The era of AI has arrived! The typical grind of waking up, working in the office, and heading home is about to change. AI tools are set to revolutionize this routine, bringing new possibilities for career, development, and enjoyment. At the center stage of this new transformative revolution is generative AI.
As the most powerful type of AI, generative AI will soon penetrate every aspect of our lives. By creating content, writing songs, and producing fantastic images and videos is going to alter our daily routine. Thus, making it more unpredictable and evoking passion for work and creativity. And it’s the latter we’d like to touch upon, among other well-known facts about AI.
Let’s investigate the world of generative Artificial Intelligence and see the pros and cons it brings.
What Is It, & How Does It Work?
Generative AI is known for its sophisticated models exploiting neural networks to detect and extract patterns and mechanisms from the given data to produce new, more original and captivating content. In this sense, the generative approach differs from the original AI form. It is quickly becoming a favorite for forcing brand-new learning methods like semi- or unsupervised learning for training.
Since its emergence, generative AI has joined diverse fields and industries and is now helping in the progression of scientific innovation and commercial tech development. It is closely studied by multiple agencies, such as Statista, which performs regular research and delivers exhaustive data about generative AI growth and implementation. In one of their recent studies, Statista determined that the generative AI market will reach $66+ billion this year, and the market breadth is anticipated to demonstrate a yearly upsurge rate of above 20%, which would result in a market capacity of $207+ billion in 6 years.
The Creative Nature: Generative AI in Arts
Use cases are springing up swiftly. What started with the scientific community quickly developed and penetrated the arts, where it has widely been believed that only human beings are capable of creating the exceptional. Let’s see if this belief is still valid.
Image Synthesis
There are special generative AI models featuring numerous high-quality applications in the synthesis of images. With this, even the most creative domains are easily expanded and revolutionized. The top pivotal applications are:
- art and design
- fashion
- gaming
- animation
- medical imaging
- photography
AI’s Generative adversarial networks (GANs) allow artists to investigate uncharted creative territories. With this model, an artist can produce new colors, textures, and even patterns to create outstanding sculptures, paintings, or furniture.
The same GAN model helps the gaming space by assisting in developing environments and characters that are true to life, thus enhancing user experience. The world’s top fashion designers apply such generative AI models to sketch unparalleled accessories and clothing.
Visual effects in movies and cartoons are streamlined by generative Artificial Intelligence, helping to automate and streamline the flow of visual content creation. As for medical imaging, realistic MRIs, CT scans, and X-rays help medical professionals address complex conditions more quickly and with better results.
Music Synthesis
This application still causes a storm of thoughts and doubts, and it’s clear why: one can hardly imagine that AI can produce anything better than works by Bach, Mozart, Beethoven, Vivaldi, or Debussy. Yet, generative AI is good at delivering original rhythms, melodies, harmonies, and songs without any human-related assistance.
The areas of application are immense, but here are some top applications in demand:
- composition of original music pieces
- generation of music on digital networks
- custom playlists
- creating reinterpretations and/or remixes
- tools and patterns for musicians
Generative AI composes original harmonies and melodies and is already applied in TV shows, video games, and commercials. Platforms like TikTok and Instagram are the core consumers of products by generative AI since they need the background music for their best videos. Recently, the technology has been used to create personalized playlists based on listeners’ shares, likes, and skips. Moreover, AI helps to recommend artists and tracks to users based on their custom playlists.
With generative AI, classic or old songs are easy to reinterpret or remix by adding more contemporary styles and applying collaborative tools used in the music industry: progressions, patterns, melodies, etc.
Human-machine collaboration is at its fullest, and it’s for creating music, not armor.
Video Synthesis
This generative AI application is reaching impressive heights: It allows users to forget about huge teams, countless work hours, and heavy & expensive equipment as the three cornerstones of video production. Generative AI technologies can automate video production stages, including script writing, scene diagramming, scene structuring, filming, editing, and end-phase tasks.
Here are the four primary application cases:
- from-scratch video generating
- video inpainting
- style transfer
- data augmentation
It’s enough for a generative AI to create video sequences from the bottom up. The technology easily fills in missing parts in videos with matching content.
Generative AI assists video makers in finding and applying a suitable artistic style without any adverse effect on the video itself. It also helps to make use of specific ML models and design video sequence variations.
Wrapping Up
For many of us, generative AI in particular and AI in general are two mysteries we are trying to avoid. This conservatism and stubbornness are blockers on the way to development, improved creativity, success, and things much greater than the daily routine.
Whether you’re an artist (or want to be one) or need to rethink your current work, generative AI is a powerful tool that can grow into a magic wand once in your hands. Use it wisely.
Image by vecstock on Freepik