Help scientists at LIGO train AI to resolve glitches in observational data

Since 2017, Virgo has helped LIGO localize astronomical phenomena

The detector near Pisa, Italy, coordinates its experimental runs with those in Hanford, Washington, and Livingston, Louisiana. Scientists can triangulate the locations of celestial events that generate gravitational waves using signal arrival times, just as earthquake locations can be determined from measurements at three seismic stations.

LIGO is part of the advanced gravitational wave detector network

Like the Laser Interferometer Gravitational-wave Observatory, Europe's Virgo Gravitational Wave Interferometer and Japan's Kamioka Gravitational Wave Detector reflect laser beams down perpendicular tunnels to detect gravitational waves in the patterns created by the recombined waves. Future observatories are expected to contribute to this network, further improving gravitational wave detections.

LIGO boosts its signal sensitivity by manipulating quantum uncertainty

According to the uncertainty principle, the amplitude, or height of a wave's peak, and its phase—the point in time when the first peak is observed—are inversely linked. Based on the frequency of the gravitational waves of interest, scientists sacrifice precision in one optical property to reduce noise in another.

Between 2002 and 2025, upgrades have increased LIGO's detection range tenfold

After the construction of Initial LIGO was completed in 1999, no gravitational waves were detected during operations between 2002 and 2010. Instrument redesigns and significant technological improvements brought about Advanced LIGO, which began observations in 2015. Continued upgrades between continuous laser runs have improved detection sensitivity and stability.

Blurriness in the James Webb Space Telescope's infrared imaging was fixed by AI

Australian researchers developed the Aperture Masking Interferometry Generative Observations AI algorithm to sharpen images affected by electronic distortions in the JWST's Aperture Masking Interferometer.

Gravitational waves—ripples in the fabric of spacetime—are detected at LIGO by measuring how two lasers traveling down equally distant, perpendicular tunnels interfere with one another after they reflect back and meet.

Six pigeons were trained to detect cancer from looking at CT scans—now that work is the basis for training new AI medical tools.

Test your ability to identify AI-generated images

This interactive project from MIT challenges users to distinguish between AI-generated images and real ones.

Using deep learning to analyze tumors

The explosive growth of life sciences data is driving artificial intelligence methods to gain traction in biology and medicine — including cancer research.

In LIGO's interferometers, light cancels itself out in the absence of gravitational waves

The devices are designed so that a laser is split into two beams that later recombine, canceling each other out and producing no signal. Changes in the lengths of the arms due to passing gravitational waves result in an interference pattern whose properties reveal features of the objects that created the waves.

LIGO made the first detection of gravitational waves

On February 11, 2016, scientists at the Laser Interferometer Gravitational-Wave Observatory announced the confirmed detection of ripples in spacetime, which were produced from the collision of two black holes 36 and 29 times the mass of the sun. The detection confirmed that gravitational waves travel at the speed of light, as predicted by Albert Einstein in 1915.

Advance genetic research by playing these scientific video games

Computers produce so much information that researchers can't properly analyze all the data produced, and the overload can also lead computers to make mistakes. Researchers are increasingly turning to citizen scientists—members of the public who are willing to volunteer—to help them make sense of data when computers can't. This article details a few of the ways you can contribute to genetics research by playing video games.

Watch the director's cut of the award-winning documentary about LIGO

Production on the film began in August 2015, shortly before the facilities detected gravitational waves for the first time on September 14. Those interviewed, including future Nobel Laureates Kip Thorne and Barry Barish, provide their accounts of the discovery as events unfold in real time.

Anthropic's interpretability team discusses how AI models' thinking mimics biology

Just as humans engage in complex behaviors to survive and reproduce, teams of experts in neuroscience, virology, mathematics, and other disciplines argue that large language models develop complex mechanisms to achieve their goals. These mechanisms can be manipulated to assess how they modify outputs—much like stimulating individual neurons—to uncover how LLMs "think."

Anthropic's Frontier Red Team assesses the dangers of its AI tools through 'evals'—safety tests that probe models to disclose sensitive information.

When you complete a CAPTCHA on a website to prove you are human, you may be unknowingly training algorithms for self-driving cars, whose systems require training data to help identify crosswalks, bicycles, and other outdoor objects.

