How AI is revolutionizing the search for extraterrestrials – 02/26/2024 – Science

There are between 10 and 50 billion possibly habitable worlds in our galaxy, says Bill Diamond. According to him, this makes his job quite difficult.

Diamond is chief executive of the US-based think tank Seti Institute. The letters Seti are an acronym for Search for Extraterrestrial Intelligence.

“Seti is looking for science and technology beyond the Solar System as evidence of life and intelligence. This is, broadly speaking, like looking for a needle in a haystack,” he says.

“We are looking for something that is probably extremely rare and that may be very difficult to find and extract from the background phenomena that we observe at the same time.”

But new tools are helping in the search. The ability of artificial intelligence (AI) to handle enormous databases — and to detect anomalies — is transforming the search for alien intelligence.

One of these projects involves a partnership between the Seti Institute and the National Radio Astronomy Observatory of the United States, in the State of New Mexico.

Federal infrastructure uses radio frequencies to study celestial objects such as planets, stars and asteroids.

Seti is building an AI-powered parallel software system for the observatory’s main facility, the Very Large Array (VLA).

Built between 1973 and 1981, the VLA is made up of 28 large satellite dishes, 25 meters in diameter, spread across a desert plain. Imagine residential satellite dishes, but on a gigantic scale.

Once operational, the AI ​​will be able to process every bit of data captured — two terabytes (TB) per second. For context, modern laptops today typically have a total storage capacity of around 1TB.

Star Trek

Diamond says the increasing use of AI is already proving indispensable to the institute’s work of hunting alien life.

And it says AI makes it possible to search for new types of radio signals from alien sources. He explains that Seti traditionally looks for narrowband signals similar to those used by humans.

“But the question always remained ‘what if there is an advanced alien technology that is using broadband (radio)?’. If that’s the case, our traditional methods wouldn’t work, it would look like a lot of noise on the screen.”

However, Diamond says AI’s ability to deal with huge amounts of data means it’s possible to take millions of “snapshots” of this audio image over time and start looking for patterns. “It’s a way to add something new to look for.”

Another project that Seti collaborates with is Breakthrough Listen. Backed with more than $125 million in private sector funding, the project scans one million stars and one hundred galaxies across a wide range of radio and optical bands for evidence of technological life.

One member of the project, Peter Ma, a student at the University of Toronto, recently developed a new AI system to examine data from telescopes and distinguish between possible real alien signals and interference.

His team did this by simulating both types of noise and then training the AI ​​to differentiate between the two.

Ma says that an alien signal, for example, “would only appear when we point our telescopes at it… and disappear when we point it away.”

The project has already identified eight potential alien signals that were not detected by traditional analysis. Ma believes, however, that as the observations have not yet been repeated, they are probably false positives.

AI is also being used to try to detect signs of life of a more modest nature and closer to home.

Last year, NASA’s Perseverance rover began collecting samples from Jezero Crater on Mars, which, if all goes well, will be brought to Earth several years from now.

Scientists already believe that the rover’s Sherloc instrument has detected organic compounds, which glow under ultraviolet light.

However, organic compounds can be created by non-biological processes, which means it is not yet possible to say whether they derive from past life on the planet.

But all that could change thanks to a new investigation from the Carnegie Institution for Science, which is using AI to analyze rock samples for signs of present or past life.

The team found that the AI ​​is able to distinguish ancient living and non-living materials with an accuracy of almost 90%.

“This is a very new approach to searching for molecular biosignatures,” says the project’s joint lead researcher, Dr. Robert Hazen.

“We employ machine learning to analyze the entire vast amount of data in an analytical method that produces half a million data points per sample. So we are looking for subtle patterns in the molecular distributions.”

Early plans are to use the system to analyze ancient samples from Earth, as well as some samples from Mars in the form of meteorites. But, says Hazen, “we could, for example, fly an instrument through the plumes of Enceladus (one of Saturn’s moons), or land a carefully designed instrument on Mars.”

It’s still early days, and any promising AI-generated results need to be validated by other observations, or by physics-based models, before they can be broadcast across the world.

But as more and more data is collected and analyzed, the chances of detecting alien life — if it exists — only increase.

Meanwhile, says Diamond, “progress is measured by the scale of effort, not results yet.”