Awesome question! I definitely laughed.

The serious answer that the GitHub link clarifies is that the model is semi-unsupervised. That means they have a lot of data, but only some of it is labeled. Presumably, the labeled data is all negative because we understand its natural origin. So effectively this becomes almost an anomaly detection sort of thing, looking for data that is least like the known natural signals.

Even if it just directs scientists to look at new natural phenomena, this sounds like a valuable task.

Wouldn’t the sorts of signals our own planet emits be a good dataset to train to recognize the sorts of signals a civilization might generate? I’d assumed from the article this is what they’d done. Seems to me the key is whether we can discern, not necessarily interpret, communications, perhaps encrypted, from cosmic noise and natural phenomena, right? So train a model to recognize any human signals from noise. You’d look in those bands that we emit that are likely to make the journey to our neighbors.

To make the data more useful, you could simulate phase shifting in the datasets of our own EM communications. Perhaps you’d want to simulate other phenomena that is likely to modify celestial signals from a neighbor civilization.

All data used in this paper are stored as high-resolution FILTERBANK and HDF5 format collected and generated from observations by the Robert C. Byrd Green Bank Telescope, which are available through the Breakthrough Listen Open Data Archive at http://seti.berkeley.edu/opendata.

But every anomaly is a potential alien signal! Lol. The truth is out there (cue X-Files music)

I'm wondering too. We'll see if these repeat. It would be great if they did. I thought this is a cool application of AI/machine learning though.

Alliens are naturally occurring too

Very high.

The standard of evidence required for aliens is also very high. It's not enough to have no known natural explanation; there's lots of natural phenomena we don't know about yet. It must affirmatively and unavoidably be artificial even after many follow-up observations.