The animation industry has gone a long way since the days of manually drawing each frame, second by second, to make an animated video. Thanks to the modernization in the animation industry, animators may now quickly create various characters, styles, and designs.
The animation industry is crawling with fresh approaches for speeding up or improving the animation production process. New ideas emerge throughout the world with the promise of encouraging artists to enhance their animation styles or develop astounding techniques. Among these innovations is artificial intelligence, from which comes the component of machine learning animation.
In this blog, you’ll learn the basics of AI animation, the benefits of machine-learning animation, and how artists and top animation companies are leveraging it to their advantage.
What Is AI and How Is It Used in Animation?
Before we go into machine learning animation, let’s take a closer look at artificial intelligence (AI). The study of utilizing machines and computers to solve problems and make judgments analogous to the human brain is known as artificial intelligence. They work by ingesting enormous amounts of data and analyzing it for patterns and correlations. The data is then used to create forecasts and develop solutions.
A good example of AI is your smartphone’s predictive messages – the way your phone foresees what you will type based on your previous messages. Besides, AI is extensively used in animation in fields such as automation, virtual scene creation, 3D model development, face animation, and virtual reality.
AI-generated animation is extremely popular today, and for this reason, major technology companies such as Google and Adobe have created animation software and tools. Adobe Sensei and Google DeepMind are two prominent examples.
What Is Machine Learning Animation?
The term machine learning was coined by the pioneer of artificial intelligence, Arthur Samuel. Machine learning helps develop solutions for problems at a rate and scale that humans just can’t. Talking about machine learning animation, it’s a component of artificial intelligence applications. It enables learning and adapting from experience rather than being programmed and functions similarly to how a human brain function.
Besides, machine learning animation benefits the animation process by predicting the next animation frame based on the recent one. Let’s look at the benefits of machine learning in animation in detail below.
The Benefits of Machine Learning Animation
Machine learning animation has revolutionized the animation landscape. Animated series and movies are being completed quickly. Video games have become much more realistic, characters and movements have become smoother, and so on.
Below are the top three benefits of employing machine-learning animation as an animator:
1. Faster and Smoother Animation
The purpose of innovation and technology is to make tasks easier and faster for humans to complete. Animation typically contains 24 to 30 frames per second. Initially, animators had to sketch each frame painstakingly by hand. As a result, a short five-minute animation would include 1,000 frames or 1,000 drawings.
But with technology and machine learning animation, animators may produce 30-minute animations and even sophisticated animation styles more quickly. For example, consider rotoscope animation – a tedious process for animators. Machine learning has cut production time by automating the whole process.
2. Encourages Creativity
Now that your work as an animator has been reduced, you can begin focusing on your animation skills. You can explore the creative aspects of animation, bridge your skills gaps, and try out new animation styles and techniques. As an animator, exploring and producing animation for various niches, such as medicine, sports, and entrainment, will diversify your portfolio and boost your animation career.
The best part, animators don’t have to spend long hours on exhausting tasks leading to burnout. Machine learning allows room for innovativeness and gives you the freedom to come up with creative animation ideas!
3. Accurate Facial Expressions
For an animator, perfecting the art of facial expressions and reactions in animations is crucial. That’s why animators spend hours doing it correctly. Using the right expressions makes the story more realistic and impactful to the viewers. When the animated characters lack real or natural expressions, it can harm the story’s influence and ruin the viewer’s experience.
However, thanks to machine learning animation, animators can quickly produce 3D animation models and facial expressions that are more accurate and realistic.
Example of AI in Animation
The first name that comes to mind when we talk about animation is Walt Disney. He was a visionary who considered the future even in his time. His ability and innovation transformed two 2D characters, a mouse and a duck, into an enterprise worth billions of dollars.
Back in the day, the animation used to be a labor-intensive and pretty tedious exercise. Animators and cartoonists had to draw each frame to complete the movie. Disney is known for using AI to generate storyboard animations just from the text by using words, such as “turn right,” and having the animated character turn in that direction.
There are numerous other films and animations that employ AI. However, keep in mind that this cycle is not as straightforward as it is portrayed and needs a lot of effort before it has the potential to function well. Even the Disney corporation admits that translating text to animation using artificial intelligence is tricky.
Summing Up – The Future of Animation with AI
In the future, AI will make animators’ work much more convenient and quicker. Besides, seeing the rise in the use of artificial intelligence in animation video production, the days may not be far behind when people will go to the cinema to watch a movie conceptualized by AI.
Moreover, advanced AI calculations are suitable for automating the delivery of enhanced visualizations. Artificial intelligence (AI) would enable creative artists to concentrate on more alluring matters instead of work that is elevated through outline-by-outline redaction procedures.