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Vance says Iran agrees to nuclear inspections, as under Obama deal
Conversations with inspectors from the International Atomic Energy Agency could occur as soon as Monday, the vice president said, as negotiations continue in Switzerland.
Think human anatomy is finished? Scientists say think again
Despite centuries of study, scientists are still finding new details and even overlooked structures within the human body. As researchers explore anatomical differences between individuals, it’s becoming clear that the body is far more complex—and less fully understood—than textbooks suggest.
Potawatomi Ventures launches business program for Native entrepreneurs
Bwadwét Innovation Community is offering a new entrepreneurial training program for members of the Forest County Potawatomi, with classes ranging from marketing to legal readiness to financing.
Pow Wow showcases culture, history & entertainment
GRAND RAPIDS, Mich. (WOOD) – A big event is happening this weekend that combines culture, history, education, and entertainment. The relationship that the Nottawaseppi Huron Band of the Potawatomi …
New plasma trick could unlock smaller, more powerful computer chips
A new technique could solve one of the biggest challenges in making future computer chips from ultrathin materials. Researchers found that coating molybdenum disulfide with oxygen or fluorine lets manufacturers remove just the top layer of atoms much more safely during plasma processing. The result is a cleaner, more controlled path toward smaller and more capable electronics.
NASA’s Quantum Lab Aboard Space Station Gets Chilly Upgrade
Upgraded hardware will allow the Cold Atom Lab to set new records in quantum physics and help develop new technologies.
Atom Computing and Phasecraft Partner on Material Science Algorithms
Neutral-atom quantum hardware developer Atom Computing and quantum software specialist Phasecraft have signed a Memorandum of Understanding to collaborate on application-focused algorithms. The partnership aims to adapt Phasecraft’s hardware-optimized software to
Scientists Built a Tiny “Universe” And Watched Time Emerge From Chaos
Scientists created a miniature universe using 24,000 ultracold atoms where time emerges from entropy flow, potentially solving physics' biggest mystery.
Interpretable AI in materials discovery: Uncovering how models make predictions
A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features from an AI model trained on atomic structural data and optical absorption spectra, and then groups materials with similar structural and spectral characteristics. This approach can be extended to reveal how atomic arrangements influence other material properties, paving the way for more efficient materials design.
DA District 23: Incumbent Adam Panter, Mayor Daniel McClure clash over politics, experience
In Lincoln and Pottawatomie counties, incumbent DA Adam Panter faces a June 16, 2026, GOP primary challenge by McLoud Mayor Daniel McClure.
Supercomputer illuminates subatomic particle that helps hold matter together
A team of researchers has leveraged a supercomputer at the U.S. Department of Energy's (DOE) Argonne National Laboratory to reveal the internal structure of a pion in unprecedented detail. The findings ...
Scientists stunned by two-headed worms—now they’re multiplying without limits - Futura-Sciences
The Unusual Reproduction of Stenostomum brevipharyngium Meet Stenostomum brevipharyngium, a microscopic flatworm that has no need for romance or even a partner when it comes to making more of its kind. This species reproduces by paratomy, an asexual process in which a new worm forms from the middle section of...
The best recent science fiction, fantasy and horror
Not With a Bang by Temi Oh; Tillinghast by Clare Cavenagh; Atomic Coffin by Benedict Anning; The Unicorn Hunters by Katherine Arden; Bad Things Happen Here by Mark Morris
The Anatomy of a Conversion: Nicolaus Steno and the Search for Certain
Blessed Nicolaus Steno’s scientific discoveries and conversion to Catholicism emerged from a unified search for truth during the Scientific Revolution.
We can create the future of science right now
Paul Litvak is the founder and Executive Director of the Robyn Dawes Institute and a Visiting Scholar at UC Berkeley. He has a PhD in Behavioral Decision Research from Carnegie Mellon where he studied emotions and the sunk cost bias. Over 15 years in industry, he solved a wide range of challenging technical problems. At Meta he created models optimizing the ad review process. At Google he ran experiments to measure social influence. At Airbnb, he was a product manager leading machine learning teams optimizing search ranking and price suggestions. He also co-founded and led product at Rhythmic Health, a venture-backed biosensing startup, creating an accurate low cost system using a color changing strip and a smart phone to measure salivary lactate. The bottleneck At this point, it is uncontroversial to say that science needs to stop using the PDF article as the unit of knowledge and currency. The unbearable slowness of scientific publishing, the profit motive and margins: I’m not saying anything new. The PDF also sucks because it’s hard to extract structured information, which makes it hard to do evidence synthesis. As a result, we do much less evidence synthesis than is needed. And evidence synthesis ultimately undergirds most policy and medical decision-making. I can see second-by-second real-time odds for any sporting or newsworthy event, but a school board can’t see the best evidence on whether their 8th graders should be taught algebra. As a society, we don’t treat this as an important problem. Again, not controversial. Not only is the problem well understood, but the solution has already been laid out. What we need is AI-assisted living evidence synthesis - (1) an open knowledge graph of atomic claims, (2) claims linked to evidence, (3) assessment and synthesis of each piece of evidence, and (4) continuous updating with new data. What few realize (yet) is that the technical capacity to build this vision for a significant portion of science already exists. Not only that, scientists and startup teams are already building many of these components. I know this because I’ve been surveying the space and talking to many of the builders. There are some missing pieces: for example, evaluations of how well some of the components work. But at this point, most of what’s missing is a fully end-to-end working integration of all of these parts. In the rest of this essay, I’m going to lay out all the parts of a working living evidence layer for science and who is working on them, and propose concrete next steps for building this system. What’s now possible The diagram above outlines the components of a living evidence synthesis platform, including some of the teams working on each component1. Scientific PDFs are processed into claims with associated evidence. The evidence is subjected to a forensic audit, methodological evaluation and robustness and reproducibility checks. Finally it’s given a weight in a continuously updating synthesis. What follows is a description and status of each component and a few of the teams working on them. Document understanding The first thing you need to be able to do is turn an article into structured data. Mostly that means parsing PDFs. There are often multicolumn layouts that confuse non-specialized PDF to text processing libraries. For scientific papers, there is the added complexity of parsing formulas and tables and figures. This is a really hot area - there are startups offering APIs, and it seems like a new open source package gets posted to Github every few weeks. What follows isn’t exhaustive. A package called GROBID was the state of the art for a while, they didn’t update their package for nearly two years until very recently. In the meantime reducto.ai released an AI powered PDF extraction API, PaddleOCR became popular, IBM released a model called Docling, and both Mistral and Gemini created models and libraries. I also know of at least one other well-funded psychology research group working on a paper parser. By contrast, there are few open evals in this space, with no extensive evals for complex table comprehension in particular. Nonetheless, I’m confident this will be a solved problem soon, given the combination of LLM advances and developer interest. Hypothesis level extraction There has been increasing interest in comprehending the extracted text of papers and linking information to evidence for each hypothesis. A lot of work has already been done. Trialstreamer (Marshall et al. 2020) and RobotReviewer LIVE (Marshall