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Global Times: How did a decade of dedicated effort build China a self-reliant ‘digital track’?
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SHANGHAI, Sept. 18, 2026 It was 11 pm in the laboratory, and the lights were still on. Liu Hongyan sat at his workstation, watching lines of code and logs scroll densely across the screen. It was his third consecutive night on duty. The system had just completed a major iteration, and as a key member of the R&D team, Liu had to make sure every module was running stably.
At daybreak, in an electric-vehicle factory, the assembly line was operating at full capacity. Each freshly produced power battery was assigned a special “ID” code. That code would stay with the battery as it entered storage, was loaded onto vehicles and hit the road, accompanying it through its entire lifecycle.
From the laboratory to the factory, this invisible data flow connects every stage of production, circulation, use and recycling across industries. And the underlying infrastructure making all of this possible is the “Industrial Internet Identifier Resolution System,” which Liu and his colleagues helped build.
In simple terms, the system is like a “digital ID card plus navigation system” for the industrial world. In the real world, everyone has an identity card and every address has a street number; on the internet, every website has a domain name. Likewise, in the era of the industrial internet, every device, component, product and piece of data needs a unique, trustworthy and resolvable digital identity.
The Industrial Internet Identifier Resolution System is China’s national-level digital infrastructure that supports the generation, query, circulation and management of those digital identities. Built and operated over nearly a decade under the leadership of CAICT, the system has become a fully self-reliant and controllable “digital track” serving China’s industrial internet.
In the article “Build China into a Sci-Tech Powerhouse” included in Volume IV of Xi Jinping: The Governance of China, Chinese President Xi Jinping emphasized “increasing our country’s strength and self-reliance in science and technology, and keeping us well-positioned in vital areas of science, technology and development.”
Looking back on the decade-long campaign, Gao Qi, deputy chief engineer at CAICT’s Industrial Internet and Internet of Things Research Institute, feels this especially deeply.
“As a critical piece of digital infrastructure, the Industrial Internet Identifier Resolution System is a vivid embodiment of this important principle in the field of industrial digitalization,” Gao told the Global Times. What this system carries is precisely the historic mission of safeguarding the lifeline of China’s digital industry, and achieving industrial self-reliance and controllability, he said.
Pioneering in uncharted territory
Fast-forward to 2015.
By then, Liu had only recently joined the CAICT. Before that, his work had focused mainly on developing software for internet domain-name resolution, so he already had a basic understanding of the underlying logic of “resolution.” But when he was assigned to take part in planning and building China’s Industrial Internet Identifier Resolution System, he knew immediately that this was something entirely different.
At the outset of the project, the most pressing challenge was a classic “chokepoint” problem. China gained full access to the global internet in 1994, which essentially meant the comprehensive adoption of technical protocols, industrial ecosystems and governance rules developed elsewhere. Building a Chinese-owned, independent and controllable identifier resolution system was not a matter of filling in a single missing technology. It meant creating an entire system from scratch. At the time, many in the industry believed the challenge was enormous, and some even said it was “practically impossible.”
Why? Gao, one of the key strategic drivers behind the system, recalled that the challenge came on three levels.
First, China then lacked a voice in international standards and had little deep technical accumulation of its own, yet it was expected to build a system capable of covering the entire industrial chain and interoperating with dozens of heterogeneous systems. The technical difficulty was immense.
Second, in a landscape long reliant on foreign technologies, persuading tens of thousands of enterprises to adopt domestic identifiers was an enormous challenge in terms of industrial deployment and promotion. Many people dismissed the idea as sheer fantasy.
Third, with no clear expectation of return on investment, who would take responsibility for pushing the project forward and explore a sustainable operating model?
Gao said that from the project feasibility study stage, the team was thinking simultaneously about the technical roadmap, the system architecture and the industrial ecosystem as a closed loop. “We had to break through core technologies, but we also had to design a mechanism that would ensure companies would be willing to connect to the system and able to benefit from it,” he recalled.
On the front line, Liu felt the pressure in a direct and concrete way. Time was tight, the mission was heavy and there was no ready-made experience to copy. Everything had to be researched and designed at the same time, developed and verified in parallel.
