Tech
IBM and NASA Develop a Digital Twin of the Sun to Predict Future Solar Storms
The Sun’s most complex mysteries could soon be solved thanks to artificial intelligence. On August 20, IBM and NASA announced the launch of Surya, a foundation model for the sun. Having been trained on large datasets of solar activity, this AI tool aims to deepen humanity’s understanding of solar weather and accurately predict solar flares—bursts of electromagnetic radiation emitted by our star that threaten both astronauts in orbit and communications infrastructure on Earth.
Surya was trained with nine years of data collected by NASA’s Solar Dynamics Observatory (SDO), an instrument that has orbited the sun since 2010, taking high-resolution images every 12 seconds. The SDO captures observations of the sun at various different electromagnetic wavelengths to estimate the temperature of the star’s layers. It also takes precise measurements of the sun’s magnetic field—essential data for understanding how energy moves through the star, and for predicting solar storms.
Historically, interpreting this vast amount of diverse and complex data has been a challenge for heliophysicists. To address this challenge, IBM says that Surya’s developers used the SDO data to create a digital twin of the sun—a dynamic virtual replica of the star that is updated when new data is captured, and which can be manipulated and more easily studied.
The process began with unifying the various data formats fed into the model, allowing it to process them consistently. Next, a long-range vision transformer was employed—AI architecture that enables detailed analysis of very high-resolution images and the identification of relationships between their components, regardless of their distance.
The model’s performance was optimized using a mechanism called spectral gating, which reduces memory usage by up to 5 percent by filtering out noise in the data, thereby increasing the quality of the processed information.
More Accurate Predictions in Less Time
Its developers say that this design gives Surya a significant advantage: Unlike other algorithms that require extensive labeling of the data that’s fed to them, Surya can learn directly from raw data. This allows it to quickly adapt to different tasks and deliver reliable results in less time.
During testing, Surya demonstrated its versatility in integrating data from other instruments, such as the Parker Solar Probe and the Solar and Heliospheric Observatory (SOHO), two other spacecraft that observe the sun. Surya also proved to be effective in various predictive functions, including predicting flare activity and solar wind speed.
According to IBM, traditional prediction models can only predict a flare one hour in advance based on signals detected in specific regions of the sun. In contrast, “Surya provided a two-hour lead by using visual information. The model is thought to be the first to provide a warning of this kind. In early testing of the model, the team said they achieved a 16 percent improvement in solar flare classification accuracy, a marked improvement over existing methods,” the company said in a statement.
NASA stresses that, although the model was designed to study heliophysics, its architecture is adaptable to different fields, from planetary science to Earth observation. “By developing a foundation model trained on NASA’s heliophysics data, we’re making it easier to analyze the complexities of the sun’s behavior with unprecedented speed and precision,” said Kevin Murphy, NASA’s director of data science, in a statement. “This model empowers broader understanding of how solar activity impacts critical systems and technologies that we all rely on here on Earth.”
The risk posed by abnormal solar activity is not minor. A major solar storm could directly affect global telecommunications, collapse electrical grids, and disturb GPS navigation, satellite operations, internet connections, and radio transmissions.
Andrés Muñoz-Jaramillo, a solar physicist at the Southwest Research Institute in San Antonio, Texas, and lead scientist on the project, emphasized that Surya’s goal is to maximize the lead time for these possible scenarios. “We want to give Earth the longest lead time possible. Our hope is that the model has learned all the critical processes behind our star’s evolution through time so that we can extract actionable insights.”
This story originally appeared on WIRED en Español and has been translated from Spanish.
Tech
Two Thinking Machines Lab Cofounders Are Leaving to Rejoin OpenAI
Thinking Machines cofounders Barret Zoph and Luke Metz are leaving the fledgling AI lab and rejoining OpenAI, the ChatGPT-maker announced on Thursday. OpenAI’s CEO of applications, Fidji Simo, shared the news in a memo to staff Thursday afternoon.
The news was first reported on X by technology reporter Kylie Robison, who wrote that Zoph was fired for “unethical conduct.”
A source close to Thinking Machines said that Zoph had shared confidential company information with competitors. WIRED was unable to verify this information with Zoph, who did not immediately respond to WIRED’s request for comment.
Zoph told Thinking Machines CEO Mira Murati on Monday he was considering leaving, then was fired today, according to the memo from Simo. She goes on to write that OpenAI doesn’t share the same concerns about Zoph as Murati.
The personnel shake-up is a major win for OpenAI, which recently lost its VP of research, Jerry Tworek.
Another Thinking Machines Lab staffer, Sam Schoenholz, is also rejoining OpenAI, the source said.
Zoph and Metz left OpenAI in late 2024 to start Thinking Machines with Murati, who had been the ChatGPT-maker’s chief technology officer.
This is a developing story. Please check back for updates.
Tech
Tech Workers Are Condemning ICE Even as Their CEOs Stay Quiet
Since Donald Trump returned to the White House last January, the biggest names in tech have mostly fallen in line with the new regime, attending dinners with officials, heaping praise upon the administration, presenting the president with lavish gifts, and pleading for Trump’s permission to sell their products to China. It’s been mostly business as usual for Silicon Valley over the past year, even as the administration ignored a wide range of constitutional norms and attempted to slap arbitrary fees on everything from chip exports to worker visas for high-skilled immigrants employed by tech firms.
But after an ICE agent shot and killed an unarmed US citizen, Renee Nicole Good, in broad daylight in Minneapolis last week, a number of tech leaders have begun publicly speaking out about the Trump administration’s tactics. This includes prominent researchers at Google and Anthropic, who have denounced the killing as calloused and immoral. The most wealthy and powerful tech CEOs are still staying silent as ICE floods America’s streets, but now some researchers and engineers working for them have chosen to break rank.
