Artificial intelligence is helping us search for intelligent alien life – and we’ve found 8 strange new signals

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About 540 million years ago, diverse life forms suddenly began to emerge from the muddy ocean floors of planet Earth. This period is known as the Cambrian Explosion, and these aquatic creatures are our ancient ancestors.


All complex life on Earth evolved from these underwater creatures. Scientists believe that all it took was a small increase in oxygen levels in the oceans above a certain threshold.

We may now be in the midst of the Cambrian explosion artificial intelligence (AI). In the past few years, a series of artificial intelligence programs with amazing capabilities such as MedjourneyAnd DALL-E 2 And chat It showcased the rapid progress we’ve made in machine learning.

Artificial intelligence is now used in almost all areas of science to assist researchers with routine classification tasks. It also helps our team of radio astronomers expand the search for it extraterrestrial lifeThe results have been promising so far.

Detecting alien signals using artificial intelligence

As scientists search for evidence of intelligent life beyond Earth, we’ve built an artificial intelligence system that excels classic algorithms in signal detection tasks. Our AI is trained to search data from radio telescopes For signals that cannot be generated by normal astrophysical processes.

When we fed our AI a previously studied data set, we detected eight important signals that the classical algorithm missed. To be clear, these signals likely aren’t from extraterrestrial intelligence, and are likely rare cases of radio interference.

However, our findings – published today in natural astronomy– Shedding light on how artificial intelligence technologies will certainly play an ongoing role in the search for extraterrestrial intelligence.

Not very smart

AI algorithms do not “understand” or “think”. They excel at Pattern recognition, and they prove to be very useful for tasks like classification – but they don’t have the ability to solve problems. They only do the specific tasks they are trained to do.

So, although the idea of ​​extraterrestrial intelligence being discovered by AI sounds like the plot of an exciting sci-fi novel, both terms are flawed: AI programs are not smart, and they seek out Extraterrestrial intelligence No direct evidence of intelligence could be found.

Instead, radio astronomers look for radio “technical fingerprints.” These putative signals point to the presence of technology and, by proxy, to the existence of a community with the ability to harness technology for communication.

For our research, we created an algorithm that uses artificial intelligence methods to classify signals as either radio interference, or a true technical signature candidate. And our algorithm works better than we could have hoped.

What does our AI algorithm do

Searches for a technological footprint have been likened to looking for a needle in a cosmic haystack. Radio telescopes produce huge amounts of data, and in them huge amounts of interference from sources like phones, Wi-Fi, and satellites.

Search algorithms must be able to sort out real tech signatures from “false positives,” and do so quickly. Our AI classifier meets these requirements.

Created by Peter Ma, a University of Toronto student and lead author on our paper. To generate a set of training data, Peter inserted simulated signals into real data, and then used this data set to train an AI algorithm called an autoencoder. As the autoencoder processed the data, it “learned” to identify salient features in the data.

In a second step, these features were fed into an algorithm called a random forest classifier. This classifier creates decision trees to determine if the signal is noteworthy, or just radio interference – essentially separating the technical signature “needles” from the haystack.

After training our artificial intelligence algorithm, we fed him more than 150 terabytes of data (480 hours of observation) from the Green Bank Telescope in West Virginia. It identified 20,515 signals of interest, which we then had to manually screen. Of these signals, eight had the characteristics of technical signatures, and could not be attributed to radio interference.

Eight signals, no rediscovery

To try and check these signals, we went back to the telescope to re-monitor all eight of the important signals. Unfortunately, we were unable to rediscover any of them in our follow-up notes.

We’ve been through similar situations before. In 2020 we detected a signal that turned out to be harmful radio interference. While we’ll keep an eye on these eight new candidates, the most likely explanation is that they were unusual manifestations of radio interference: they’re not aliens.

Unfortunately, the wireless interference issue isn’t going anywhere. But we will be better prepared to deal with it as new technologies emerge.

Narrow your search

Our team recently published a file Powerful signal processor On the Meerkat Telescope in South Africa. MeerKAT uses a technique called interferometry to combine its 64 dishes to act as a single telescope. This technology is better able to determine where in the sky the signal is coming from, greatly reducing false positives from radio interference.

If astronomers can detect a technical signature that cannot be interpreted as confusionHowever, it strongly suggests that humans are not the only creators of technology within the galaxy. This would be one of the most profound discoveries imaginable.

At the same time, if we haven’t discovered something, it doesn’t necessarily mean that we are the only “intelligent” species with technological capabilities around. The lack of detection could also mean that we haven’t been looking for the right kind of signal, or that our telescopes aren’t sensitive enough yet to detect faint transmissions from distant exoplanets.

We may need to cross a sensitivity threshold before Cambrian explosion discoveries can be made. Instead, if we are truly alone, we should reflect on the unique beauty and fragility of life here on Earth.

more information:
Peter Xiangyuan Ma et al, An in-depth search of technical fingerprints from 820 nearby stars, natural astronomy (2023). DOI: 10.1038/s41550-022-01872-z

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