“There was also the pressure on the team,” Liu told the Global Times. With the team under intense pressure, uncertainty in direction or repeated setbacks could easily cause anxiety among engineers. As both the leader of a development group and the person responsible for core module development, Liu had to solve technical problems while also keeping the team’s pace steady.
The work was tense, but Liu felt calm and confident. “The project had already been thoroughly validated by experts and academicians in China, so the direction was clear. What we, as R&D personnel, needed to do was find a way to bring the design goals to life in the system,” he said.
It was precisely this belief – the direction is clear, just keep moving forward – that sustained the team as it navigated uncharted territory step by step.
The road from zero to one is never smooth. Liu recalled a particularly tough test the team faced on the eve of deployment, just before the system was to go live. That day, testers suddenly reported a performance bottleneck. It was not a single-point failure; it was the kind of problem that rippled through the entire system, bringing many functions to a standstill. From morning until late at night, then from the early hours until daybreak, Liu and his teammates combed through the code line by line and tested again and again.
“As the launch drew near, it felt like the pressure had automatically spread to everyone,” said Liu. “Everyone was staring intently at the system, and no one felt sleepy.”
Finally, the problem was precisely identified and fixed. When the testers said the system had “passed,” there were no cheers or high-fives. They simply exchanged glances and smiled. “That smile wasn’t one of relief. It was the kind of smile that comes after winning a hard-fought battle,” Liu told the Global Times. “I was really happy at that moment. Not just because the problem was solved and the system could go live, but because I confirmed something even more important: our team had cohesion. When it mattered most, we didn’t fall apart. We could take on the toughest fights.”
After countless days and nights, this group of Chinese engineers laid down a solid foundation for China’s high-quality industrial development with technology and conviction. The “digital track” was finally in place.
Serve the industrial chain
In the “Build China into a Sci-Tech Powerhouse” included in Volume IV of Xi Jinping: The Governance of China, Xi noted that, “we should make solid efforts to promote the deep integration of sci-tech innovation and industrial innovation, and boost new quality productive forces.”
On July 8, at a meeting that brought together the national science and technology award conference, the general assemblies of the members of the Chinese Academy of Sciences and the Chinese Academy of Engineering, and the 11th national congress of the China Association for Science and Technology, Xi further emphasized the need to promote the deep integration of sci-tech innovation with industrial innovation, opening up channels for accelerating the transformation of sci-tech achievements into real productive forces.
The value of technological innovation must ultimately be reflected in industry. From the very beginning, the Industrial Internet Identification and Resolution System was never designed to “publish papers.” It was designed to address longstanding pain points in the development of the real economy.
According to Gao, enterprises have long faced three common challenges in the process of digital and intelligent transformation: data could not be found because different systems lacked a unified identity; data could not be connected because cross-company mutual recognition was absent; and data could not be put to good use because intelligent decision-making could not be formed. The Industrial Internet Identifier Resolution System was built precisely to tackle these three issues and provide foundational capabilities.
But for a new technology to truly integrate into industry, writing code in front of a computer is not enough. Over the past decade, Gao has led his team on repeated visits to key industries, pushing the system from “technically feasible” to “commercially usable.” Liu and his colleagues have also visited many factory workshops and spoken face-to-face with business owners.
“Back in the office, what we saw were system metrics, interfaces, logs and data,” Liu said. “But once we were on site, we saw individual parts, production lines and real business processes. It felt completely different.”
During field research at enterprises, Liu and his coworkers witnessed firsthand how the system they had helped develop was enabling data connectivity across systems on production lines. They also learned that, in areas such as quality traceability, product management and supply-chain coordination, the system was helping companies reduce management costs and defect rates.
“At that moment, I felt that the identifiers were no longer just something on paper or on a platform – they were really being put to use. And once they start being used, they can go deeper and spread further,” Liu recalled. As an R&D engineer, Liu said he felt proud to see companies using the system he had helped develop on the ground. “The late nights and the pressure we went through were all worth it.”
Stories like this are countless in the system’s rollout. In the new-energy vehicle sector, for example, unified identifiers give each battery pack a unique identity, allowing it to be “recognizable at all times and traceable throughout the chain.” In high-end equipment manufacturing, data generated during the operation of large machinery is uploaded in real time through the system and analyzed to predict failure risks, enabling maintenance to be arranged in advance. In the pharmaceutical industry, identifiers make it possible to trace medicines through the entire process: from factory to pharmacy, every box can be verified.