et al. 2023) demonstrated automated extraction of trial population, intervention, and outcome at scale on clinical RCTs. PaperQA2 (Skarlinski et al. 2024) and Ai2 ScholarQA (2024) extended this to retrieval-augmented question answering with citation grounding. Elicit, Consensus, and SciSpace operationalized claim-level extraction for end users. OpenEval (Booeshaghi et al. 2026) is the most recent and most ambitious: 1.96 million atomic claims extracted from 16,087 eLife manuscripts using Claude Sonnet 4.5, grouped into ~299,000 results, with LLM evaluations showing 81% agreement with human peer review on a 2,487-paper subset. None of these solutions link claims to test-statistics, as you would need to evaluate randomized controlled trials. This is why I built the evidence.guide API - to extract hypotheses and associated test statistics from behavioral science papers. The best public eval of this kind of extraction I’m aware of comes from the recent SCORE project - they had humans code thousands of psychology papers to extract their claims by hand. It would be extremely helpful to the world if all scientific PDFs were available as structured open data. I’ve been working to make this happen, both directly at Berkeley and through coordination with large entities I can’t yet speak of; as hard as it is to do, I think it’s possible2. Forensic audit A lot of work has been done on forensic audit, but some gaps remain. Of course, for biology papers that rely on images for evidence, there are a variety of tools (notably Proofig and ImageTwin) to spot anomalies. These are still well short of what sleuths like Elizabeth Bik can do on her own, but these tools are constant companions among fraud analysts. There’s someone working on auditing Excel files for anomalies, and a number of teams are automating numerical checks like GRIM and SPRITE, including Scrutiny project, the INSPECT-SR team as well as statcheck. The regcheck team is building a way to use AI to compare preregistrations to analyses in papers, to ensure there aren’t significant deviations. Nonetheless, there are many other kinds of anomalies to screen for, both public and less publicly known. And there are no formal evals for anomaly detection that I’m aware of. Still, there’s a lot to draw from in this space and I’m pretty certain we will be able to scan papers for most kinds of obvious anomalies in the near future. Methodological review This area has been white hot, though I fear for many of the startups in this space, because this capability may become commoditized. There are at least six different AI peer review companies, including Refine.ink, Reviewer3, ReviewerZero.ai, Q.E.D. Science, Paper Wizard, and Isitcredible. Coarse (a pun on refine) was also recently created as an open source alternative. These systems provide qualitative feedback on the content of papers, spotting methodological weaknesses and mathematical errors. They seem to work pretty well, and many academics report bitterly that they exceed the average quality of typical peer reviewers. But there are few evals here either. What evals exist so far involve using LLM-as-judge (circularity problems abound) or comparing against human reviews of questionable quality. What you’d ideally want is an eval that measures capturing known errors in papers3. Reproducibility and robustness Another active area has been using AI agents to automate computational reproducibility4 and robustness5 checks in papers that report numerical results. For more recent papers where data and code are available, AI agents can see whether they can re-run the analyses and produce the numbers reported in the published paper. In addition to a handful of individual academics who have been experimenting using Claude Code for this, the Institute for Replication is a leading group working on building an end to end system. The evals related to this problem are the most mature, with CORE-Bench (Siegel, Kapoor, Narayanan 2024) and PaperBench (OpenAI 2025) available to benchmark agents on this task. There is also work on getting AI agents to test alternative ways of analyzing the data to ensure the results are robust to small analytic design choices. Synthesis This is the most underdeveloped area where significant investment is required. Although some automated evidence synthesis systems exist — for example, otto-sr is building an AI agent to write systematic reviews — none of these incorporate the full range of paper level signals to weight evidence appropriately. Nor is there anything like an eval or a gold standard for a good systematic review. Arguably Cochrane reviews are the closest we have to gold standard human systematic reviews, though I’ve heard academics in the know complain about their uneven quality. A key question for a synthesis platform is how to weight anomalies and methodological issues in assessing the quality of a piece of evidence. This is an unsolved problem and one I’m very keen to work on. Continuous updating There are many pieces of basic infrastructure available for monitoring for new research and initiating updates. OpenAlex is the current open citation graph. Retraction Watch integrated into Crossref in October 2023. Scite tracks how citations support, contrast, or mention prior claims. The Living Evidence Network demonstrated continuous-update workflows in clinical guidelines. Engineering this is a relatively straightforward task. When you look over this technical architecture and all the progress being made, it’s hard not to be optimistic that a living guide to scientific evidence will be built. The stakeholders are ready The social infrastructure for this is starting to coalesce — it’s not just a pie in the sky academic exercise to imagine this coming into existence. Institutions like the Center for Open Science, the Institute for Replication, the INSPECT-SR, the Living Evidence Network and more are all working on scaling work to improve research quality. Funders are also aligned. The Sloan Foundation has funded living evidence work through COS. Coefficient Giving supports the Institute for Replication and COS. The Astera Institute and the Institute for Progress have shown interest in this space. NIH has established an Office for Replication and Reproducibility. Although there are (very unfortunately) serious headwinds in science funding generally, there is an active group of funders interested in metascience. A brief word about what I’ve been doing at RDI. First, as a Visiting Scholar at Berkeley I’ve been actively figuring out how a non-profit and a public university can conduct and make public the results of large-scale academic article data mining. With some of the money I raised from donors, I commissioned a legal analysis of recent case law and publisher text data mining (TDM) agreements in order to understand whether a massive open data mining of academic articles is possible (with caveats, it is). I’ve also been working to bring together stakeholders in this space, and identify gaps. I’ve also been doing some software development in this space, with more to come. A pilot proposal The assumption undergirding all of this is that an AI, given all this information, would make the right judgment about a scientific claim with lots of conflicting evidence, weighing all the factors appropriately. That’s the hypothesis we need to test. Randomized control trial research is the best place to focus on first. RCTs are used to make many of the important decisions in society - from medical trials to public policy changes. And they use a relatively uniform set of inferential statistics with lots of known and available diagnostics. Behavioral science experiments, within the broader realm of RCTs, should be first used as a testbed whose results can be generalized. Because behavioral science is at the vanguard of open science practices, replications abound (there are thousands of them) to serve as ground truth training data. Key Hypothesis Therefore the pilot would test, in behavioral RCTs that have been replicated, whether the quality of evidence for a claim can be used to accurately predict whether that claim will replicate. Secondary Hypotheses Compared to claims that replicated, non-replicated claims demonstrate a greater share of forensic anomalies in their source literatures. Hypothesis level claim and statistic extraction is accurate enough to scale living evidence without onerous human review costs. Replication prediction is more accurate than prediction markets6 or journal prestige. If all the different quality signals we gather do accurately predict which studies will replicate, then we can use that model to score evidence to power the living evidence layer. Why this is informative