Have you ever wondered what kind of life other worlds have? The continuous development of artificial intelligence makes the prediction of the probability of life on different planets much easier and simpler than expected. But how does it happen? Keep reading to find out.

Artificial neural networks are classified as systems that replicate how human brain learns. They are tools utilized in machine learning. They are also excellent at determining several patterns that biological brain cannot process.

A team from the Centre for Robotics and Neural Systems based at Plymouth University has already made their network well-equipped to classify planets into types. It is based on whether they are like the present Earth, the early one, Venus, moon Titan of Saturn, and Mars. These rocky bodies are known to be one of the most habitable objects in the solar system.

Based on Mr. Christopher Bishop’s study, presented at the European Week of Astronomy and Space Science, the artificial neural networks help prioritize exploration. There would also be a hypothetical, interstellar, or impressive spacecraft scanning, which would be a great use for the coming years.

Mr. Bishop, together with his team, is presently looking for a large area and deployable antennas to retrieve data back to earth. This could aid predict the lives on other planets though it is at a large distance. These tools are much significant when the technology is utilized in the future robotic spacecraft.

Spectra, simply known as atmospheric observation of the bodies in the solar system are presented as an input to a network. Then, they are categorized depending on the planetary type. At present, life only exists on Earth. However, there is a great probability of life on other worlds. This is based on the atmospheric as well as orbital properties of the target types mentioned earlier.

The team of Mr. Bishop has a hundred parameters that certainly contribute to habitability. The network presented a test spectral profile that has not seen over the past few years. The method may prove to be useful for classifying the types of the exoplanets. Plus, it may be suited to select specific targets for observations as long as there is an increased spectral detail from James Webb Space Telescope (NASA) and Ariel Space Mission from ESA. Indeed, as artificial intelligence improves, there is a big chance to prove that life exists on other planets.