Gao said that he is pleased to see more and more companies have shifted from “I have to use it” to “I want to use it.” He told the Global Times the system not only helps enterprises cut costs and improve efficiency in practice, but more importantly, “some scenarios that used to rely on foreign identifier systems are now being gradually replaced by our independently controllable system.”
From ‘follower’ to ‘pacesetter’
A decade of dedicated work has yielded a remarkable harvest for China’s Industrial Internet Identifier Resolution System.
The system now comprises 407 second-level nodes and more than 600,000 connected enterprises; the number of registered identities has surpassed 700 billion, with core indicators ranking among the world’s best. The system has been deeply deployed across more than 40 industries, including automotive, electronics, pharmaceuticals and equipment manufacturing, and now covers every province on the Chinese mainland. Viewed globally, it has become one of the largest industrial internet identifier practices in terms of scale, the broadest in application and the most mature in industrial ecosystem.
Looking back on the past decade, Gao summed up the system’s journey from “almost impossible” to global leadership as four key leaps.
The first was a strategic breakthrough, when the state explicitly incorporated the identity resolution system into its national strategy and completed the top-level design. The second was a technological breakthrough, marked by the independently designed national top-node architecture and advances in core protocols. The third was large-scale rollout, achieved through the innovative three-tier structure of national top nodes, second-level nodes and enterprise nodes. The fourth was value realization, as identities evolved from simply “enabling connectivity” to “creating value,” with deep integration into blockchain, AI and other emerging technologies.
Each leap was driven not by chance, but by the coordinated advancement of technology, industry and ecosystem development. “We did not just build a system. We explored a China-specific path characterized by national strategic guidance, breakthroughs led by research institutions, industry leadership from enterprises and ecosystem co-construction across the industrial chain,” Gao told the Global Times.
In Gao’s view, the most essential “code” behind the building of this system is a steadfast commitment to greater self-reliance and strength in science and technology. “We did not simply copy foreign technologies. Instead, we focused on national strategic needs and pursued independent innovation, advancing basic research, key technological breakthroughs and industrial applications in parallel.”
On July 8, at the meeting bringing together the national science and technology award conference, the general assemblies of the members of the Chinese Academy of Sciences and the Chinese Academy of Engineering, and the 11th national congress of the China Association for Science and Technology, Xi underscored that, “We must seize the historic opportunity, rise to the challenges of the times, accelerate efforts to achieve high-level self-reliance and strength in science and technology, and make steady progress toward the 2035 goal of becoming a leading country in science and technology.”
In the field of the Industrial Internet Identifier Resolution System, China has, over the course of 10 years, transformed itself from a passive “follower” in global internet rules into a “pacesetter,” completing the full journey from following, to running alongside, to leading in some areas.
Gao said the greatest significance of building this system lies not only in creating an independent infrastructure, but in forging a development path with Chinese characteristics. “Having our own identifier system means China can participate more proactively in global digital governance and contribute Chinese wisdom in new areas such as trusted identity, trusted data and intelligent interconnectivity, while providing a more solid technological foundation for building a community with a shared future in cyberspace.”
On another ordinary evening at work, Liu’s desk lamp was still on. He was fine-tuning a new data exchange protocol, while test results flickered continuously across his screen. Nights like this have long become routine for him.
Outside the window, the lights of the city were coming on one by one. Behind him, countless streams of data were flowing, being parsed and transmitted through the system – traces left by products across the global industrial chain, and the digital imprint of China’s manufacturing sector as it moves toward high-quality development.
“I work on identity (system) for a day; I’ll work on it for a lifetime.” That is a phrase Liu often repeats. He says the road from “zero” to “one” has already been carved out; what matters now is to set out once again from “one.” Beyond that road lies an even faster digital frontier.
View original content:https://www.prnewswire.com/news-releases/global-times-how-did-a-decade-of-dedicated-effort-build-china-a-self-reliant-digital-track-302883353.html
SOURCE Global Times
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Technology
New Poll: Young Adults Nearly Split on Socialism, While 62% of Older Americans Reject It as a Capitalism Replacement
Published
32 minutes agoon
September 18, 2026By
Early data from iCitizen’s national survey reveals a sharp generational divide, with 18–34-year-olds divided 48% to 52% on free-market capitalism vs. socialism.