How artificial intelligence, which detects patterns, can identify burnout

Researchers are training AI to detect stress-related symptoms, helping physicians and other medical workers recognize and reduce stress from overwork and potentially avoid burnout.

Just as large language models are trained on text to enable generative AI systems to mimic natural language, automated AI robotic systems are trained in virtual environments to help them 'learn' about the properties of reality.

Can AI revolutionize cancer detection?

Scientists have developed a tool to evaluate the risk of lung cancer, the most deadly form of the disease. Named "Sybil," this AI program was trained using CT scans with clear cancer signs, followed by scans where cancer wasn’t obvious. The tool is able to review CT scan data to predict a patient's of developing a lung cancer within six years. See how it works here.

Artificial intelligence may further enhance smart city data analysis

Identifying patterns within systems in the Internet of Things may enable AI tools to make informed decisions regarding transportation, safety, and sustainability without human intervention. However, such tools will also need to successfully address concerns about privacy, digital equity, and algorithmic bias.

Listen to the pair of colliding black holes detected by LIGO

As ripples in spacetime, gravitational waves do not produce sound, which is the perception of specific vibrations in matter (e.g., vocal cords vibrating air molecules). The "chirp" of gravitational waves comes instead from converting the spacetime ripples into sound waves that the human ear can hear.

The basis for AI image and video generation was first introduced in 2014

Through generative adversarial networks, the generator (a neural network that creates fictional data) competes against the discriminator (a neural network that assesses the data) to continuously train the former until it can make content indistinguishable from the real thing. Training with unstructured data can enable software to identify characteristics of gender, age, and expression.

AI may enable smart cities to drastically improve public safety

By utilizing machine learning techniques to analyze real-time monitoring reports against facial recognition databases, artificial intelligence can enhance the identification of criminals and coordinate an appropriate emergency response across various scenarios.

AI vs. machine learning vs. deep learning

Machine learning is best understood with visuals. A collection of the best 9 images, videos and flowcharts that explain what it is and how it works.

Potential LIGO sites were selected in pairs, approximately 3,000 kilometers apart

The 1,864-mile distance meant gravitational wave signals would be detected no more than 10 milliseconds apart, ruling out many background signals. The sites needed sufficient plots of nearly flat land, proximity to infrastructure (e.g., electricity), and adequate distance from urban areas and geologically active areas to reduce environmental noise.

The next generation of gravitational wave detectors may include a triangular design

The Einstein Telescope will use three pairs of underground detectors—each with arms separated by 60 degrees—arranged in an equilateral triangle. The European observatory will work alongside the Cosmic Explorer, a pair of new US detectors, to provide an eightfold increase in sensitivity over LIGO and extend the current detection frequency range.

See the news with AI-generated data visualizations

Realtime uses generative AI to create immediate data visualizations of news items on its regularly-updated feed, pulling from public data feeds. Peruse stories around sports, economics, politics, and more with the helpful aid of charts and graphs. See the shape of the news with this clever AI tool here.

The construction of LIGO needed to compensate for Earth's curvature

Across the 4-kilometer (2.5-mile) arms, the height of Earth's surface falls by almost a meter, preventing the lasers traveling within the arms from meeting the mirror at the end of each. Concrete slabs built beneath the arms help keep them level and provide structural support against seismic vibrations.

The AI that creates any picture you want and how it works

Since January 2021, advances in AI research produced a plethora of deep-learning models capable of generating original images from simple text prompts. Researchers at OpenAI, Google, Facebook, and others have developed yet to be released text-to-image tools, and similar models have proliferated online. This video is a primer on how we got here, how the technology works, and its implications.

The 2017 Nobel Prize in physics was awarded to LIGO's founders

Rainer Weiss, Kip Thorne, and Barry Barish won the award for their contributions to the detector a year after the discovery of gravitational waves was announced. Acknowledging the Nobel statutes limited the prize to no more than three people, Thorne stated, "our marvelous discovery is the work of more than a thousand."

Play 'Quick, Draw!' to help train Google's neural networks

Players are tasked with drawing objects, and Google’s AI—which has been trained on millions of user-submitted doodles—tries to guess what’s being sketched. Over 50 million drawings across 345 categories have been created and can be reviewed by users.