regardless of outcome If the pilot succeeds, the architecture extends to medical RCTs (where Living Evidence already operates and integration is mostly about claim representation), then to slices of basic biology with stable replication structure. If it fails, the field learns which quality signals are load-bearing and which ones metascience has oversold. Either result is a contribution to knowing what the literature supports. Implications for funders Because this burgeoning ecosystem of builders already exists, a well-informed philanthropic or government funder could play a crucial catalyzing role in bringing this future about. They could play at least three roles: creating open structured datasets, publishing open benchmarks and incentivizing the solving of key technical challenges. First, open archives of papers that the government maintains, like PubMed, could be turned into structured data amenable to large scale metascience and claim aggregation. I know the US government already has an interest in doing this, though some key open questions remain unanswered. How do you determine the best models and systems for accurately extracting information from papers? How can you establish a robust way to allow researchers to flag errors and correct them? And finally, how do you create a legal regime in working with publishers to maximize the scope of available papers? For the latter, a university or a private philanthropy may be better positioned to make structured data publicly available under journal subscription terms or fair use. Philanthropists or government funders could also coordinate to create or commission benchmarks that evaluate whether important problems have been solved. For example, an open benchmark for claim extraction from a range of different scientific article types would be extremely helpful. Ensuring the underlying data are accurate is vital for creating these evaluations. I’ve discussed opportunistically using various human-created datasets for this purpose, but a consistent problem is that errors in human data make it difficult for them to serve as a gold standard. Finally, with structured data and benchmarks available, the government or private philanthropy could use them to incentivize groups to develop machine learning systems that meet these benchmarks. Prizes are one potentially valuable tool for this. For example, you could establish a prize for a system that accurately updates a living meta-analysis for a small set of claims. Prizes are particularly useful as signals of problem importance, and can help create vibrant ecosystems of public and private research—see, for example the role the government played in kickstarting the current work on nuclear fusion. Conclusion The drawbacks of the current scientific publishing system are known. Scientists agree, metascientists agree, philanthropists agree: the published PDF plus citation graph isn’t the right substrate for maintaining a representation of the evidence base in science. The pieces needed to build the alternative either already exist or are rapidly taking shape. The community is forming around exactly this problem, with concrete partnerships and shared infrastructure. A pilot should start on behavioral science RCTs because that’s the slice of empirical science most amenable to legibility, where replication ground truth is richest, and where the failure modes are best documented. What’s been missing is the galvanizing mission to assemble these pieces into something that works. That’s what I’m proposing to build. *** 1 I have a broader field map that I’ll release publicly soon. This is me, building in public! 2 If this is something that you are excited about, please reach out and talk to me. 3 More on this very soon too! 4 This tests whether, given the code and the data, you can get the same statistics as reported in the published paper. 5 This tests whether the results are the same as a paper’s given alternative analytical decisions in conducting the analysis (like outlier omission). Closely related is the idea of a “multiverse” where you come up with many different ways of answering the same underlying research question with the same data, and test whether the results hold in all those alternative methods. There’s been work on the latter as well. 6 Some of the replications, e.g. those from the SCORE project, had paired the experiments with forecasts from prediction markets. So we get to look at this for free.
Scientists design 2D materials with atomic precision for future devices, next-gen technologies
DOE scientists have created dozens of new MXene-related materials that can be controlled to design materials for future technologies.
Scientists found a surprisingly simple way to create powerful quantum states
A team at the University of Chicago has discovered a surprisingly simple way to create powerful quantum states that are normally difficult to produce. By making small adjustments to the energy levels of atoms inside an optical cavity, researchers can generate a wide variety of highly entangled states without adding complicated hardware.
Potawatomi Zoo hosts free admission day for children
Potawatomi Zoo offers free admission for children ages 14 and younger on June 10 during its annual Children's Day event.
A tiny atomic shift gives scientists powerful control over metals
A team at the University of Minnesota discovered that changing a metal film's thickness by just a few nanometers can dramatically alter how it behaves electronically. The finding reveals a surprising new way to control metals and could help power future advances in electronics, catalysis, and quantum technology.
Atomic City Quilts Seeks New Business Partners For Los Alamos Store
Quilt fabrics and more at Atomic City Quilts. Courtesy photo Scene from the Atomic Quilts store in Los Alamos. Courtesy photo Scene from the Atomic Quilts store in Los Alamos. Courtesy photo ATOMIC…
'Grey's Anatomy' star talks future amid cast exits: Every show 'gets canceled someday'
'Grey's Anatomy' actor Jason George has revealed he's returning to the show after the cast exit saw Kim Raver and Kevin McKidd leave the series: Every show 'gets canceled someday,' George said.
Scientists discover a quantum effect that could eliminate batteries
Researchers have discovered how microscopic imperfections and atomic vibrations can be used to control a powerful quantum effect in an advanced material. The effect can turn alternating electrical signals from the environment directly into the kind of current electronic devices need, without traditional components. As temperature changes, the signal can even flip direction, giving scientists a new way to tune device performance.
From atomic chaos to custom materials
Argonne researchers show how a class of 2D materials called MXenes can be designed atom-by-atom by tuning composition, atomic order and surface chemistry, opening paths to better materials for energy storage, electronics, shielding and biomedicine.
Factorial Raises $150 Million to Expand AI Agents in Business Software
Venture-capital firm General Catalyst led the funding round—that also attracted interest from Atomico and Four Rivers—as AI reshapes the business-management software market.
Atomic reshuffle leads to record-breaking catalysts for hydrogen production
Researchers have discovered that atoms can be mixed, separated, and recombined within the same experiment, providing a pathway to a record-breaking catalyst for green hydrogen production. In their study, ...
New light-powered chip could accelerate AI and quantum computing
Scientists have created a tiny chip that can generate, steer, and read light-based information all in one device, marking a major leap toward ultra-fast, energy-efficient computing. The breakthrough uses atomically thin materials and nanoscale structures to control a unique quantum property of light called the “valley” degree of freedom, allowing information to be encoded in new ways.
Vanderbilt Health study explores GLP-1 therapies to improve asthma outcomes in patients with obesity
The study is still recruiting participants. It will conclude in 2026 and provide insight for further investigations into the role GLP-1 agonists may offer in treating respiratory illnesses and overall immune responses.
Kratom drink Feel Free gains popularity despite growing concerns about addiction, health impact and death
Feel Free, a kratom drink, is easy to buy and increasingly popular, even as doctors and medical experts grow more concerned about its health impacts, addiction rates and deaths.
Gold Does Not Tarnish Like Other Metals And Scientists Finally Found a Major Reason Why
Gold’s shine may depend on a hidden atomic rearrangement at its surface.