NASHVILLE, Tenn., Sept. 18, 2026 /PRNewswire/ — While a strong majority of Americans continue to favor free-market capitalism over socialism, a deep generational divide is emerging among younger voters, according to early polling data released today by icitizen.com.
Among more than 1,500 respondents surveyed in icitizen’s ongoing national economic poll, 62% overall rejected socialism as a replacement for capitalism. However, support for socialism jumps significantly among younger demographics: 48% of adults aged 18–34 supported socialism as an alternative, compared to just 29% of respondents aged 50 and older.
“While national toplines show broad support for free-market principles, the underlying demographic data tells a much more complex story,” said Tony Harkin, CEO of icitizen.com. “Younger generations are questioning traditional economic structures at dramatically higher rates than their parents and grandparents. As we approach the upcoming elections, this generational split on core economic philosophy could prove pivotal for policy debates.”
Key Findings
The Youth Divide: Adults aged 18–34 were almost evenly split, with 48% supporting socialism as a replacement for capitalism and 52% opposing.Partisan Consensus & Divergence: Opposition to socialism is strongest among Republicans (96%) and Independents (72%). Support remains heavily concentrated among Democrats (73%).Gender Gap: Women reported higher support for socialism (39%) than men (27%).
Methodology & Poll Details
The icitizen “Capitalism vs. Socialism” survey went live on September 3, 2026, and remains open for public participation through October 3, 2026. Data in this preliminary release reflects responses gathered through September 15, 2026 (N = 1,564). Note: Data represents a weighted online opt-in sample.
To view real-time updated results visit: https://icitizen.com/
About icitizen
icitizen is a civic engagement platform dedicated to connecting citizens, elected officials, and organizations through transparent polling and data insight tools.
View original content:https://www.prnewswire.com/news-releases/new-poll-young-adults-nearly-split-on-socialism-while-62-of-older-americans-reject-it-as-a-capitalism-replacement-302883404.html
SOURCE iCitizen
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AIR Experts to Present at the Society for Research on Educational Effectiveness 2026 Annual Conference
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32 minutes agoon
September 18, 2026By
ARLINGTON, Va., Sept. 18, 2026 /PRNewswire/ — Experts from the American Institutes for Research (AIR) will present at several sessions during the 2026 Society for Research on Educational Effectiveness (SREE) conference. The conference will be held September 23-26, 2026, at the Baltimore Marriott Waterfront in Baltimore, MD.
AIR experts will share their work across a variety of topics, including work-based learning, high-quality instructional materials; individualized math instruction; digital learning programs; and more. Built around the theme, “Education and Public Trust: Evidence and Accountability in a Changing Landscape,” the conference will bring together education researchers, policy leaders, and professionals from around the country.
AIR is a Silver Conference Sponsor and will have a booth available in the Exhibitor Hall. Sessions featuring AIR experts and their work are listed below (all times are in Eastern Daylight Time). Learn more about all conference presentations and activities on the conference website.
Wednesday, September 23
9:30 a.m. – 11:30 a.m.
Workshop: Matching Methods for Multilevel Data in Education Research: A Practical Guide and Illustration of Approaches in R
Location: Baltimore Marriott Waterfront – Laurel AB
AIR Authors: Jordan Rickles, Alberto Guzman-Alvarez, and Qi Zhang
2:45 p.m. – 4:15 p.m.
Paper Presentation: Impacts of Work-Based Learning Programs on Student Outcomes: A Systematic Review and Meta-Analysis
Location: Baltimore Marriott Waterfront – Laurel CD
AIR Presenters/Authors: Kelly Reese and Susan Therriault
Paper Presentation: From Foundational Skills to Community College: A Quasi-Experimental Study of Illinois Bridge Programs for Adult Learners
Location: Baltimore Marriott Waterfront – Laurel CD
AIR Presenters/Authors: Neha Nanda, Amani Talwar, Roman Ruiz, Jessica Stockham, and Oshin Khachikian
4:15 p.m. – 5:15 p.m.