More than 150 tech workers have so far signed a petition asking for their company CEOs to call the White House, demand that ICE leave US cities, and speak out publicly against the agency’s recent violence. Anne Diemer, a human resources consultant and former Stripe employee who organized the petition, says that workers at Meta, Google, Amazon, OpenAI, TikTok, Spotify, Salesforce, Linkedin, and Rippling are among those who have signed. The group plans to make the list public once they reach 200 signatories.
“I think so many tech folks have felt like they can’t speak up,” Diemer told WIRED. “I want tech leaders to call the country’s leaders and condemn ICE’s actions, but even if this helps people find their people and take a small part in fighting fascism, then that’s cool, too.”
Nikhil Thorat, an engineer at Anthropic, said in a lengthy post on X that Good’s killing had “stirred something” in him. “A mother was gunned down in the street by ICE, and the government doesn’t even have the decency to perform a scripted condolence,” he wrote. Thorat added that the moral foundation of modern society is “infected, and is festering,” and the country is living through a “cosplay” of Nazi Germany, a time when people also stayed silent out of fear.
Jonathan Frankle, chief AI scientist at Databricks, added a “+1” to Thorat’s post. Shrisha Radhakrishna, chief technology and chief product officer of real estate platform Opendoor, replied that what happened to Good is “not normal. It’s immoral. The speed at which the administration is moving to dehumanize a mother is terrifying.” Other users who identified themselves as employees at OpenAI and Anthropic also responded in support of Thorat.
Shortly after Good was shot, Jeff Dean, an early Google employee and University of Minnesota graduate who is now the chief scientist at Google DeepMind and Google Research, began re-sharing posts with his 400,000 X followers criticizing the Trump administration’s immigration tactics, including one outlining circumstances in which deadly force isn’t justified for police officers interacting with moving vehicles.
He then weighed in himself. “This is completely not okay, and we can’t become numb to repeated instances of illegal and unconstitutional action by government agencies,” Dean wrote in an X post on January 10. “The recent days have been horrific.” He linked to a video of a teenager—identified as a US citizen—being violently arrested at a Target in Richfield, Minnesota.
In response to US Vice President JD Vance’s assertion on X that Good was trying to run over the ICE agent with her vehicle, Aaron Levie, the CEO of the cloud storage company Box, replied, “Why is he shooting after he’s fully out of harm’s way (2nd and 3rd shot)? Why doesn’t he just move away from the vehicle instead of standing in front of it?” He added a screenshot of a Justice Department webpage outlining best practices for law enforcement officers interacting with suspects in moving vehicles.
Tech
A Brain Mechanism Explains Why People Leave Certain Tasks for Later
How does procrastination arise? The reason you decide to postpone household chores and spend your time browsing social media could be explained by the workings of a brain circuit. Recent research has identified a neural connection responsible for delaying the start of activities associated with unpleasant experiences, even when these activities offer a clear reward.
The study, led by Ken-ichi Amemori, a neuroscientist at Kyoto University, aimed to analyze the brain mechanisms that reduce motivation to act when a task involves stress, punishment, or discomfort. To do this, the researchers designed an experiment with monkeys, a widely used model for understanding decisionmaking and motivation processes in the brain.
The scientists worked with two macaques that were trained to perform various decisionmaking tasks. In the first phase of the experiment, after a period of water restriction, the animals could activate one of two levers that released different amounts of liquid; one option offered a smaller reward and the other a larger one. This exercise allowed them to evaluate how the value of the reward influences the willingness to perform an action.
In a later stage, the experimental design incorporated an unpleasant element. The monkeys were given the choice of drinking a moderate amount of water without negative consequences or drinking a larger amount on the condition of receiving a direct blast of air in the face. Although the reward was greater in the second option, it involved an uncomfortable experience.
As the researchers anticipated, the macaques’ motivation to complete the task and access the water decreased considerably when the aversive stimulus was introduced. This behavior allowed them to identify a brain circuit that acts as a brake on motivation in the face of anticipated adverse situations. In particular, the connection between the ventral striatum and the ventral pallidum, two structures located in the basal ganglia of the brain, known for their role in regulating pleasure, motivation, and reward systems, was observed to be involved.
The neural analysis revealed that when the brain anticipates an unpleasant event or potential punishment, the ventral striatum is activated and sends an inhibitory signal to the ventral pallidum, which is normally responsible for driving the intention to perform an action. In other words, this communication reduces the impulse to act when the task is associated with a negative experience.
The Brain Connection Behind Procrastination
To investigate the specific role of this connection, as described in the study published in the journal Current Biology, researchers used a chemogenetic technique that, through the administration of a specialized drug, temporarily disrupted communication between the two brain regions. By doing so, the monkeys regained the motivation to initiate tasks, even in those tests that involved blowing air.
Notably, the inhibitory substance produced no change in trials where reward was not accompanied by punishment. This result suggests that the EV-PV circuit does not regulate motivation in a general way, but rather is specifically activated to suppress it when there is an expectation of discomfort. In this sense, apathy toward unpleasant tasks appears to develop gradually as communication between these two regions intensifies.
Beyond explaining why people tend to unconsciously resist starting household chores or uncomfortable obligations, the findings have relevant implications for understanding disorders such as depression or schizophrenia, in which patients often experience a significant loss of the drive to act.
However, Amemori emphasizes that this circuit serves an essential protective function. “Overworking is very dangerous. This circuit protects us from burnout,” he said in comments reported by Nature. Therefore, he cautions that any attempt to externally modify this neural mechanism must be approached with care, as further research is needed to avoid interfering with the brain’s natural protective processes.
This story originally appeared in WIRED en Español and has been translated from Spanish.
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