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Sam Altman’s worst-case AI scenario may already be here

Sam Altman, CEO of OpenAI, appeared at a Federal Reserve event on July 22 and outlined three “scary categories” of how advanced artificial intelligence could threaten society.

The first two scenarios — a bad actor using artificial intelligence for malfeasance and a rogue AI taking over the world — were accompanied by the insistence that people were working to prevent them. However, Mr. Altman offered no such comfort with the third scenario, the one that seemed to trouble him most.

He described a future where AI systems become “so ingrained in society … [that we] can’t really understand what they’re doing, but we do kind of have to rely on them. And even without a drop of malevolence from anyone, society can just veer off in a sort of strange direction.”

The first experimental realization of quantum optical skyrmions in a semiconductor QED system

Skyrmions are localized, particle-like excitations in materials that retain their structure due to topological constraints (i.e., restrictions arising from properties that remain unchanged under smooth deformations). These quasiparticles, first introduced in high-energy physics and quantum field theory, have since attracted intense interest in condensed matter physics and photonics, owing to their potential as robust carriers for information storage and manipulation.

Researchers at Sun Yat-sen University and Tianjin University recently reported the first experimental realization of single-photon quantum skyrmions (i.e., localized light structures) in a semiconductor cavity quantum electrodynamics (QED) system. Their paper, published in Nature Physics, could open new possibilities for the study of quantum light-matter interactions, while also contributing to the advancement of photonic quantum devices.

“Our work was motivated by the longstanding challenge of realizing topological photonic structures—specifically skyrmions—at the quantum level,” Ying Yu, co-senior author of the paper, told Phys.org.

Using sound to remember quantum information 30 times longer

While conventional computers store information in the form of bits, fundamental pieces of logic that take a value of either 0 or 1, quantum computers are based on qubits. These can have a state that is simultaneously both 0 and 1. This odd property, a quirk of quantum physics known as superposition, lies at the heart of quantum computing’s promise to ultimately solve problems that are intractable for classical computers.

Many existing quantum computers are based on superconducting electronic systems in which electrons flow without resistance at extremely low temperatures. In these systems, the quantum mechanical nature of electrons flowing through carefully designed resonators creates superconducting qubits.

These qubits are excellent at quickly performing the logical operations needed for computing. However, storing information—in this case quantum states, mathematical descriptors of particular quantum systems—is not their strong suit. Quantum engineers have been seeking a way to boost the storage times of quantum states by constructing so-called “quantum memories” for superconducting qubits.

The shape of the universe revealed through algebraic geometry

How can the behavior of elementary particles and the structure of the entire universe be described using the same mathematical concepts? This question is at the heart of recent work by the mathematicians Claudia Fevola from Inria Saclay and Anna-Laura Sattelberger from the Max Planck Institute for Mathematics in the Sciences, recently published in the Notices of the American Mathematical Society.

Mathematics and physics share a close, reciprocal relationship. Mathematics offers the language and tools to describe physical phenomena, while physics drives the development of new mathematical ideas. This interplay remains vital in areas such as and cosmology, where advanced mathematical structures and physical theory evolve together.

In their article, the authors explore how algebraic structures and geometric shapes can help us understand phenomena ranging from particle collisions such as happens, for instance, in particle accelerators to the large-scale architecture of the cosmos. Their research is centered around . Their recent undertakings also connect to a field called positive geometry—an interdisciplinary and novel subject in mathematics driven by new ideas in and cosmology.

Going places: Muscle-inspired mechanism powers tiny autonomous insect robots

Science frequently draws inspiration from the natural world. After all, nature has had billions of years to perfect its systems and processes. Taking their cue from mollusk catch muscles, researchers have developed a low-voltage, muscle-like actuator that can help insect-scale soft robots to crawl, swim and jump autonomously in real-world settings. Their work solves a long-standing challenge in soft robotics: enabling tiny robots to move on their own without sacrificing power or precision.

Muscles are that work by contracting and relaxing to cause movement. Insect muscles are particularly good at this because they are incredibly powerful for their small size. Similarly, actuators are devices that convert mechanical energy into motion.

However, when it comes to robotics, creating tiny, powerful actuators that move with the same agility, precision and resilience as a biological has proved challenging. What’s more, the rigid motors in current robotic systems are difficult to scale down because they easily break.

Don’t throw away those cannabis leaves—they’re packed with rare compounds

Analytical chemists from Stellenbosch University (SU) have provided the first evidence of a rare class of phenolics, called flavoalkaloids, in cannabis leaves.

