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Artificial intelligence (AI) has been advancing rapidly, but its inner workings often remain obscure, characterized by a “black box” nature where the process of reaching conclusions is not visible. However, a significant breakthrough has been made by Prof. Dr. Jürgen Bajorath and his team, cheminformatics experts at the University of Bonn. They have devised a technique that uncovers the operational mechanisms of certain AI systems used in pharmaceutical research.

Surprisingly, their findings indicate that these AI models primarily rely on recalling existing data rather than learning specific chemical interactions for predicting the effectiveness of drugs. Their results have recently been published in Nature Machine Intelligence.

Which drug molecule is most effective? Researchers are feverishly searching for efficient active substances to combat diseases. These compounds often dock onto protein, which usually are enzymes or receptors that trigger a specific chain of physiological actions.

A long-awaited space mission in the coming year could herald the start of a new era where so many science fiction dreams finally begin to cement themselves as science fact. But first we must pass a critical test of our own making that pits our technological expansion into orbit against the sun itself.

It’s not that difficult to predict what science stories we’ll be talking about over the next year: artificial intelligence, climate change and advances in biotechnology will remain front of mind. But there’s a pair of happenings just beyond our planet that I’ll be watching closely, because they amount to tests of a sort that could determine the trajectory of our species.

The first story you’ve probably already heard about. NASA aims to launch its Artemis II mission by the end of the year, carrying humans on a journey around the moon and back. This marks the first time anyone has traveled farther than low-earth orbit in more than 50 years.

This whirling image features a bright spiral galaxy known as MCG-01–24-014, which is located about 275 million light-years from Earth. In addition to being a well-defined spiral galaxy, MCG-01–24-014 has an extremely energetic core known as an active galactic nucleus (AGN) and is categorized as a Type-2 Seyfert galaxy.

Seyfert galaxies, along with quasars, host one of the most common subclasses of AGN. While the precise categorization of AGNs is nuanced, Seyfert galaxies tend to be relatively nearby and their central AGN does not outshine its host, while quasars are very distant AGNs with incredible luminosities that outshine their host galaxies.

There are further subclasses of both Seyfert galaxies and quasars. In the case of Seyfert galaxies, the predominant subcategories are Type-1 and Type-2. Astronomers distinguish them by their spectra, the pattern that results when light is split into its constituent wavelengths. The spectral lines that Type-2 Seyfert galaxies emit are associated with specific ‘forbidden’ emission lines. To understand why emitted light from a galaxy could be forbidden, it helps to understand why spectra exist in the first place.