天文学家

A global team of astronomers and machine learning researchers today announced the release of the "Multimodal Universe" - a groundbreaking 100 terabyte dataset that brings together hundreds of millions of astronomical observations in unprecedented detail and scale. This massive collection of space data aims to revolutionize how artificial intelligence can be applied to unlock the mysteries of the cosmos.

“DeepDISC relies on these AI models that are supervised, which means that to train them, we need some form of pre-labeled information,” Merz explained. This concept, known as ground truth in machine learning, poses a challenge because the project uses real data, such as the locations of stars. “We don’t know exactly where objects are beforehand,” he said. Another issue they encounter is deblending, a process in astronomy that involves differentiating and characterizing light sources in images.

For the first time, these computational tools offer astronomers the faculty of “systematically searching for the unknown,” Garraffo says. In January, AstroAI researchers used this method to catalogue over 14,000 detections from x-ray sources, which are otherwise difficult to categorize. Another way AI is proving fruitful is by sniffing out the chemical composition of the skies on alien planets.

Machine learning could boost multimessenger astronomy by automating crucial early phases of discovery, winnowing potential signals from torrents of noise-filled data so that astronomers can focus on the most tantalizing targets.

Using next-generation observatories like the Nancy Grace Roman Telescope and James Webb Space Telescope (JWST), astronomers intend to use ML to detect water, ice, and snow on rocky planets. While many ML models are trained to distinguish between different types of data, others are intended to produce new data. These generative models are a subset of AI techniques that create artificial data products, such as images, based on some underlying understanding of the data used to train it.

More recently, researchers harnessed 150,000 personal computers and 1.8 million citizen scientists to look for artificial radio signals. Now, researchers are using AI to sift through reams of data much more quickly and thoroughly than people can.

It is likely that essentially all jobs will become automated once we get true AI. ... No. Astronomy is data rich.