AI Research

AI decodes dusty plasma mystery and describes new forces in nature

Published

1 month ago

August 3, 2025

Unlike typical AI research, where a model predicts outcomes or cleans up data, researchers at Emory University in Atlanta did something unusual. They trained a neural network to discover new physics.

The team achieved this unique feat by feeding their AI system experimental data from a mysterious state of matter called dusty plasma, a hot, electrically charged gas filled with tiny dust particles. The scientists then watched as the AI revealed surprisingly accurate descriptions of strange forces that were never fully understood before.

The development shows that AI can be used to uncover previously unknown laws that govern how particles interact in a chaotic system. Plus, it corrects long-held assumptions in plasma physics and opens the door to studying complex, many-particle systems ranging from living cells to industrial materials in entirely new ways.

“We showed that we can use AI to discover new physics. Our AI method is not a black box: we understand how and why it works. The framework it provides is also universal. It could potentially be applied to other many-body systems to open new routes to discovery,” Justin Burton, one of the study authors and a professor at Emory, said.

How did the AI learn to create laws?

The researchers combined real-world experiments with a carefully designed AI model. They began by studying dusty plasma. This state of matter is found across the universe, from Saturn’s rings and the moon’s surface to wildfire smoke on Earth.

However, despite its cosmic presence, the exact forces acting between the particles in dusty plasma have remained poorly understood. That’s because the system behaves in a non-reciprocal way, which means that the force one particle applies on another isn’t necessarily matched in return.

Understanding such interactions using traditional physics has proven incredibly difficult. So to tackle this problem, the scientists built a sophisticated 3D imaging system to observe how plastic dust particles moved inside a chamber filled with plasma. They used a laser sheet and high-speed camera to capture thousands of tiny particle movements in three dimensions over time.

These detailed trajectories were then used to train a custom neural network. Unlike most AI models that need huge datasets, the Emory team’s network was trained on a small but rich dataset and was engineered with built-in physical rules, like accounting for gravity, drag, and particle-to-particle forces.

“When you’re probing something new, you don’t have a lot of data to train AI. That meant we would have to design a neural network that could be trained with a small amount of data and still learn something new,” said Ilya Nemenman, senior study author and a professor at the university.

The neural network broke down the particle motion into three components: velocity effects (like drag), environmental forces (such as gravity), and inter-particle forces. This allowed the AI to learn complex behaviors while obeying basic physics principles.

As a result, it discovered precise descriptions of the non-reciprocal forces with over 99% accuracy. One surprising insight was that when one particle leads, it pulls the trailing one toward it, but the trailing one pushes the leader away. This kind of asymmetric interaction had been suspected but never clearly modeled before.

Neural network also rectified past assumptions

The AI corrected some faulty assumptions that shaped plasma theory for years. “What’s even more interesting is that we show that some common theoretical assumptions about these forces are not quite accurate. We’re able to correct these inaccuracies because we can now see what’s occurring in such exquisite detail,” Nemenman added.

For instance, one such assumption was that a particle’s electric charge increases exactly with its size—turns out, it doesn’t. Instead, the relationship depends on the surrounding plasma’s density and temperature.

Another mistaken idea was that the force between particles always decreases exponentially with distance, regardless of their size. The AI revealed that this drop-off also depends on how big the particles are, an insight previously overlooked.

The best part is, this AI model ran on something as modest as a desktop computer. It produced a universal framework that can now be applied to all sorts of many-particle systems, from paint mixtures to migrating cells in living organisms. This research also demonstrates that AI can go far beyond crunching numbers. It can actually help scientists discover the hidden rules that govern nature.

“For all the talk about how AI is revolutionizing science, there are very few examples where something fundamentally new has been found directly by an AI system,” Nemenman said. Hopefully, this work will encourage scientists to explore many other ways in which AI can benefit science and society.

The study is published in the journal PNAS.