Trump’s Science Advisor Calls Nuclear EO ‘Most Consequential Day’ Since Atoms for Peace in 1953
When a sitting administration’s top science advisor invokes Eisenhower’s 1953 Atoms for Peace speech to frame a present-day policy move, investors should pay attention. That is exactly what happened at the Operation Gigawatt Summit, where Michael Kratsios, Chief Science and Tech Policy Advisor to President Trump, anchored the case for a structural reordering of US ... Trump’s Science Advisor Calls Nuclear EO ‘Most Consequential Day’ Since Atoms for Peace in 1953
Trump's Science Advisor Calls Nuclear EO 'Most Consequential Day' Since Atoms for Peace in 1953
When a sitting administration’s top science advisor invokes Eisenhower’s 1953 Atoms for Peace speech to frame a present-day policy move, investors should pay attention. That is exactly what happened at the Operation Gigawatt Summit, where Michael Kratsios, Chief Science and Tech Policy Advisor to President Trump, anchored the case for a structural reordering of US ... Trump’s Science Advisor Calls Nuclear EO ‘Most Consequential Day’ Since Atoms for Peace in 1953
Wilmer Valderrama Reflects on Tragic ‘Grey’s Anatomy’ Arc, 10 Years Later
Here's what fans still say to him about Kyle Diaz.
Wilmer Valderrama Reflects on Tragic ‘Grey’s Anatomy’ Arc, 10 Years Later
Here's what fans still say to him about Kyle Diaz.
Scientists discover atoms suddenly spinning backward in quantum experiment
Scientists have directly watched angular momentum move through a crystal for the very first time — and discovered a bizarre twist along the way. Using ultra-powerful terahertz laser pulses, researchers triggered tiny atomic rotations inside a quantum material and found that the direction of rotation can unexpectedly flip as momentum is transferred. The strange reversal happens because of the crystal’s underlying symmetry, creating an almost impossible-sounding effect where two rotations combine into one spinning the opposite way.
Physics explains why gold stays pristine
Metals like copper oxidize — reacting with oxygen in the air — but gold doesn’t, thanks to a quick switch in atom arrangement on its surface.
Scientists discover a strange hidden state in “sandwich” molecules
Scientists have uncovered a strange hidden structure formed during the creation of metallocenes, a class of sandwich-like molecules used in everything from catalysis to medicine. The newly characterized intermediate features a rare “double ring-slip,” where both carbon rings partially detach from the metal atom. By finally observing this fleeting state, researchers gained fresh insight into how these molecules assemble and transform.
Scientists discover why gold doesn’t ‘rust’
Gold doesn’t tarnish like similar metals do. A new paper says that the key is the intricate “herringbone” pattern of its atoms.
Scientists Identify Atomic Trick That Keeps Gold Shiny
Gold’s characteristic glow famously doesn’t fade for thousands of years—and scientists have finally found the molecular trick that makes it so.
Physicists confirm 'negative time' is real by asking the atoms themselves
A new experiment confirms that photons passing through a cloud of atoms can spend a negative amount of time there, and the atoms themselves are the ones saying so.
A 'Grey's Anatomy' spinoff set in Texas is in the works. Here's what to know.
The untitled spinoff comes more than 20 years after the Ellen Pompeo-led series premiered.
New MatterChat Model Helps AI to ‘See’ the Language of Science
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.
Scientists Created a Subatomic Particle That Defies Our Understanding of Physics
The eta prime meson held together without one of the fundamental forces of the universe.
Kenyan scientist advances energy storage research in Germany
A Kenyan scientist in Germany is using advanced microscopy to study how batteries work at the atomic level—research that could lead to longer-lasting batteries while reducing the need for scarce raw materials.
Franklin County Career and Technology Center Adds Anatomage Table for Health Science Students
Franklin County Career and Technology Center is highlighting its new Anatomage Table, an advanced life-sized touch-screen display used for 3D anatomy education and virtual dissection. The table allows users to […]
Anatomy of a speech: how does a Republican leader say no to Trump?
South Carolina’s state senate majority leader offered a nuanced case for rejecting Trump’s redistricting demands
Puberty field trip? Philly-area students get a front-row seat to health education
Lankenau Medical Center’s health education center provides free interactive programs on nutrition, exercise, drugs and alcohol, puberty and more.
'Grey’s Anatomy' star Chyler Leigh announces split from husband of more than 20 years
'Grey's Anatomy' star Chyler Leigh announced that she has split from her husband after more than two decades of marriage: 'It was time to let it go.'
The First Atomic Bomb Made a Crystal Scientists Had Never Seen Before
Trinitite still holds strange matter forged in seconds by the Trinity blast.
MNG Brands Supports Science-Based Kratom Regulation and Consumer Safety Standards
MNG Brands, parent company of CBD Kratom and Korthals' Collection, including DER- a low-dose kratom beverage line developed in collaboration with actor and artist Nico Tortorella, is encouraged by the support shown for natural leaf kratom by President Donald J Trump. In an Oval Office appearance on May 10, the President stated that he was in favor of his Administration taking steps to approve some forms of kratom. "We're looking very seriously at natural 7-OH and getting that approved" was the m
Health department reminds of kratom risks following Marquette County overdose death
Marquette County has recently experienced an overdose death associated with the use of kratom derivative products that are available for legal retail sale.
A rare cancer-fighting plant compound has been decoded
Scientists at UBC Okanagan have uncovered how plants produce mitraphylline, a rare natural compound with promising anti cancer potential. The team identified two enzymes that work together to build the molecule’s unusual twisted structure, solving a mystery that had puzzled researchers for years. Because mitraphylline appears only in tiny amounts in tropical plants like kratom and cat’s claw, the discovery could make it far easier to produce sustainably in the future.
Amer Sports Sustainability Report 2025 is published
We have published the Amer Sports Sustainability Report 2025, which outlines our sustainability priorities, actions, and performance across climate, circularity, people, and the value chain during the…
New 'trick' fixes major flaw in neutral-atom quantum computers — inching us closer to a superpowerful system
A new "geometry‑based" quantum swap gate makes neutral‑atom computers far less sensitive to laser noise — bringing large‑scale, stable quantum processors a step closer to reality.
Scientists Discover a New Way To Control Metals at the Atomic Scale
The discovery could help make electronics faster and more energy efficient.
The hidden atomic gap that could break next-generation computer chips
A major obstacle may be standing in the way of the next generation of ultra-tiny computer chips. Researchers discovered that many promising 2D materials lose their advantages because an invisible atomic-scale gap forms when they are combined with insulating layers. That tiny gap weakens electronic performance and could prevent further miniaturization. The team says new “zipper materials” that lock together more tightly may offer a path forward.
