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Elon Musk backed Nvidia CEO Jensen Huang after affair admission

Musk stands by jensen huang after affair admission.

Nvidia CEO Jensen Huang has admitted to an affair, and Elon Musk is publicly backing him. The show of support from one of tech’s loudest voices is already stirring debate about how Silicon Valley judges its biggest names. Here’s what was said.

Democrats responded angrily to the news, the AP reported. Sen. Elizabeth Warren, a Massachusetts Democrat, said in a statement on Nov. 9 that Nvidia had reportedly received approvals to export “hundreds of thousands of advanced AI chips to China.” She said Huang’s relationship with Alice Huang “raises important questions NVIDIA must answer.” The AP also reported bipartisan calls for congressional investigations and a Justice Department probe.

Dan Ives, a partner at Yorkville & Ives Co., called the news “a black eye moment for Jensen,” according to CNN. George Chen, a partner at The Asia Group, wrote in a note that it would not serve the interests of Nvidia shareholders and industry partners if Huang quit suddenly.

More on this story: Trump said he believes Nvidia CEO Jensen Huang as Democrats vow inquiries.

New method maps DNA folding and epigenetic marks in single cells

A new experimental procedure developed by researchers at Yale School of Medicine could help scientists better understand how DNA structure influences disease and development.

DNA underpins nearly all cellular functions. Which genes a cell uses depends on the structure of DNA in the nucleus—shaped by both DNA’s three-dimensional (3D) folding and the chemical modifications to DNA and its associated proteins called epigenetic marks.

Understanding the relationship between the 3D genome and epigenetics has implications for DNA function and disease. However, most methods struggle to combine these two factors.

Ultrasound and AI turn off-the-shelf smartwatch into full-body tracker without cameras

For the first time, researchers can track the movement of a person’s entire body with ultrasonic sound waves, using just an off-the-shelf smartwatch and a lightweight artificial intelligence model—all while ensuring privacy and efficiency.

The new technology, called EchoMotion, was developed by Cornell’s Smart Computer Interfaces for Future Interactions (SciFi) Lab, directed by Cheng Zhang, associate professor of information science in the Cornell Ann S. Bowers College of Computing and Information Science. It uses the built-in speaker and microphone on a commercial smartwatch to determine a person’s body position using a sonar-like sensing system. Once EchoMotion is integrated into commercial wearables or virtual reality (VR) systems, it could be used for tracking workouts, daily activities and progress on physical rehabilitation.

EchoMotion represents a scalable approach that can use AI to understand human behaviors in the real world, Zhang said.

Engineers challenge 90-year limitation in digital audio sensing

What does a faint heartbeat have in common with a thunderous concert? Both present a challenge for digital technology: capturing the quietest details without losing the loudest sounds.

For nearly 90 years, engineers have managed this trade-off by balancing the loudness of sound a device can capture against the number of bits used to represent it.

Now, researchers at Imperial College London have demonstrated a radically different approach called USF-Audio. Rather than allowing loud signals to be clipped, their system deliberately folds them into a smaller range before digitization. Although the resulting waveform can look or sound scrambled, its mathematical structure allows the original sound to be reconstructed.

3D-printed robotic frog swims using six artificial muscles powered by light

A small robotic frog developed at Aarhus University can swim using six artificial muscles activated by light. Behind the achievement is a systematic approach that could help researchers develop muscles for the next generation of soft robots.

It has no motor, batteries or wires. Yet a small frog created using a 3D printer by Ph.D. student Cecilie Ryberg from the Department of Chemistry at Aarhus University can swim across the water’s surface.

It is not particularly fast. In laboratory experiments, it traveled 8 centimeters (3.1 inches) in almost two minutes. But what makes the frog interesting is how it moves.

Chip identifies cells by their electrical signature, then separates them with a precisely aimed sound wave

In biomedicine, sorting cells accurately without damaging them remains a persistent problem. Current methods, like fluorescence-activated cell sorting, rely on labeling the cells extrinsically, which can stress the cells, alter their behavior and even interfere with the assay. A collaborative study between researchers in Singapore and China has now developed a noninvasive, label-free method to sort cells.