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AI Research

Back to School – With Help From AI – Terms of Service with Clare Duffy

Published

24 minutes ago

September 16, 2025

The Editors

Back to School – With Help From AI – Terms of Service with Clare Duffy – Podcast on CNN Podcasts

Kirk suspect reportedly confesses, Tesla stock, ‘tooth-in-eye’ surgery & more

5 Things

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New technologies like artificial intelligence, facial recognition and social media algorithms are changing our world so fast that it can be hard to keep up. This cutting-edge tech often inspires overblown hype — and fear. That’s where we come in. Each week, CNN Tech Writer Clare Duffy will break down how these technologies work and what they’ll mean for your life in terms that don’t require an engineering degree to understand. And we’ll empower you to start experimenting with these tools, without getting played by them.

Back to School – With Help From AI

Sep 16, 2025

22 mins

Kids are heading back to school. One thing students, teachers and parents can expect to encounter this year is artificial intelligence, which has raised all kinds of questions, both positive and negative. So, how can you make sure your student is navigating AI safely and successfully? Dr. Kathleen Torregrossa has been an educator for 37 years in Cranston, Rhode Island. She explains how teachers are using AI in the classroom, and what families need to know about its impact on learning.

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This episode includes a reference to suicide. Help is available if you or someone you know is struggling with suicidal thoughts or mental health matters. In the US: Call or text 988, the Suicide & Crisis Lifeline. Globally: The International Association for Suicide Prevention and Befrienders Worldwide have contact information for crisis centers.

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AI Research

Lewis Honors College introduces ‘Ideas that Matter’ program series

Published

31 minutes ago

September 16, 2025

The Editors

LEXINGTON, Ky. (Sept. 16, 2025) — This fall, the Lewis Honors College (LHC) launches its “Ideas that Matter” series, a program connecting students with leading scholars, innovators and changemakers on issues shaping today’s world — from free speech and artificial intelligence to nonprofit innovation.

LHC Director of College Life Libby Hannon, who initiated the series, said the goal is to spark lively dialogue.

“The ‘Ideas that Matter’ discussions combine intellectually engaging questions with interactive conversations and allow our students to speak with some of the most forward-thinking scholars, changemakers and entrepreneurs from Lexington and beyond,” Hannon said.

The series begins Sept. 18 with University Research Professor Neal Hutchens, Ph.D., who will explore the historical and legal background of free speech and academic freedom in campus life. His talk, 5-6 p.m. in the Lewis Scholars Lounge, will conclude with an interactive Q&A.

“I’m especially looking forward to the conversation part of the evening, where we engage in and model the kind of vibrant back-and-forth that is crucial to maintaining systems of free speech and academic freedom,” Hutchens said.

On Oct. 6, Lewis Lecturer Sherelle Roberts, Ph.D., will moderate a panel of experts on artificial intelligence as they discuss “The Future of Earth and AI,” including the current and potential impacts of artificial intelligence on the future of work, the economy and the environment.

“Artificial Intelligence is quickly becoming a part of our everyday lives. Some even believe AI will transform our world as dramatically as the Industrial Revolution,” Roberts said. “This event will get our students thinking critically about our possible AI-driven future, while also having some fun.”

The event will begin at 5:30 p.m. with movie snacks and will transition into the panel discussion at 6 p.m., featuring faculty and staff from a variety of disciplines. The movie, an animated film that conceptualizes our AI-powered future, will begin at 7 p.m.

The final event of the semester on Nov. 11, will spotlight local nonprofit Operation Secret Santa (OSS), 5-6 p.m. in the Lewis Scholars Lounge. Founder Katie Keys and honors program alum Lucy Jett Waterbury will share the story of OSS’s creation in 2016 and its growing impact on the community.

“Operation Secret Santa is built on the belief that no child should face barriers to feeling loved and celebrated,” said Keys. “We meet families where they are, right at their doorsteps, bringing not only gifts and food, but the reminder that their village sees them and cares.”

“From (Katie’s) big heart, she has built a big, yet lean and efficient, nonprofit that has one very simple goal, to bring joy to Kentucky kids at Christmas time,” Waterbury said.

Through this series, LHC offers students a chance to engage with pressing issues, broaden their perspectives and learn directly from those making a difference.