Location: Baltimore Marriott Waterfront – Harborside Foyer
Poster Session: Motivation and Engagement Profiles in Middle School Social Studies and Their Instructional Implications
AIR Presenters/Authors: Alida Hudson, Lauren Artzi, Patrick Steele, Hannah Keepers, and Isabelle D’Souza
Poster Session: Ready Set Succeed: Examining the Impacts and Costs of a Kindergarten Transition Program
AIR Presenters/Authors: Leanne Elliott, Rachel Feldman, Danielle Riser, Lara Iqbal, Eboni Howard, and Hans Bos
Poster Session: Teaching Tomorrow’s Skills Today: Insights from the Teach Tech Kentucky Project
AIR Presenters/Authors: Laura Buckley, Rachel Garrett, and Eben Witherspoon
Poster Session: Building Trust in Educational Evidence: A Study of Reporting Bias in Impact Evaluations
AIR Presenter/Author: Joesph Taylor
Thursday, September 24
9:00 a.m. – 10:30 a.m.
Paper Presentation: The Impact of Teacher Professional Learning Designed to Support Effective Use of High-Quality Instructional Materials
Location: Baltimore Marriott Waterfront – Harbor D
AIR Presenters/Authors: Andrew Wayne, Sami Kitmitto, Catherine Jacques, Cheryl Graczewski, and Alice Hung
Paper Presentation: From Interviews to Evidence: Using Large Language Models Responsibly in Program Evaluation
Location: Baltimore Marriott Waterfront – Laurel AB
AIR Presenters/Authors: Ruhan Circi, Burhan Ogut, Tabitha Tezil, Eben Witherspoon, and Amelia Vasquez
10:30 a.m. – 11:30 a.m.
Location: Baltimore Marriott Waterfront – Harborside Foyer
Poster Session: Building Validity for AI-Supported Formative Assessment: Evidence From Phase 1 of the ADAPT-AI Project
AIR Presenters/Authors: Bo Zhu and Margarita Olivera-Aguilar
Poster Session: The Associations Between Preparation and Pathways and the Composition, Distribution, and Stability of Special Educators
AIR Presenter/Author: Allison Gilmour and Roddy Theobald
Poster Session: Research on Using Simulation to Practice Evidence-Based Math Instruction
AIR Presenters/Authors: Erin McCopp, Melissa Yisak, Rachel Garrett, Toni Smith, and Jasmine James
Poster Session: Of ‘Dear Colleague’ Letters and Federal Injunctions: How Federal DEI Actions Influence Teachers’ Use of Culturally Responsive Practices
AIR Presenters/Authors: Laura Brady
Poster Session: Teaching with AI: Building Evidence for Professional Learning That Supports Responsible Classroom Integration
AIR Presenters/Authors: Rebecca Bergey, Ryan Eisner, Tiffini Pruit- Britton, Dena Slanda, Fei Tan, Kelsey Woodrick, and Isaac Kaplan
Poster Session: Synthesizing Evidence on Standalone Digital Learning Programs in Math and Science to Inform K-12 Instructional Strategies
AIR Presenters/Authors: Qi Zhang and Kamal Middlebrook
3:30 p.m. – 5:00 p.m.
Panel: URE Moderated Discussion — Trusted by Whom? Rethinking Public Trust in Education Research
Location: Baltimore Marriott Waterfront – Harbor E
AIR Organizer & Panel Chair: Rachel Garrett
AIR Presenters/Authors: Joseph Taylor and Rachel Garrett
Friday, September 25
9:00 a.m. – 10:30 a.m.
Panel: RM Moderated Discussion — Supporting Early-Career Education Researchers
Location: Baltimore Marriott Waterfront – Harbor B
AIR Presenter/Author: Danielle Ferguson
Paper Presentation: Propensity Score Matching in Multilevel Educational Settings: A Review and Guide for Applied Researchers
Location: Baltimore Marriott Waterfront – Laurel AB
AIR Presenters/Authors: Jordan Rickles, Alberto Guzman-Alvarez and Qi Zhang
Paper Presentation: The Benefits and Costs of Educational Inclusion: Evidence from an Evaluation of the Special Olympics Unified Champion Schools Program
Location: Baltimore Marriott Waterfront – Galena
AIR Presenters/Authors: Jesse Levin, Rachel Feldman, Katie Laird, and Brad Salvato
10:45 a.m. – 12:15 p.m.
Keynote Panel: The Education Research Ecosystem: What Would it Take for Evidence to Matter More?