The European Space Agency is building a space-based gravitational wave observatory

The Laser Interferometer Space Antenna will consist of three spacecraft forming an equilateral triangle that will trail Earth as it orbits the sun. Lasers will travel 2.5 million kilometers along the sides of the triangle between these spacecraft to detect massive objects undergoing mergers or inspiraling, as well as speculative phenomena (e.g., cosmic strings).

Watch an animated visualization of how the Large Hadron Collider works, including how particles are accelerated through a series of machines and how collision data is collected and distributed worldwide.

Try to catch the 'sound' of black holes in gravitational wave detector data

In "Black Hole Hunter," users try to listen for gravitational wave signals from black holes in four sample data files that include substantial background noise. With each level, learn more about black holes while being faced with ever-quieter signals.

The NSF funded the design and construction of LIGO by MIT and Caltech

The 1992 Cooperative Agreement between the National Science Foundation and both research institutions came twelve years after funding 1.5-meter (4.9-foot) and 40-meter (131-foot) prototypes. With a 1992 budget of $395M, LIGO was once one of the largest NSF-funded projects in history

AI tools can reinforce existing societal biases—especially racial ones—because they are trained on human-created data containing implicit and explicit biases.

Throughout its 10-year mission to create a time-lapse of the universe, the Vera C. Rubin Observatory will generate 500 petabytes of data by taking an ultrawide, ultra-high definition image every 34 seconds.

AI tools that generate images, audio, video, and 3D models rely on diffusion models, which begin with random data, such as visual noise, and gradually refine it into the requested media.

Understanding how Claude Code and other AI coding agents function

Under human oversight, a supervising large language model interprets user tasks and delegates work to subordinate LLMs, which can generate code, fix bugs, and run tests, often most effectively for proofs of concept. Incremental backups and versioning are crucial when using such agents, which can lose details during their work as a result of compressing context history to work around memory limitations.

Decoding the hype around AI

2022 was the year AI broke onto the scene, with applications like ChatGPT amazing users with its ability to generate realistic-sounding answers. Technologist Arvind Narayanan presents a clear-eyed view of what the technologies can (and can't) do.

How AI helped the Beatles win their eighth Grammy

It’s been decades since the legendary British rock band broke up, yet they still managed to snag a Grammy at the 2025 awards ceremony. This feat is thanks to AI, specifically machine-learning technology, to isolate and clean up different components of a late 1970s recording. This mini-documentary shows how the band's surviving members crafted “Now and Then” with the modern technology.

Computer systems create artificial voices by stitching together phonemes—individual sounds that make up speech, such as 't,' 'long a,' and 'k' to say 'take.'

Teaching a robot to laugh

Researchers have designed a shared-laughter AI system that responds to human laughter in order to build a sense of empathy into dialogue. Learn how they did it with this explainer.

Create flute, saxophone, trumpet, or violin reproductions of any 15-second piece of audio using machine learning.

As of 2025, artificial intelligence systems remain narrow and specialized

Efforts are ongoing to create artificial general intelligence, where machines outperform humans across a wide range of cognitive tasks, including those for which they have not been specifically trained. Current models utilize machine learning and neural networks to perform tasks for which they are programmed, leveraging provided training data.

Scientists increasingly can't predict what AI will do

Most AI systems are so-called "black box" models, where we only see inputs and outputs while the inner workings remain obscure. This piece, written prior to the launch of ChatGPT, cautions developers to know why and how a system produces its results, and not to sacrifice explainability for accuracy.

AI excels at assisting with structured tasks involving logistics and planning

Tools like ChatGPT, Gemini, and Perplexity can help organize chaotic calendars, troubleshoot bedtime routines, and assist with salary planning and moving. However, specific quotes, like insurance, and local cost comparisons can be flawed since AI draws from nonlocalized datasets.

Emergency room evaluations may be improved with AI algorithms

Emergency room care teams must make fast and crucial decisions. They must determine if patients need to be admitted or discharged and when to order more tests or not. Researchers have been exploring how often patients died in the week after they were sent home and evaluating how this and other aspects of emergency care decision-making could be improved with AI algorithms to assist decision-makers.

Algorithms can be designed to train themselves and self-improve without human input, to the point where the optimized code is too complex for programmers to understand.

Anthropic's Claude Science is an AI workbench connected to more than 60 scientific databases, designed to assist scientific research in molecular and cellular biology and drug discovery.