The universe is coming into clearer view, thanks to artificial intelligence. Leveraging the deep learning techniques of AI, a research group of astronomers mainly from the National Astronomical Observatory of Japan (NAOJ) have achieved extremely high accuracy for finding and classifying spiral galaxies. The group applied AI to an ultra-wide field-of-view images of the distant Universe observed by the Subaru Telescope and were able to classify as many as 560,00 galaxies from those images, according to the NAOJ. Previously, the amount visible in these images would have been impossible to be counted individually and detected by the human eye and therefore unable to be classified. However, the AI technique allowed the researchers to perform this massive pricing without any human contribution, the NAOJ said.

Humanity is still a long way away from a fully artificial intelligence system. For now at least, AI is particularly good at some specialized tasks, such as classifying cats in videos. Now it has a new skill set: identifying spiral patterns in galaxies. As with all AI skills, this one started out with categorized data. In this case, that data consisted of images of galaxies taken by the Subaru Telescope in Mauna Kea, Hawaii.

A research group, consisting of astronomers mainly from the National Astronomical Observatory of Japan (NAOJ), applied a deep-learning technique, a type of Artificial Intelligence (AI), to classify galaxies in a large dataset of images obtained with the Subaru Telescope. Thanks to its high sensitivity, as many as 560.000 galaxies have been detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological classification. The AI enabled the team to perform the processing without human intervention. Automated processing techniques for extraction and judgment of features with deep-learning algorithms have been rapidly developed since 2012.

Astronomers have applied artificial intelligence (AI) to ultra-wide field-of-view images of the distant Universe captured by the Subaru Telescope, and have achieved a very high accuracy for finding and classifying spiral galaxies in those images. This technique, in combination with citizen science, is expected to yield further discoveries in the future. A research group, consisting of astronomers mainly from the National Astronomical Observatory of Japan (NAOJ), applied a deep-learning technique, a type of AI, to classify galaxies in a large dataset of images obtained with the Subaru Telescope. Thanks to its high sensitivity, as many as 560,000 galaxies have been detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological classification.

This June, 2020, NASA announced that intelligent computer systems will be installed on space probes to direct the search for life on distant planets and moons, starting with the 2022/23 ESA ExoMars mission, before moving beyond to moons such as Jupiter's Europa, and of Saturn's Enceladus and Titan. "This is a visionary step in space exploration." said NASA researcher Victoria Da Poian. "It means that over time we'll have moved from the idea that humans are involved with nearly everything in space, to the idea that computers are equipped with intelligent systems, and they are trained to make some decisions and are able to transmit in priority the most interesting or time-critical information". "When first gathered, the data produced by the Mars Organic Molecule Analyzer (MOMA) toaster-sized life-searching instrument will not shout out'I've found life here', but will give us probabilities which will need to be analyzed," says Eric Lyness, software lead in the Planetary Environments Lab at NASA Goddard Space Flight Center. "We'll still need humans to interpret the findings, but the first filter will be the AI system".

A research group, consisting of astronomers mainly from the National Astronomical Observatory of Japan (NAOJ), applied a deep-learning technique, a type of AI, to classify galaxies in a large dataset of images obtained with the Subaru Telescope. Thanks to its high sensitivity, as many as 560,000 galaxies have been detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological classification. The AI enabled the team to perform the processing without human intervention. Automated processing techniques for extraction and judgment of features with deep-learning algorithms have been rapidly developed since 2012.

Astronomers have applied artificial intelligence (AI) to ultra-wide field-of-view images of the distant Universe captured by the Subaru Telescope, and have achieved a very high accuracy for finding and classifying spiral galaxies in those images. This technique, in combination with citizen science, is expected to yield further discoveries in the future. A research group, consisting of astronomers mainly from the National Astronomical Observatory of Japan (NAOJ), applied a deep-learning technique, a type of AI, to classify galaxies in a large dataset of images obtained with the Subaru Telescope. Thanks to its high sensitivity, as many as 560,000 galaxies have been detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological classification.

Astronomers have applied artificial intelligence (AI) to ultra-wide field-of-view images of the distant Universe captured by the Subaru Telescope, and have achieved a very high accuracy for finding and classifying spiral galaxies in those images. This technique, in combination with citizen science, is expected to yield further discoveries in the future. A research group, consisting of astronomers mainly from the National Astronomical Observatory of Japan (NAOJ), applied a deep-learning technique, a type of AI, to classify galaxies in a large dataset of images obtained with the Subaru Telescope. Thanks to its high sensitivity, as many as 560,000 galaxies have been detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological classification.