Location: Baltimore Marriott Waterfront – Harborside C Ballroom
AIR Convenor & Panel Chair: Dan Goldhaber
1:00 p.m. – 2:00 p.m.
Location: Baltimore Marriott Waterfront – Harborside Foyer
Poster Session: In-the-Pipeline: Individualized Math Instruction with The Modern Classrooms Project – Preliminary Analyses
AIR Presenters/Authors: Robert Nathenson, Xiaying Zheng, Erin McCopp, and Toni Smith
Poster Session: Using Retrospective Pretest Items in Educational Program
AIR Presenters/Authors: Diana Oh and Margarita Olivera-Aguilar
Poster Session: Designing and Evaluating AI‑Assisted Qualitative Analysis Workflows for Education Impact Studies
AIR Presenters/Authors: Graham Chickering, Billie Day, and Garry Davis
2:15 p.m.
Panel: OSS Invited Moderated Discussion — School Accountability and Turnaround in a Time of Federal Limbo
Location: Baltimore Marriott Waterfront – Galena
AIR Presenter/Author: Drew Atchison and Kerstin Le Floch
5:15 p.m.
Paper Presentation: Nudged, But at What Cost? Assessing the State of Economic Evaluation in a Systematic Review of Postsecondary Nudge Interventions
Location: Baltimore Marriott Waterfront – Laurel CD
AIR Presenters/Authors: Chris Brooks, Melissa Rodgers, Charleen Gust, Amanda Danks, and Megan Austin
Paper Presentation: Scaling Effective Educational Interventions
Location: Baltimore Marriott Waterfront – Kent AB
AIR Presenters/Authors: Yinmei Wan
Saturday, September 26
8:30 a.m. – 10:00 a.m.
Paper Presentation: Student Engagement as a Pathway Linking Teacher Support to Mathematics Achievement: A Meta-Analytic Structural Equation Modeling Review
Location: Baltimore Marriott Waterfront – Laurel CD
AIR Presenters/Authors: Qi Zhang and Yibing Li
Paper Presentation: Student Perceptions of and Performance in Math: Effects of Middle School Access to Real-World Math Lessons
Location: Baltimore Marriott Waterfront – Laurel CD
AIR Presenters/Authors: Jordan Rickles, Fei Tan, Santiago Nicotera, and Amelia Auchstetter
10:15 a.m. – 11:45 a.m.
Paper Presentation: Evaluation Findings of the Equity Leader Accelerator Program
Location: Baltimore Marriott Waterfront – Laurel AB
AIR Presenters/Authors: Martyna Citkowicz, Sarah Mae Olivar, Sarah Peko-Spicer, Jasmine James, Sonica Dhillon, and Jill Bowdon
Paper Presentation: Impacts of a Rural, Community-Based Summer Literacy Program on Early Elementary Struggling Readers’ Outcomes: Evidence from a Quasi-Experimental Study
Location: Baltimore Marriott Waterfront – Kent AB
AIR Presenters/Authors: Patrick Rich, Karen Manship, Aleksandra Holod, and Alberto Guzman-Alvarez
About AIR
Established in 1946, the American Institutes for Research (AIR) is a nonpartisan, not-for-profit organization that conducts behavioral and social science research and delivers technical assistance both domestically and internationally in the areas of education, health, and the workforce. With headquarters in Arlington, Virginia, AIR has offices across the U.S. and abroad. For more information, visit www.air.org.
Contact: Dana Tofig, dtofig@air.org
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SOURCE American Institutes for Research
Technology
USRA Contributes Planetary Science Expertise to NASA-IBM Lunar Foundation Model
Published
32 minutes agoon
September 18, 2026By
Open-source artificial intelligence model combines diverse lunar datasets to support scientific analysis of the Moon
WASHINGTON, Sept. 18, 2026 /PRNewswire/ — Universities Space Research Association (USRA) contributed planetary science expertise, lunar dataset development, and scientific evaluation to the newly released NASA-IBM Lunar Foundation Model, an open-source artificial intelligence (AI) model designed to help researchers analyze the large and diverse datasets collected by lunar missions.
Developed through a collaboration led by NASA and IBM Research, the NASA-IBM Lunar Foundation Model was pretrained from scratch using SomBench, a multimodal lunar dataset containing nearly two million co-registered data bundles spanning 11 modalities and two spatial scales. The model brings together complementary information about the lunar surface, including imagery, topography, illumination geometry, thermophysical properties, mineralogy, radar, gravity, and other geologic and environmental data.
