A desolate and barren alien world, set against a backdrop of a purple sky, with stars, planets, moons, asteroids, and more (artist's rendition). Image source: Forbes biweekly website.
An extensive observation network spanning Earth and space (artistic rendering). Image source: Forbes biweekly website.
In the vast cosmos, are humans the only known intelligent life? This question has lingered in the minds of countless scientists for years, propelling them to continually delve deeper into the unknown.
According to recent reports from the biweekly website of Forbes, advancements in artificial intelligence (AI), including machine learning, are providing scientists with greater assistance in the search for extraterrestrial life, fundamentally altering the landscape of extraterrestrial exploration. For instance, machine learning technologies hold the promise of transforming the way scientists handle and analyze astronomical observation data, and advanced AI tools are more likely to identify signals indicating the presence of extraterrestrial life, significantly accelerating scientists' efficiency in discovering life in other corners of the universe.
Machine Learning Identifies Potential Signals
The "Search for Extraterrestrial Intelligence (SETI)" project primarily aims to detect signals of extraterrestrial life in the universe. Given the vastness of the cosmos, this is a daunting task. AI can process and analyze massive datasets far beyond human capabilities, with machine learning algorithms capable of filtering out noise from cosmic radiation, thereby enabling the identification of signals that may indicate the existence of extraterrestrial life with unprecedented speed and accuracy.
One area where AI shines in SETI is the "Breakthrough Listen" project. This project utilizes telescopes distributed worldwide to search for signs of intelligent life among a million stars.
Scientists from the University of Toronto in Canada and the University of California published a paper in the journal Nature Astronomy at the end of February, detailing their development of a machine learning software that analyzed observation data from 820 stars in the "Breakthrough Listen" project, identifying nearly 3 million valuable signals. Although most signals were discarded as interference, among the over 20,000 signals manually reviewed, they found eight promising candidate signals that could indicate extraterrestrial intelligence, highlighting the potential of AI in accelerating the data-driven new era of astronomy.
Neural Networks Discover Hidden Exoplanets
Identifying planets outside the solar system is crucial for the search for extraterrestrial life. AI algorithms are increasingly indispensable in this task, particularly in analyzing data collected by NASA's Kepler Space Telescope and the Transiting Exoplanet Survey Satellite (TESS).
The Kepler Space Telescope has discovered thousands of exoplanets using the transit method. In 2022, a Google AI research team developed a neural network called ExoMiner, which, by sifting through Kepler telescope data, discovered 301 previously unknown exoplanets, demonstrating the potential of AI in discovering habitable planets.
Neural networks are algorithms that, with enough input data, can learn and improve their abilities. With this successful experience, scientists plan to use this algorithm to help sift through data collected by other exoplanet "hunters," such as the European Space Agency's "Convection, Rotation, and Planetary Transits" mission and data captured by the next-generation planet-hunting mission "PLATO," set to launch in 2026.
Meme Algorithm Identifies Habitable Planets
Determining whether exoplanets are suitable for sustaining life is a complex challenge that requires analyzing numerous factors, from atmospheric composition to surface temperature.
AI models are being trained to predict the habitability of discovered exoplanets. By learning from Earth's known conditions and limited data obtained from exoplanets, AI can assess the likelihood of other planets in the Milky Way hosting life-sustaining environments.
Furthermore, scientists are also using AI tools to discover new habitable planets. According to reports from the Russian satellite communication agency, Indian astronomers have developed a new AI algorithm called "MSMBTAI," which identified around 60 potentially habitable planets from a known pool of 5,000 planets.
MSMBTAI is based on a multi-stage meme algorithm and serves as a rapid screening tool to evaluate the habitability of planets based on observed features.
Additionally, if signals from extraterrestrial civilizations are indeed received, decoding their content will pose unprecedented challenges. AI tools such as natural language processing and machine learning may aid in deciphering such information.
Scientists suggest that if humanity receives signals similar to the Arecibo message from extraterrestrial civilizations, AI could analyze the binary-encoded information, decipher potential meanings, and respond accordingly. The Arecibo message was a radio message beamed towards the M13 star cluster in the constellation of Hercules, 25,000 light-years away, using the Arecibo Observatory, the most powerful radio telescope on Earth at the time.
With the assistance of AI, scientists are poised to more quickly unravel the age-old question of whether humans are the only intelligent beings in the universe.
