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    Home»Laptops»Oxford University is using AI to find supernovae in the sky
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    Oxford University is using AI to find supernovae in the sky

    techupdateadminBy techupdateadminSeptember 13, 2025No Comments3 Mins Read
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    NGC numbers: 2237, 2238, 2239, 2246 and the open star cluster NGC 2244. Taken in Nerja. Andalusia. South of Spain.
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    AI is everywhere, it can be overwhelming, and lots of folks will be sick of hearing about it. But it’s also important to continue to recognize where AI can make a real difference, including in helping our understanding of the universe.

    That’s exactly what’s been happening at Oxford University, one of the UK’s most respected academic centers. A new tool built by its researchers is enabling them to find “the needles in a cosmic haystack” while significantly reducing the workload on its scientists conducting the research.

    Specifically what’s been presented is an AI-powered tool that is helping astronomers find supernovae by providing an efficient way to comb through hundreds of signals per day that would take up hours of manpower ordinarily to manually sift through.


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    Instead, this new approach using the power of AI reduces the human aspect of the workload by as much as 85%, while maintaining an outstanding accuracy record and freeing up scientists to better use their time, and their minds.

    The Virtual Research Assistant is efficient and accurate and reduces the load on the astronomers who would ordinarily have processed the data manually. (Image credit: Getty Images | Javier Zayas Photography)

    From Oxford University, here’s a little about how it works:

    “The new tool, called the Virtual Research Assistant (VRA), is a collection of automated bots that mimics the human decision-making process by ranking alerts based on their likelihood of being real, extragalactic explosions. Unlike many AI-automated approaches that require vast training data and supercomputers, the VRA uses a leaner approach. Instead of data-hungry deep learning methods, the system uses smaller algorithms based on decision trees that looks for patterns in selected aspects of the data. This allows scientists to inject their expertise directly into the model and guide the algorithms to key features to look for.”

    One of the key takeaways besides the obvious time saving aspect for the scientists using it is that the VRA wasn’t built like an LLM, using massive datasets and equally massive quantities of computing power and energy.

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    Instead, it was possible to train using just 15,000 examples and a laptop to train the algorithms used in the VRA.

    Image of the ASUS ROG Zephyrus G14 (2025) gaming laptop.

    Unlike a traditional LLM, it was possible to train the VRA using nothing but a laptop. (Image credit: Windows Central | Zachary Boddy)

    It continues to update its assessments of the signals as the same patch of sky is re-scanned, and as such only the most likely positive signals get passed to the astronomers for final verification.

    In the first year of use, it processed over 30,000 alerts and missed less than 0.08% of real ones.

    With a new survey starting in 2026 that will produce up to 10 million alerts per night, having an AI tool that can reduce workload for the humans by 85% certainly sounds like it arrived at the right time.

    I won’t pretend to understand any of the science, but this is proof if ever it were needed of the benefits AI can provide. A human with the right expertise still has the final signoff, but properly trained AI can crunch significant quantities of data faster and make the end job for that human more efficient.

    AI isn’t always about asking ChatGPT to help with a recipe or researching your homework. In the right hands, it can do phenomenal work to change the way we understand the universe around us.

    Find Oxford sky supernovae University
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