Trends in Female First Authorship in Anatomical Science International: A 24-Year Analysis (2002-2025)
In recent years, the promotion of gender equity and diversity in academic research has attracted increasing international attention. However, studies examining gender differences in authorship w...
Scientists make stunning discovery that could change our understanding of the Universe
Scientists may have uncovered a surprising secret behind why life exists at all. A new study suggests that the Universe’s fundamental constants — the deep physical rules that govern everything from atoms to stars — appear to sit within an incredibly narrow “sweet spot” that allows liquids to flow properly inside living cells. Even tiny shifts in these constants could make blood too thick, water too sticky, or cellular motion impossible, potentially wiping out life as we know it.
Scientists Want to Use AI to Track Elusive Particles in the World’s Most Powerful Collider
Muons are a key subatomic particle in the discovery of new physics, but after particle collision, they’re difficult to track.
Northshore business owner arrested, accused of selling newly criminalized drug
A Covington business owner faces charges for allegedly selling kratom, a drug that became illegal in Louisiana less than a year ago.
Linked to health risks | Democratic lawmakers in Pa. are seeking to regulate kratom
Kratom, a substance advertised as an energy booster, mood lifter, and pain reliever, is skyrocketing in popularity and is easily accessible, including at gas stations.
Single dose of magic mushroom psychedelic can cause anatomical brain changes, study finds
Participants took 25mg of psilocybin, reporting deeper psychological insight and better wellbeing a month later
Scientists unlock new way to engineer next-generation glass
Scientists have adapted a centuries-old principle of chemistry to fine-tune a new type of glass made from metal–organic frameworks (MOFs)—metal atoms connected by organic molecules—that efficiently trap ...
MIT scientists finally reveal the hidden structure of a mysterious high-tech material
For decades, relaxor ferroelectrics have powered everything from medical ultrasounds to sonar systems, yet their inner atomic structure remained a mystery—until now. Researchers have finally mapped their three-dimensional structure in unprecedented detail, uncovering hidden patterns in how electric charges are arranged at the nanoscale. The breakthrough not only challenges long-standing assumptions about how these materials behave but also allows scientists to refine the models used to design them.
Grand Forks Public Health advises against using kratom products without medical oversight
Kratom is a plant, native to Southeast Asia, that is used in products that people ingest to self-treat pain, anxiety, depression and opioid withdrawal. The products are not FDA approved.
Punk Politics/Camp Costume is a fashion exhibition curated by (some of my) brilliant Parsons students!
I have the most amazing students. I teach Fashion Journalism at Parsons, as part of its MA Fashion Studies degree, though I have students of all different disciplines throughout the New School in my class — from fine-art photographers to investigative journalists to textile designers. And I learn about all sorts of fascinating things from them, like that designers are adding faux sweat stains to their garments now (part of a trend piece about “anatomy core”) and that real “French girl style” is actually about being “cunti cunta” (aka loud, rude, too much, liberated). So when I found out that some of my students were curating a fashion exhibition opening tonight(!!!), I just knew that it would be brilliant too. Wearable Art is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe It’s called Punk Politics/Camp Costuming1, and it’s up through May 10 at La Sudestada, the wonderful gallery and concept store in Greenpoint, Brooklyn. I asked the exhibit’s lead curator, Ella Birney (a talented costume and knitwear designer from Belfast who also happens to be in my class), all about it. This conversation has been edited for length and clarity. Tell me about the idea of this exhibition and how it came about. Ella Birney: For our Fashion Curation class, we had to pitch [exhibition] proposals to our professor, Jessica [Glasscock], and I really wanted to continue on the themes that I was exploring in my BA when I was studying in London a couple of years ago. My BA was very punk-inspired and very political. Everything I do, as you know from my writing, always has a slight Irish, political twist to it2. So in my BA project, it was looking at knitwear as a conveyor for exploring political identity in somewhere like Ireland, where identity is such a point of contention. And looking at the images that I generated from that project, there was something so camp about the whole thing. Like, it’s so playful and in bad taste to do a political message — like a knitted Union Jack — out of mohair. There’s something very camp about that. So that’s where it kind of became punk politics/camp costuming — looking at how from the 1970s to now there’s been protest through costume and clothing. What was your BA in? It was fashion textiles, knitwear. Very craft heavy, which — craft is never taken seriously either. That’s also a kind of spin [on the punk/camp thing]. The Union Jack knit that you made is included in the show — what is camp about knitting a Union Jack out of mohair? The whole ethos of camp is kind of bad taste, doing things that are tongue in cheek and a bit wink, wink, nudge, nudge. Like, this is a bit silly. Everything I do is like, this is a bit silly. Like, being from the North of Ireland, everything you do is political. So it’s like, everything is going to be looked at in a certain lens anyway, so we may as well lean into it. So the Union Jack was because I come from a mixed marriage — Protestant-Catholic. And in the North of Ireland, that’s still a big deal. And even though I’m a Catholic and brought up in a very like Catholic Nationalist family, there [were] Union Jacks [the symbol of the United Kingdom] on my street. So I was like, then I’m gonna make your Union Jack out of knitwear. And then that kind of all linked back to the punk movement that Vivian Westwood forefronted in the late 70s, [with her stores] Let It Rock and Seditionaries. How did you source your items? Once we decided on this exhibition idea, everyone in the class was put to [think about] what do you think can fit into punk politics/camp costuming and finding designers that fit that brief. Me and my co-curators, Dulcinea Flores and Allison Gramando, made a brief to send out — with a mood board and color stories, stuff like that — and then everyone kind of got to work emailing people. We reached out to other Parsons grads. Even through Instagram stories we’ve been able to reach so many people who were like, Yeah, of course, I’ll write something for this, or Please — let me submit stuff. It actually was quite easy sourcing things. … The Parsons thing gets you quite far. What were some great pieces you got? There’s a Brooklyn-based, nonbinary artist called Buzz Slutsky. I can’t even remember how I found them, but I came across this crazy, shoe thing — they had made all these different shoes out of papier-mâché, and the story behind them is so fantastic, so interesting. They were just so obliging, like, Of course, you can have these for a few weeks. I was really happy about that. And then we have art from a collective here called Art Comes First. And they lent loads of really amazing pieces that just tied everything together. You have your Union Jack knit in the show too. Any other pieces that you made? There’s three of my BA mohair knits. There’s the Union Jack. There’s a mohair with the word “No” — which is based on an old political campaign in Ireland that was “Ulster says no to sodomy.” And then there’s another one that is red, white and blue, like the Union Jack, but has the word “Catholic” on it and lots of holy medals. I’m so happy I got to include those. How many pieces are in the show? Between 49 and 52, something like that. A load of clothing and accessories, shoes. There’s a Brooklyn-based Irish photographer who’s given us photos. There’s also a shopping cart that is an art piece by Art Comes First that has gold knuckle dusters as the handles. There’s also lots of T-shirts, original pins from the 70s and 80s that were from people’s dads. I also brought my record player, and all of [co-curator] Allison’s dad’s original albums so everyone could play records. Oh my gosh! Yeah, it’s cool. Anything else you would like to add? If we get to do an exhibition, why would we not make it political in this day and age? I hope that people come. There’s a lot of history, because it starts back in the 70s. It’s not like chronological or anything, but there are historical objects. I hope people come out of it thinking, out of all the really horrendous decades of the 70s and 80s and 90s, all these amazing subcultures happened. There are horrible political times, but there’s art that comes out of it that lasts. Punk Politics/Camp Costume is on view May 1-10 at La Sudestada, 67 West St. Suite 513, Greenpoint, Brooklyn. RSVP for the opening Friday May 1 6pm-8pm here. There’s also a button-making and patch-making workshop and artist talk May 9. Follow the show’s Instagram page @punkxcamp.parsons. Special shout out to all the students who put on this show: Ella Birney (lead curator), Dulcinea Flores (curator), Allison Gramando (curator), Pierre Sanon (lead exhibition designer), Eliana Daneshvari (exhibition designer), Reilly Lowell (editor), Jess Gayo (researcher/writer), Joyce Gayo (researcher/writer), Maria Magdalena Ugarte Montero (researcher/writer), Cassidy Colarik (exhibition press officer), Shelby Shovein (educator), Sarah Mahnke-Baum (educator), Trinidy Coleman (graphic designer), and Leonie Soravia (project manager). Jessica Glasscock was the faculty advisor. 1 The website is definitely worth checking out. 2 This is true!