Phenolic compounds, especially flavonoids, are well-known and sought after in the because of their antioxidant, anti-inflammatory, and anti-carcinogenic properties.

The researchers identified 79 in three strains of cannabis grown commercially in South Africa, of which 25 were reported for the first time in cannabis. Sixteen of these compounds were tentatively identified as flavoalkaloids. Interestingly, the flavoalkaloids were mainly found in the leaves of only one of the strains. The results were published in the Journal of Chromatography A recently.

Customized moiré patterns achieved using stacked metal-organic framework layers

When two mesh screens or fabrics are overlapped with a slight offset, moiré patterns emerge as a result of interference caused by the misalignment of the grids. While these patterns are commonly recognized as optical illusions in everyday life, their significance extends to the nanoscale, such as in materials like graphene, where they can profoundly influence electronic properties.

This phenomenon opens new avenues for advancements in areas like superconductivity and quantum effects. Traditionally, controlling the length scales of moiré patterns has been challenging due to the fixed nature of atomic structures, which limits the ability to fine-tune .

A research team, led by Professor Wonyoung Choe at Ulsan National Institute of Science and Technology (UNIST), South Korea, has demonstrated, for the first time, the ability to precisely control over moiré periods by stacking (MOFs) layers—crystalline materials composed of metal clusters linked by .

Bioelectrosynthesis platform enables switch-like, precision control of cell signaling

Cells use various signaling molecules to regulate the nervous, immune, and vascular systems. Among these, nitric oxide (NO) and ammonia (NH₃) play important roles, but their chemical instability and gaseous nature make them difficult to generate or control externally.

A KAIST research team has developed a platform that generates specific signaling molecules in situ from a single precursor under an applied electrical signal, enabling switch-like, precise spatiotemporal control of cellular responses. This approach could provide a foundation for future medical technologies such as electroceuticals, electrogenetics, and personalized cell therapies.

The research team led by Professor Jimin Park from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Jihan Kim’s group, has developed a bioelectrosynthesis platform capable of producing either or on demand using only an electrical signal. The platform allows control over the timing, spatial range, and duration of cell responses.

Quasi-solid electrolyte developed for safer and greener lithium-ion batteries

3D-SLISE is a quasi-solid electrolyte developed at the Institute of Science Tokyo, which enables safe, fast-charging/discharging of 2.35 V lithium-ion batteries to be fabricated under ambient conditions. With energy-efficient manufacturing using raw materials free from flammable organic solvents, the technique eliminates the need for dry rooms or high-temperature processing. Moreover, it also allows direct recovery of active materials through water dispersal—ensuring a sustainable, recyclable approach to battery production.

In today’s era of portable power and , form the backbone of modern technology—powering everything from smartphones to electric vehicles. While demand for lithium-ion batteries continues to grow, so do concerns about their safety, environmental impact, and recyclability. Most lithium-ion batteries that rely on flammable organic solvents are energy-intensive to manufacture, and require complicated recycling processes. These issues not only drive up costs but also pose serious safety and —highlighting the need for safer and cleaner alternatives.

To address this challenge, a research team from Institute of Science Tokyo (Science Tokyo), Japan, led by Specially Appointed Professor Yosuke Shiratori and Associate Professor Shintaro Yasui from the Zero-Carbon Energy Research Institute, Science Tokyo, developed a new quasi-solid electrolyte called 3D-Slime Interface Quasi-Solid Electrolyte (3D-SLISE), which can transform battery manufacturing. With a simple borate-water matrix, the electrolyte supports the production of 2.35 V lithium-ion batteries under standard air conditions. The detailed findings of the study were made available in the journal Advanced Materials on July 9, 2025.

Finding clarity in the noise: New approach recovers hidden signals at the nanoscale

In the world of nanotechnology, seeing clearly isn’t easy. It’s even harder when you’re trying to understand how a material’s properties relate to its structure at the nanoscale. Tools like piezoresponse force microscopy (PFM) help scientists peer into the nanoscale functionality of materials, revealing how they respond to electric fields. But those signals are often buried in noise, especially in instances where the most interesting physics happens.

Now, researchers at Georgia Tech have developed a powerful new method to extract meaningful information from even the noisiest data, or when, alternatively, the response of the material is the smallest. Their approach, which combines physical modeling with advanced statistical reconstruction, could significantly improve the accuracy and confidence of nanoscale measurement properties.

The team’s findings, led by Nazanin Bassiri-Gharb, Harris Saunders, Jr. Chair and Professor in the George W. Woodruff School of Mechanical Engineering and School of Materials Science and Engineering (MSE), are reported in Small Methods.

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