USRA’s contribution to the project was provided by Dr. Rachel Slank, an associate scientist with USRA’s Science and Technology Institute, on assignment at NASA’s Marshall Space Flight Center. She served as a planetary science subject-matter expert on the NASA-IBM Lunar Foundation Model team. Slank worked across both the science and modeling teams, helping connect lunar science priorities and the physical characteristics of planetary datasets with decisions about model development, applications, and evaluation.
The NASA-IBM Lunar Foundation Model was evaluated across three downstream benchmarks: crater detection at both regional and meter scales, segmentation of irregular mare patches (IMPs), and regression of lunar polar ice prospectivity. Together, these applications assess the model’s performance across a diverse range of lunar science challenges, from identifying impact features and mapping unusual volcanic landforms to integrating environmental datasets associated with the stability and potential distribution of polar volatiles.
Across all three benchmarks, the pretrained NASA-IBM Lunar Foundation Model matched or outperformed comparison models based on ImageNet pretraining, as well as an architecturally identical model initialized without lunar pretraining. The study also demonstrated particularly strong label efficiency in crater detection, suggesting that the representations learned through lunar pretraining can reduce the amount of task-specific labeled data required for certain applications.
The multimodal design of the NASA-IBM Lunar Foundation Model allows it to learn relationships among different types of lunar observations rather than treating each dataset independently. The model was designed to operate across both regional-scale Wide Angle Camera (WAC) observations and meter-scale Narrow Angle Camera (NAC) data while incorporating information such as terrain, illumination geometry, and other lunar surface properties.
By releasing the pretrained model, fine-tuning code, and benchmark datasets openly, the NASA-IBM Lunar Foundation Model team aims to provide the planetary science and AI communities with a reusable foundation for developing new lunar research applications.
A major component of this work was the collaborative development of SomBench, the dataset used both to pretrain the NASA-IBM Lunar Foundation Model and to support standardized evaluation of lunar machine learning (ML) applications.
SomBench contains two complementary components: a core multi-instrument dataset that serves as the pretraining corpus for the NASA-IBM Lunar Foundation Model and a suite of application benchmarks used to evaluate ML methods on representative lunar science problems. The benchmark suite addresses three broad science themes: impact processes, volcanic history, and polar volatiles.
As part of that effort, Slank led development of the high-resolution Lunar Reconnaissance Orbiter Camera (LROC) NAC crater benchmark, manually identifying more than 49,000 lunar craters. The resulting dataset uses high-resolution lunar imagery together with co-registered digital terrain models to evaluate crater detection at meter-scale resolution. She also contributed to the broader SomBench datasets and science applications and provided extensive scientific review of both the SomBench study and the NASA-IBM Lunar Foundation Model study.
“One of the biggest challenges was bringing together lunar datasets that span very different instruments and spatial resolutions (1m to 20km per pixel) while still preserving the scientific value of each dataset,” said Dr. Slank. “Because I worked across both the science and modeling teams, I could help make sure those differences were considered as the data was brought together and used to train and evaluate the foundation model. I can’t wait to see what new science researchers will be able to do with the help of the NASA-IBM Lunar Foundation Model!”
The NASA-IBM Lunar Foundation Model and associated datasets are available through Hugging Face.
NASA announcement:
https://science.nasa.gov/science-research/artificial-intelligence-lunar-foundation-model/
IBM announcement:
About USRA
Founded in 1969, under the auspices of the National Academy of Sciences at the request of the U.S. Government, the Universities Space Research Association (USRA) is a nonprofit corporation chartered to advance space-related science, technology, and engineering. USRA operates scientific institutes and facilities and conducts other major research and educational programs under federal funding. It engages the university community and employs in-house scientific leadership, innovative research and development, and project management expertise.
More information about USRA is available at www.usra.edu.
PR Contact:
Suraiya Farukhi
sfarukhi@usra.edu
443-812-6945
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SOURCE Universities Space Research Association
New Poll: Young Adults Nearly Split on Socialism, While 62% of Older Americans Reject It as a Capitalism Replacement
AIR Experts to Present at the Society for Research on Educational Effectiveness 2026 Annual Conference
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