Scientists catch antimatter “atom” acting like a wave for the first time
Quantum physics once shocked scientists by revealing that particles can behave like waves—and now, that strange behavior has been pushed even further. For the first time, researchers have observed wave-like interference in positronium, an exotic “atom” made of an electron and its antimatter partner, a positron. This breakthrough not only strengthens the weird reality of quantum mechanics but also opens the door to new experiments involving antimatter, including the possibility of testing how gravity affects it—something never directly measured before.
April 30 dual language science lecture will explore industry in space
Dr. Solange Massa, founder and CEO of Ecoatoms, will give a science lecture split into English and Spanish with translation available for both languages.
Alleged would-be Trump assassin once made an "atomic fighting game", which Steam have now yanked from sale
Valve have disabled Steam purchases of Bohrdom, an experimental 2D game made by the developer accused of shooting up a White House press dinner in April 2026.
Scientists Think Time Could Move Fast and Slow All at Once. They’re About to Prove It.
Ultraprecise atomic clocks could test the idea that time moves at multiple speeds.
Trump Seeks to Abolish Iran’s Atomic Stockpile, a Problem He Helped Create
President Trump withdrew from the Obama-era nuclear accord in 2018, saying it was the worst deal ever. But Iran responded with an enrichment spree that haunts the negotiations to this day.
Al Gore Reflects on 20 Years Since 'An Inconvenient Truth'
The former vice president made an appearance at THR and the Sustainable Entertainment Alliance's Sustainability in Entertainment Honors, with awards presented to 'Paradise,' 'The Boroughs' and 'Grey's Anatomy.'
AI just discovered new physics in the fourth state of matter
Physicists have taken a major step toward using AI not just to analyze data, but to uncover entirely new laws of nature. By combining a specially designed neural network with precise 3D tracking of particles in a dusty plasma—a strange “fourth state of matter” found from space to wildfires—the team revealed hidden patterns in how particles interact. Their model captured complex, one-way (non-reciprocal) forces with over 99% accuracy and even overturned long-held assumptions about how these forces behave.
New issue: Mirrorlife | BBC Science Focus Magazine
Mirror life could end all life on Earth. That sounds dramatic, but senior biologists have raised the alarm about experiments happening all around the world. It sounds like something in a Doctor Who plot, but no – mirror life is a real possibility. So why do scientists want to create something that’s potentially apocalyptic? Well, it could also have huge benefits (think back to splitting the atom). The first thing to say, however, is that mirror organisms are still a little way away yet – but only decades, not centuries. So far, scientists have only made mirror molecules, one of life’s building blocks. What for? Life works because its building blocks fit together. Imagine drilling a screw into a piece of wood. The screw cuts a hole with a thread that snugly matches its own. If, for some reason, the Doctor showed up and handed you a mirror version of the screw, its thread would be in reverse. It wouldn’t twist into the hole you’d just made as the threads wouldn’t match. That said, the mirror screw would still work; you’d just have to create a mirror hole for it. Mirror molecules, including DNA, work a bit like that. They follow the same principles as the biology around us, but they’re entirely incompatible with traditional biological functions. In medical terms, this means they’re effectively invisible to your body’s systems. Our biology doesn’t have the tools to recognise these molecules and break them apart. And if someone took these mirror molecules and put them together to make a cell and then an organism… you’d have mirror life. But we don't have any way of breaking it down. If it escaped the lab, we’d just have to hope it didn’t have an appetite.
New NASA Views of Earth, From (S)PACE
NASA has a fleet of satellites in orbit, gathering data around the clock, to explore unique views of our home planet’s ocean, atmosphere, and land surfaces.
Visiting Fulbright scholar from Poland joins INL researcher to study actinide physics, unlock atomic secrets
For Adam Piotr Pikul of the Polish Academy of Sciences, there is always more to understand about the basic physics of uranium atoms. That’s why Pikul, a professor at the Institute of Low Temperature and Structure Research in Wrocław, is studying actinide quantum materials at the Idaho National Laboratory (INL) on a Fulbright Senior Award. Actinides are a group of 15 radioactive elements, including uranium.
A bizarre new state of matter may be hiding inside Uranus and Neptune
Deep inside planets like Uranus and Neptune, scientists may have uncovered a bizarre new state of matter where atoms behave in unexpected ways. Advanced simulations suggest that carbon and hydrogen, under crushing pressures and scorching temperatures, can form a strange hybrid phase—part solid, part fluid—where hydrogen atoms spiral through a rigid carbon framework. This unusual “superionic” structure could reshape how heat and electricity flow inside these distant worlds, potentially helping explain their mysterious magnetic fields.
Scientists Captured Light in a Trap 2,000 Times Thinner Than a Human Hair
Microscopic gadgets could be next.
Using atomic nuclei could allow scientists to read time more precisely than ever
Most clocks, from wristwatches to the systems that run GPS and the internet, work by tracking regular, repeating motions.
Building Custom Atomistic Simulation Workflows for Chemistry and Materials Science with NVIDIA ALCHEMI Toolkit
For decades, computational chemistry has faced a tug-of-war between accuracy and speed. Ab initio methods like density functional theory (DFT) provide high fidelity but are computationally expensive…
'Really, really weird': Physicists entangle two moving atoms for the first time, validating 'spooky' quantum theory
For the first time, scientists have observed quantum entanglement in the momentum of massive particles. The result, decades in the making, could help physicists probe the relationship between quantum mechanics and gravity.
