas de conversión de texto a voz y los subtítulos generados por inteligencia artificial pueden ayudar a las personas con discapacidades visuales o auditivas, mientras que la traducción de idiomas basada en la inteligencia artificial puede ayudar a las empresas a llegar a un público global de manera más eficaz.
Además, los medios sintéticos se pueden utilizar para crear contenido localizado, adaptándose a diferentes idiomas, culturas y preferencias.
Entrenamiento de escenarios sin riesgos
Los estudiantes de medicina pueden practicar el diagnóstico de enfermedades raras utilizando imágenes generadas por IA de síntomas que serían difíciles de documentar en pacientes reales.
Por ejemplo, un hospital universitario podría generar miles de variaciones en las presentaciones del melanoma en diferentes tipos y etapas de la piel, de modo que los estudiantes puedan desarrollar habilidades de reconocimiento de patrones sin tener que esperar años para detectar estos casos de forma natural.
Del mismo modo, los equipos de respuesta a emergencias pueden entrenarse utilizando vídeos sintéticos de escenarios de desastres que serían peligrosos o imposibles de filmar, como simulaciones realistas de accidentes nucleares o varios tipos de derrumbes estructurales.
Desventajas de los medios sintéticos
Si bien los medios sintéticos ofrecen numerosas ventajas, es igualmente importante reconocer y abordar las posibles desventajas y riesgos asociados con esta tecnología.
A medida que los medios sintéticos se generalizan, debemos considerar las implicaciones éticas, sociales y legales de su uso.
Difusión de desinformación y noticias falsas
Uno de los riesgos más importantes asociados con los medios sintéticos es su potencial para difundir desinformación y noticias falsas.
A medida que el contenido generado por IA se vuelve más realista y difícil de distinguir del contenido auténtico, se puede utilizar para crear y difundir información engañosa o falsa.
Esto puede tener consecuencias graves, como influir en la opinión pública, socavar la confianza en los medios de comunicación y las instituciones o incluso incitar a la violencia.
Preocupaciones de privacidad y seguridad
Los medios sintéticos plantean importantes problemas de privacidad y seguridad, especialmente en lo que respecta al uso de datos personales.
Los algoritmos de IA requieren grandes cantidades de datos para crear contenido sintético realista, y estos datos pueden incluir información personal, como imágenes, grabaciones de voz o datos biométricos.
Si estos datos no están debidamente protegidos o si las personas no dan su consentimiento explícito para su uso, pueden producirse violaciones de la privacidad y un posible uso indebido.
El futuro de los medios sintéticos
Los datos del mercado muestran que los medios sintéticos explotarán hasta 2030. La generación de inteligencia artificial en tiempo real igualará la calidad creada por el hombre, ya que los nuevos sistemas combinarán texto, voz y vídeo simultáneamente.
Para 2027, predecimos que el 90% del contenido en línea contendrá elementos sintéticos, y los gigantes tecnológicos ya están creando herramientas de detección y marcos de seguridad. Los sistemas de autenticación y las marcas de agua pasarán a ser estándar.
Surgirán plataformas de «realidad sintética» en las que los usuarios interactúen sin problemas con entornos y personajes generados por la IA.
Está claro que los medios sintéticos tienen implicaciones positivas si se usan correctamente, y crear contenido de calidad nunca ha sido tan sencillo.
Soluciones como Foto parlante de AKOOL permiten a los usuarios dar vida a las imágenes fijas animando las expresiones faciales y los movimientos de los labios. ¿Con Intercambio de caras los usuarios pueden intercambiar rostros en vídeos o imágenes sin problemas.
Si los casos de uso y el ejemplo anteriores te han parecido interesantes, prueba nuestros Face Swap, Talking Photo, Avatar parlante, o Avatar en streaming herramientas para explorar las imágenes sintéticas y el deepfake por ti mismo.