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AI Research

Ethereum Foundation Bets Big on AI Agents with New Research Team

Published

1 hour ago

September 16, 2025

Trader Edge

TLDR

Ethereum Foundation launches new dAI Team led by research scientist Davide Crapis to connect blockchain and AI economies
Team focuses on enabling AI agents to make payments and coordinate without intermediaries on Ethereum
Group continues work on ERC-8004 standard for proving AI agent identity and trust
Initiative aims to make Ethereum the settlement layer for autonomous machine transactions
Foundation hiring AI researcher and project manager to staff the new specialized unit

The Ethereum Foundation has formed a specialized artificial intelligence research team to position Ethereum as the foundation for autonomous machine transactions. Research scientist Davide Crapis announced the new dAI Team on Monday, outlining plans to merge blockchain technology with AI systems.

The team will pursue two main goals according to Crapis. First, enabling AI agents to conduct payments and coordinate activities without human intermediaries. Second, building a decentralized AI infrastructure that reduces dependence on major technology companies.

We’re starting a new AI Team at the Ethereum Foundation (the dAI Team).
Our mission: make Ethereum the preferred settlement and coordination layer for AIs and the machine economy.

The team will focus on two main areas:
– AI Economy on Ethereum = giving AI agents and robots ways… pic.twitter.com/9sWVS4dp0K

— Davide Crapis (@DavideCrapis) September 15, 2025

Crapis leads the new unit and will connect its work with the Foundation’s protocol development group and ecosystem support division. The team has begun hiring for an AI researcher position and a project manager role to drive coordination efforts.

The dAI Team builds on existing work around ERC-8004, a proposed Ethereum standard co-authored by Crapis. This standard aims to establish identity and reputation systems for autonomous AI agents. The protocol would allow these agents to prove their trustworthiness and coordinate activities without centralized oversight.

AI Agent Infrastructure Development

The Ethereum Foundation sees growing demand for settlement systems as AI agents begin conducting more transactions. Crapis stated that intelligent agents need neutral infrastructure for handling value transfers and reputation management. Ethereum’s censorship resistance and verifiability make it suitable for these functions.

Current blockchain activity supports this vision of expanded use cases. CryptoQuant data shows Ethereum processed 12 million daily smart contract calls on Thursday. The analytics firm noted that network activity remains in expansion mode with record transaction volumes and active addresses.

AI agents operate as programs that make decisions with minimal human supervision. They can execute transactions and perform tasks on behalf of their programmers. Blockchains with programmable features like smart contracts provide suitable environments for these autonomous systems.

The Foundation restructured in 2025 to handle Ethereum’s growth through specialized units. The dAI Team represents part of this shift toward addressing emerging technologies. Previous focus areas included layer-2 scaling solutions and zero-knowledge proof development.

Decentralized AI Stack Goals

Multiple blockchain projects are working to integrate AI and distributed ledger technology. Matchain launched a decentralized AI blockchain in 2024. KiteAI announced an AI-driven blockchain in the Avalanche ecosystem in February 2025.

The Ethereum Foundation’s approach differs by focusing on standards and infrastructure rather than creating new blockchains. The dAI Team will support public goods and projects that combine AI with existing Ethereum capabilities.

Crapis emphasized the mutual benefits of linking AI and Ethereum. He stated that Ethereum makes AI more trustworthy while AI makes Ethereum more useful. This relationship could expand as more autonomous agents require blockchain services.

The team operates under Ethereum’s decentralized acceleration philosophy. This approach prioritizes open and verifiable AI development while maintaining human oversight of intelligent systems. The Foundation aims to prevent AI infrastructure lock-in by major technology companies.

Industry experts see potential for AI agents and blockchain technology to reshape digital commerce. The combination could enable new forms of autonomous economic activity without traditional intermediaries.

The Ethereum Foundation has begun publishing resources for the new team according to Crapis. He stated the Foundation will work with urgency to connect AI developers with the Ethereum ecosystem and accelerate research between the two fields.

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