Jaylen Brown on the Science Behind 741 Rover "Atomic Pack"
Jaylen Brown discusses why he wants fans to choose their energy with the 741 Rover "Atomic Pack."
How aggressive breast cancer turns off the immune system
Researchers are launching a new project to crack the mystery of aggressive breast cancer, where predicting disease progression remains a major hurdle. By studying how tumors interact with and suppress the immune system, scientists aim to identify new biomarkers that reveal how the cancer evolves. Using real patient samples, the team hopes to turn earlier discoveries into practical clinical tools. The goal: more precise, personalized treatments that can outsmart even the most dangerous tumors.
Gravitational waves may be hidden in the light atoms emit
Scientists have proposed a surprising new way to detect gravitational waves—by observing how they change the light emitted by atoms. These waves can subtly shift photon frequencies in different directions, leaving behind a detectable signature. The effect doesn’t change how much light atoms emit, which is why it’s gone unnoticed until now. If confirmed, this approach could lead to ultra-compact detectors using cold-atom systems.
Has ‘Grey’s Anatomy’ Already Done a Bridge Collapse Disaster Before?
We dig into the archives to find out why this storyline might seem familiar to fans.
City of Independence bans synthetic 7-OH, regulates kratom sold in businesses
The City of Independence voted to ban synthetic 7-OH and regulate its parent product, kratom, at Wednesday night's city council meeting.
MXene breakthrough boosts conductivity 160x with perfect atomic order
A new breakthrough is transforming MXenes—ultra-thin, high-tech materials—into something far more powerful and precise. Researchers have developed a cleaner, more controlled way to build these materials using molten salts and iodine, eliminating the messy chemical processes that once left their surfaces disordered. The result is a perfectly arranged atomic structure that lets electrons flow with remarkable ease, boosting conductivity by up to 160 times.
Las Vegas Atomic Museum hosting Star Wars science event
The National Atomic Testing Museum is partnering up with DRI for an out-of-this-world celebration of science and Star Wars.
Gemma 4 and what makes an open model succeed
Having written a lot of model release blog posts, there’s something much harder about reviewing open models when they drop relative to closed models, especially in 2026. In recent years, there were so few open models, so when Llama 3 was released most people were still doing research on Llama 2 and super happy to get an update. When Qwen 3 was released, the Llama 4 fiasco had just gone down, and a whole research community was emerging to study RL on Qwen 2.5 — it was a no brainer to upgrade. Today, when an open model releases, it’s competing with Qwen 3.5, Kimi K2.5, GLM 5, MiniMax M2.5, GPT-OSS, Arcee Large, Nemotron 3, Olmo 3, and others. The space is populated, but still feels full of hidden opportunity. The potential of open models feels like a dark matter, a potential we know is huge, but few clear recipes and examples for how to unlock it are out there. Agentic AI, OpenClaw, and everything brewing in that space is going to spur mass experimentation in open models to complement the likes of Claude and Codex, not replace them. Especially with open models, the benchmarks at release are an extremely incomplete story. In some ways this is exciting, as new open models have a much higher variance and ability to surprise, but it also points at some structural reasons that make building businesses and great AI experiences around open models harder than the closed alternatives. When a new Claude Opus or GPT drops, spending a few hours with them in my agentic workflows is genuinely a good vibe test. For open models, putting them through this test is a category error. Something else to be said about open models in the era of agents is that they get out of the debate of integration, harnesses, and tools and let us see close to the ground on what exactly is the ability of just a model. Of course, we can’t test some things like search abilities without some tool, but being able to measure exactly the pace of progress of the model alone is a welcome simplification to a systematically opaque AI space. Share The list of factors I’d use to assess a new open-weight model I’m considering investing in includes: Model performance (and size) — how this model performs on benchmarks I care about and how it compares to other models of a similar size. Country of origin — some businesses care deeply about provenance, and if a model was built in China or not. Model license — if a model needs legal approval for use, uptake will be slower at mid-sized and large companies. Tooling at release — many models release with half-broken, or at least substantially slower, implementations in popular software like vLLM, Transformers, SGLANG, etc due to pushing the envelope of architectures or tools. Model fine-tunability — how easy or hard it is to modify the given model to your use-case when you actually try and use it. The core problem is that some of these are immediately available at release, e.g. general performance, license, origin, etc. but others such as tooling take day(s) to week(s) to stabilize, and others are open research questions — with no group systematically monitoring fine-tunability. In the early era of open models, the days of Llama 2 or 3 and Qwen pre v3.5, the architectures were fairly simple and the models tended to work out of the box. Some of this was due to the extremely hard work of the Llama, Qwen, Mistral, etc. developer teams. Some is due to the new models being genuinely harder to work with. When it comes to something like Qwen 3.5 or Nemotron 3, with hybrid models (either gated delta net or mamba layers), the tooling is very rough at release. Things you would expect to “just work” often don’t. I’ve been following this area closely since we released Olmo Hybrid with a similar architecture, and Qwen 3.5 is just starting to work well in the various open-source tools that need to all play nice together for RL research. That’s 1.5 months after the release date! This is just to start really investing more into understanding the behavior of the models. Of course, others started working on these models sooner by investing more engineering resources or relying on partially closed software. The fully open and distributed ecosystem takes a long time to get going on some new models. All of this is lead-in for the most important question for open models — how easy is it to adapt to specific use-cases? This is a different problem for different model sizes. Large MoE open-weight models may be used by entities like Cursor who need complex capabilities in their domain, e.g. Composer 2 trained on Kimi K2.5. Other applications can be built on much smaller models, such as Chroma’s Context-1 model for agentic search, built on GPT-OSS 20B. The question of “which models are fine-tunable” is largely background knowledge known by engineers across the industry. There should be a thriving research area here to support the open ecosystem model. The first step is to understand characteristics of different base and post-trained models to understand what they look like. The second step is to tune pretraining recipes for open models so they’re more flexible. Interconnects AI is a reader-supported publication. Consider becoming a subscriber. Subscribe For The ATOM Project and other Interconnects endeavors, we’ve put in substantial effort to measuring adoption trends in the open ecosystem. Everything takes a long time to unfold after a model is first publicly available — and adaptability is why. What we know for sure now, when Qwen has been going from strength to strength with its releases, is that technical staff across the industry has gotten comfortable working with Qwen models. Countless research methods and datasets were made to work with Qwen. It’ll take patience for any other model family to get to this point — a patience I’m not sure many open model builders have. This takes us to Gemma 4, Google’s latest open models. Gemma 3 was released more than a year ago, in March of 2025, and is a bit underrated. Gemma 4 comes in 4 sizes for now, with a bigger, MoE model of over 100B total parameters rumored