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Tech & Engineering

Updates every hour. Last Updated: 10-Jun-2026 04:16 ET (10-Jun-2026 08:16 GMT/UTC)

Most AI bots lack basic safety disclosures, study finds

University of Cambridge
Reports and Proceedings

The AI Agent Index investigates 30 top AI bots and finds just four have published formal safety and evaluation documents relating to the actual agents. The new wave of AI web browser agents, many designed to mimic human browsing, have the highest rates of missing safety information.

Biochar nanomaterials could transform medicine, energy, and climate solutions

Biochar Editorial Office, Shenyang Agricultural University
Peer-Reviewed Publication

A new scientific review highlights how emerging biochar-based nanomaterials could play a powerful role in tackling global challenges ranging from climate change to healthcare innovation. Researchers report that nanobiochar and biochar nanocomposites, advanced forms of carbon-rich materials derived from biomass, are showing promise across fields including renewable energy storage, sustainable construction, agriculture, and even medicine.

Journal: Biochar

Exposing biases, moods, personalities, and abstract concepts hidden in LLMs

Massachusetts Institute of Technology
Peer-Reviewed Publication

A new method can test whether a large language model contains hidden biases, personalities, moods, or other abstract concepts. MIT researchers can zero in on connections within a model that encode for a concept of interest, to improve LLM safety and performance.

Journal: Science
Funder: National Science Foundation, Simons Foundation, TILOS institute, U.S. Office of Naval Research

Idaho National Laboratory to accelerate nuclear energy deployment with NVIDIA AI through the Genesis Mission

DOE/Idaho National Laboratory
Business Announcement

Prometheus Grand Challenge aims to deploy commercial-scale nuclear reactors in years, not decades.

IDAHO FALLS, Idaho —The Idaho National Laboratory and NVIDIA have partnered to advance nuclear energy deployment through artificial intelligence. The collaboration aims to accelerate advanced nuclear reactor deployment and reduce costs.

Social pressure forces baby clownfish to lose their bars faster

Okinawa Institute of Science and Technology (OIST) Graduate University
Peer-Reviewed Publication

Growing up, you probably changed your style based on your social influences. It turns out, such pressures affect the appearance of young clownfish (anemonefish) too. A new study from the Okinawa Institute of Science and Technology (OIST) has revealed the social influences and biological mechanisms controlling bar loss in tomato anemonefish, showing how the presence of older fish changes the speed at which young fish lose their additional white vertical stripe.

Journal: PLOS Biology

“Cyborg” pancreatic organoids can monitor the maturation of islet cells

American Association for the Advancement of Science (AAAS)
Peer-Reviewed Publication

Qiang Li and colleagues have created “cyborg” pancreatic organoids that combine stretchy miniature electronics with stem cell-derived pancreatic islets, using the implanted electronics to monitor electrical activity related to glucose regulation in maturing α and β cells. Islet α and β cells secrete glucagon and insulin hormones, in response to electrical changes in the cell membrane. The researchers also used the electronics to stimulate the cells to enhance their glucose responsiveness and show how that responsiveness changes as the cells mature, how it is affected by different chemical compounds and circadian hormones, and how it is related to gene expression. Together, the cyborg organoids offer a path to study the biology and trace the maturation of α and β cells at the single-cell level, with an eye toward potentially treating or engineering new pancreatic islets in people with diabetes. In a related Perspective, Jochen Lang and Matthieu Raoux discuss how the cyborgs could be used to guide the growth of mature human pancreatic organoids for regenerative medicine and other applications.

Journal: Science

Technique to extract concepts from AI models can help steer and monitor model outputs

American Association for the Advancement of Science (AAAS)
Peer-Reviewed Publication

AI models have their own internal representations of knowledge or concepts that are often difficult to discern, even as they are critical to the models’ output. For instance, knowing more about a model’s representation of a concept would help explain why an AI model might “hallucinate” information, or why certain prompts can trick it into responses that dodge its built-in safeguards. Daniel Beaglehole and colleagues now introduce a robust method to extract these representations of concepts, which works across several large-scale language, reasoning, and vision AI models. Their technique uses a feature extraction algorithm called the Recursive Feature Machine. By extracting concept representations with this technique, Beaglehole et al. were able to monitor these models in ways that exposed some of their vulnerabilities to behaviors like hallucinations and to steer them toward improved output responses. Surprisingly, the concept representations were transferable between different languages and could be combined with other concept representations for multi-concept steering, the researchers noted. “Together, these results suggest that the models know more than they express in responses and that understanding internal representations could lead to fundamental performance and safety improvements,” the authors write.

Journal: Science

MULTI-evolve: Rapid evolution of complex multi-mutant proteins

Arc Institute
Peer-Reviewed Publication

Researchers at Arc Institute developed MULTI-evolve, an AI-guided framework that compresses protein engineering from months of iterative experimentation into weeks using as few as 200 strategic lab measurements. By training neural networks on pairwise combinations of beneficial mutations, the approach learns the rules of how mutations interact and accurately predicts complex multi-mutant proteins, achieving up to 256-fold activity improvements in a single experimental round. Published in Science, the framework and open-source tools are applicable to enzymes, genome editors, and therapeutic proteins.

Journal: Science

A new method to steer AI output uncovers vulnerabilities and potential improvements

University of California - San Diego
Peer-Reviewed Publication

A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, and less computationally expensive training of LLMs. But it also exposes potential vulnerabilities. The researchers present their findings in the Feb. 19, 2026, issue of the journal Science.

Journal: Science
Funder: Office of Naval Research, Simons Foundation