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In a physics first, a team including scientists from the National Institute of Standards and Technology (NIST) has created a way to make beams of neutrons travel in curves. These Airy beams (named for English scientist George Airy), which the team created using a custom-built device, could enhance neutrons’ ability to reveal useful information about materials ranging from pharmaceuticals to perfumes to pesticides—in part because the beams can bend around obstacles.

“We’ve known about these strange, self-steering wave patterns for a while, but until now, no one had ever made them with neutrons,” said NIST’s Michael Huber, one of the paper’s authors. “This opens up a whole new way to control neutron beams, which could help us see inside materials or explore some big questions in physics.”

A paper announcing the findings appears in Physical Review Letters.

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Northwestern Medicine investigators have discovered how disruptions in the circadian rhythm in our muscles combined with poor diet can contribute to the development of diabetes, according to a recent study published in Proceedings of the National Academy of Sciences.

“When we mess up our through environmental circadian disruption like , jet lag or , it’s possible that it’s impacting our muscle clocks and metabolism. If that’s happening and we are combining this with an unhealthy diet, this might make it more likely for us to develop glucose intolerance and diabetes,” said Clara Peek, Ph.D., assistant professor of Biochemistry and Molecular Genetics and of Medicine in the Division of Endocrinology, Metabolism and Molecular Medicine, who was senior author of the study.

The body’s natural is comprised of proteins called that are present throughout the body, including . The clock synchronizes physical and behavioral changes to the external environment during the 24-hour light cycle.

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Knots are generally understood to form due to twists and turns of long, flexible materials that keep shoes on your feet or frustrate your attempts at hanging holiday decorations. A beam of light doesn’t sound like a material that can create a knot.

But it is.

Imagine throwing several rocks into a pond all at once. At a certain point on the water’s surface, the resulting ripple rings would all mix to form a complex pattern. Now imagine being able to control the shape and speed of each ring. With enough planning, you could get that mesh point to form in 3D on demand.

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A research team from the Ningbo Institute of Materials Technology and Engineering (NIMTE) of the Chinese Academy of Sciences (CAS) has proposed a hybrid transfer and epitaxy strategy, enabling the heterogeneous integration of single-crystal oxide spin Hall materials on silicon substrates for high-performance oxide-based spintronic devices.

The study is published in Advanced Functional Materials.

Spintronic devices are gaining attention as a key direction for next-generation information technologies due to their , non-volatility, and ultra-fast operating capabilities.

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In a recent study, researchers made a significant observation of the Berezinskii-Kosterlitz-Thouless (BKT) phase transition in a 2D dipolar gas of ultracold atoms. This work marks a milestone in understanding how 2D superfluids behave with long-range and anisotropic dipolar interactions. The researchers are an international team of physicists, led by Prof. Jo Gyu-Boong from the Department of Physics at the Hong Kong University of Science and Technology (HKUST).

Their findings are published in the journal Science Advances.

In conventional three-dimensional (3D) systems, , such as ice melting into water, are governed by the spontaneous breakdown of symmetries. However, pioneering work in the 1970s predicted that two-dimensional (2D) systems could host a unique topological phase transition known as the BKT transition, where vortex-antivortex pairs drive superfluidity without conventional symmetry breaking, with interaction playing a crucial role. Since then, this phenomenon had primarily been studied in various quantum systems with only short-range isotropic contact interactions.

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Laser-plasma accelerators can accelerate particles over distances that are up to 1,000 times shorter than those required by conventional accelerators. The technology promises compact systems that have enormous potential to open up new applications for accelerators, for example in medicine or industry. However, the current prototypes have one drawback: most can only accelerate a few particle bunches per second—not enough for practical applications.

DESY’s new flagship laser, KALDERA, has now made a decisive step forward: Driving the compact accelerator MAGMA, the innovative laser has been shown to accelerate 100 particle bunches per second. This increased repetition rate opens the path to actively stabilize the plasma accelerator performance in the future, which will bring it a good deal closer to first applications.

In conventional accelerators, radio-frequency waves are fed into so-called resonators. These waves can give a push to particles passing through them—in most cases electrons—and transfer energy to them. In order to raise the particles to high energy levels, numerous resonators have to be connected in series. This makes the systems long and expensive.

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Scientists at EPFL have made a breakthrough in designing arrays of resonators, the basic components that power quantum technologies. This innovation could create smaller, more precise quantum devices.

Qubits, or , are mostly known for their role in , but they are also used in analog quantum simulation, which uses one well-controlled quantum system to simulate another more complex one. An analog quantum simulator can be more efficient than a digital computer simulation, in the same way that it is simpler to use a to simulate the laws of aerodynamics instead of solving many complicated equations to predict airflow.

Key to both digital quantum computing and analog quantum simulation is the ability to shape the environment with which the qubits are interacting. One tool for doing this effectively is a coupled array (CCA), made of multiple microwave cavities arranged in a repeating pattern where each cavity can interact with its neighbors. These systems can give scientists new ways to design and control quantum systems.

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Researchers at the European XFEL have developed a new device for X-ray measurements at high photon energies—a so-called Laue spectrometer. It enables X-ray light with photon energies of more than 15 kiloelectronvolts to be detected with improved efficiency and highest precision.

This is important for researching technically significant materials that, for example, transport electricity without losses or ensure that chemical processes run more efficiently. The findings are published in the Journal of Synchrotron Radiation.

To unravel the secrets of the world of atoms, molecules and materials in general, scientists often use special measurement devices known as spectrometers. They work by recording the light that objects emit. From the way in which the objects do that, researchers learn a lot about the physical processes that take place in the materials.

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In this episode, renowned AI researcher Pedro Domingos, author of The Master Algorithm, takes us deep into the world of Connectionism—the AI tribe behind neural networks and the deep learning revolution.

From the birth of neural networks in the 1940s to the explosive rise of transformers and ChatGPT, Pedro unpacks the history, breakthroughs, and limitations of connectionist AI. Along the way, he explores how supervised learning continues to quietly power today’s most impressive AI systems—and why reinforcement learning and unsupervised learning are still lagging behind.

We also dive into:
The tribal war between Connectionists and Symbolists.
The surprising origins of Backpropagation.
How transformers redefined machine translation.
Why GANs and generative models exploded (and then faded)
The myth of modern reinforcement learning (DeepSeek, RLHF, etc.)
The danger of AI research narrowing too soon around one dominant approach.

Whether you’re an AI enthusiast, a machine learning practitioner, or just curious about where intelligence is headed, this episode offers a rare deep dive into the ideological foundations of AI—and what’s coming next.

Continue reading “How Connectionism Is Reshaping the Future of Machine Learning | Pedro Domingos” | >