“The cell-sorting platform is an integrated system that requires pre-focusing, cell sensing, and single-cell-level manipulation,” said associate professor Ye AI from Singapore University of Technology and Design, who co-led the study, “Label-free impedance-activated acoustic sorting of cells from structural to molecular scale in microfluidics,” published in Small Methods.

New algorithm improves phase readout for space-based gravitational wave detection

In a study published in Optics Communications, a research group led by Yu Tao from the Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP) of the Chinese Academy of Sciences proposed a new analytical phase readout algorithm for deep frequency modulation interferometry (DFMI).

The method improves phase measurement accuracy and simplifies signal processing by eliminating the need to explicitly estimate modulation parameters. This offers a promising approach for developing compact interferometric measurement systems for space gravitational wave detection.

Space-based gravitational wave detection requires precise measurements of tiny changes in the distances between freely falling test masses. Laser interferometry provides a powerful means of detecting these minute displacements by measuring variations in optical phase. However, conventional interferometric systems often require complex optical arrangements and electronic components, creating challenges for spacecraft applications.

A standard shortcut, used since the 1970s, hides a magneto-optic effect in ordinary glass fiber

For more than 50 years, engineers have described light in optical fiber using a convenient shortcut, one that works so well it is rarely questioned. Engineers at the University of the Witwatersrand (Wits University) in Johannesburg, South Africa, have now shown that this shortcut hides a small but real effect. A magnet placed beside a multimode fiber, rather than along it, can change the light traveling inside.

Optical fibers are best known for carrying the light signals that connect us to the internet. These hair-thin strands of glass can also act as sensors, and for decades engineers have used them to measure magnetic fields, including those produced by the electrical currents in power lines and substations.

Such sensors rely on the so-called Faraday effect, first observed by Michael Faraday in a block of glass in 1845. When a magnetic field points along a fiber, it slightly twists the polarization of the light traveling through it. Polarization is the direction in which the light wave oscillates, much as a rope can be shaken up and down or side to side. Measuring the twist reveals the strength of the magnetic field, and therefore the strength of the current that produced it.

Superconducting vortices provide experimental evidence that clogging is a phase transition

Clogging is a phenomenon in which moving particles get stuck, slowing or blocking the flow, but how this transition occurs has remained experimentally unproven. Researchers from Science Tokyo studied superconducting vortices to demonstrate that clogging is a nonequilibrium phase transition. Using a two-step measurement protocol, they distinguished clogging from conventional pinning and revealed that both transitions share a critical point, offering new insights into predicting and controlling clogging across diverse systems.

Clogging is a common phenomenon where flowing particles encounter bottlenecks that restrict their passage, slowing down or completely halting movement. This phenomenon is observed across a wide range of systems, including granular materials, filtration devices, industrial pipelines and biological transport networks. Understanding how and why clogging occurs is essential for preventing blockages and maintaining efficient transport across natural and engineered systems.

Despite its widespread incidence, the physical mechanisms governing the transition from continuous flow to complete clogging remain incompletely understood. Previous studies predicted that this transition represents a nonequilibrium phase transition, in which the time required to reach a stable flowing or completely blocked state diverges near a critical point. However, experimental confirmation of this prediction remained lacking.

III-nitride device integrates sensing and memory for in-sensor computing

A new study published in Nature Materials reports that researchers have developed an aluminum gallium nitride device that combines light detection, memory and basic processing by controlling charge at polarization interfaces. The device can detect light at the nanowatt-per-square-centimeter level and operate stably at temperatures up to 300°C.

The study was led by researchers from the Changchun Institute of Optics, Fine Mechanics and Physics of the Chinese Academy of Sciences (CAS), Peking University, East China Normal University, the Shanghai Institute of Technical Physics of CAS and Zhejiang University.

In-sensor computing reduces the need to transfer raw data between separate detectors, memory units and processors. Existing devices often rely on defects to store charge, which can consume photogenerated carriers and weaken the response. Other approaches use stacked two-dimensional materials that remain difficult to manufacture over large areas. Group III nitride semiconductors offer an alternative because their material quality, fabrication processes and industrial supply chain are well established.