but not released yet. The models we have today come in sizes of ~5B dense, 8B dense, 26B total 4B active MoE, and 31B dense. I’m most excited that they’re finally adopting a standard Apache 2.0 open source license. This’ll massively boost adoption. The standard of better licenses for strong open-weight LLMs was set by mostly Chinese open model labs in the last 1-2 years, and now U.S. companies are following suit. I will personally be so happy if the horrible Llama licenses and Gemma terms of service were an ~18-month transient dynamic of the industry being nervous about releasing strong open models. The Gemma 4 scores look very solid, the small models have incredible benchmark scores (especially in general domains like LMArena) and the 31B model rivals the recent Qwen 3.5 27B, which is the leading member of that class. The ~30B size range is an important one, as it’s accessible both to researchers and to enterprises looking to deploy the model in real use-cases. Where the 7B model scale is the default for tinkering and research, a 30B model is the default for seeing if an open model can unlock substantial value in your specific workflow — a good mix of intelligence, low price, tractability for downstream training, etc. This takes us back to the above adoption criteria I mentioned for open models and the bigger question — do I think Gemma 4 will be an overwhelming success? Previous Gemma models have been plagued by tooling issues and poorer performance when being finetuned. Gemma 4’s success is going to be entirely determined by ease of use, to a point where a 5-10% swing on benchmarks wouldn’t matter at all. It’s strong enough, small enough, with the right license, and from the U.S., so many companies are going to slot it in. I’m cautiously optimistic that Gemma 4 is going to work better here. Winds are shifting for open models built in America. We saw GPT-OSS go through a bumpy launch to become an overwhelming success. There’s a collective energy around the likes of Reflection, Arcee, Nemotron, Gemma, Olmo, and peers that show substantial demand for building new stacks around open models. There’s capital to be spent on AI stacks across the economy by those who want more ownership of everything, including the model. After launching The ATOM Project 240 days ago, the conversation is shifting into the next stage. Summer of 2025 was a crisis moment where the U.S. AI scene realized it can’t wait and figure out open models after building AGI. The two markets will capture different areas and proceed in parallel. Now that more companies in the U.S. are releasing strong models, we need to improve the ecosystem so that these models are easy to use, understand, and build value around. It’s the hard work to build another inflection point in these adoption plots I’ve been updating consistently, but that’s the work to be done. Join me in it. More data coming soon! Here’s a sneak peek:
Assistant Beamline Scientist Grace Luo is facilitating next-generation science at the Advanced Photon Source
At Argonne’s Advanced Photon Source (APS), Grace Luo helps scientists understand atomic‑scale dynamics in functional devices to discover ways of creating more robust and efficient technologies.
Author Mary Roach to speak on weird science, human anatomy at Lawrence event
Mary Roach, a popular science writer with a funny bone, will talk in Lawrence about her new book on weird science and human anatomy, as part of a public library reading series.
Fallout 76 | Fallout 76: Rip Daring vs Aliens C.A.M.P. Showdown
Submit a Rip Daring–inspired or Alien–inspired C.A.M.P. or Shelter for a chance at Atoms and an exclusive C.A.M.P. title. Submissions run April 2–April 27 at 12PM ET.
A new way to detect breakthroughs in science: Large-scale analysis reveals 'disruptive' innovations in research history
The history of science and technology is marked by major breakthroughs—the theory of evolution, the splitting of the atom, the development of antibiotics—and a research team including faculty at Binghamton ...
Just 10,000 quantum bits might crack internet encryption schemes
Quantum computers based on atoms could provide access to encrypted data much sooner than scientists thought.
Eureka! Scientists develop new way to detect breakthroughs in science
The history of science and technology is marked by major breakthroughs — the theory of evolution, the splitting of the atom, the development of antibiotics — and a research team including faculty at Binghamton University, State University of New York, has developed a method to help pinpoint discoveries that reshaped the course of science. A study publishing in Science Advances on April 1 maps the landscape of innovation to identify disruptive studies and patents that challenge existing paradigms and inspire waves of follow-up research. The measure was developed by a team including Sadamori Kojaku, assistant professor of systems science and industrial engineering at Binghamton University, along with his colleagues Munjung Kim and Yong-Yeol Ahn at the University of Virginia.
Airbnb Externship Shows 3L Isabel Samayoa How Legal Strategy Drives Business Growth - UC Law San Francisco (Formerly UC Hastings)
An externship at Airbnb provided 3L Isabel Samayoa exposure to areas such as contracts, licensing, risk management, and growth strategy, helping her develop the skills and experience to thrive in her future career as a corporate transactions attorney. 3L student Isabel Samayoa reflects on her work with Airbnb’s in-house legal team through UC Law SF’s Corporate Counsel Externship Program. Supported Airbnb’s legal team on commercial contracts, open-source licensing, external partnerships, product counseling, and legal research. Observed how legal advice aligns with business strategy and risk management. Gained exposure to strategic decision-making while preparing for a career in corporate transactions. Q: What did you do in this corporate externship? A: I supported the Airbnb legal team across several functions, including commercial contracts, open-source licensing matters, strategic external partnerships, legal research, real estate matters, internal AI integration, and product counseling. I also gained exposure to corporate structure counseling, litigation, patent counseling, and the company’s broader business strategy. Q: What did you take away from this experience? A: One of the most valuable parts of this experience was learning how a business actually operates. I had never worked on such a large team in the private sector, so I had little exposure to how companies run internally. I learned how lawyers can provide valuable advice to support business goals, seeing how leadership evaluates risk and develops growth strategies. Understanding those priorities allows me to calibrate my legal advice to clients, balancing the client’s goals against the level of risk they are willing to take. Q: How does this experience support your career goals? A: Exploring the anatomy of a successful company was incredibly valuable because I plan to pursue a career as a corporate transactions lawyer. Being in the room with the teams discussing important decisions allowed me to see firsthand the factors that contribute to that success and how lawyers help guide those decisions. Q: Would you recommend UC Law SF and this externship? Why? A: I would absolutely recommend this opportunity. While the team worked on high-stakes matters at a highly successful company, they still created an environment where I felt welcomed. They trusted me with meaningful work and supported me every step of the way. This helped me build confidence in my analytical abilities. Q: What’s your favorite UC Law SF memory so far? A: Some of my favorite UC Law SF memories, aside from my time at Airbnb, involve mentorship. I have benefited from mentorship and have also had the chance to mentor other law students. Watching the students I mentored go on to mentor others has been particularly rewarding. I think mentorship is integral to the legal profession, and it has been inspiring to see that culture thrive at UC Law SF and continue beyond the classroom. The Evidence of Success series highlights UC Law SF students as they share how the College’s opportunities equip them with the experience, skills, and confidence to excel in the legal profession.
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