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China’s New DuClaw AI Just Made OpenClaw Instant and Unstoppable

China just released DuClaw, a new platform that lets anyone run OpenClaw AI agents instantly from a web browser without dealing with deployment, servers, or API keys. At the same time, researchers at Stanford introduced OpenJarvis, a framework that allows personal AI assistants to run entirely on your own computer instead of the cloud. Meanwhile Google is using Gemini to build the largest flash flood dataset ever created, mapping millions of disaster events across the planet. And a new toolkit called gstack is turning AI coding into something far more autonomous, allowing AI systems to plan software, test applications, and review code automatically.

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🧠 What You’ll See.
Baidu launches DuClaw to run OpenClaw AI agents directly from a browser.
SOURCE: https://pandaily.com/baidu-ai-cloud-l… introduces OpenJarvis for fully local AI assistants SOURCE: https://www.marktechpost.com/2026/03/.… Google uses Gemini to build the largest flash flood dataset ever created SOURCE: https://www.wsj.com/articles/google-t… gstack toolkit organizes AI into automated software development workflows SOURCE: https://www.producthunt.com/products/.… 🚨 Why It Matters These developments show how quickly artificial intelligence is moving toward more autonomous systems. From browser based AI agents that run instantly, to personal assistants that operate entirely on local machines, the way people interact with AI is changing rapidly. At the same time, large scale AI systems are being used to analyze global disasters and predict floods, while new developer tools are allowing AI to plan, test, and review software almost like an engineering team. #ai #artificialintelligence #ainews.

Stanford introduces OpenJarvis for fully local AI assistants.
SOURCE: https://www.marktechpost.com/2026/03/.

Google uses Gemini to build the largest flash flood dataset ever created.
SOURCE: https://www.wsj.com/articles/google-t

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New chip lets robots see in 4D by tracking distance and speed simultaneously

Current vision systems for robots and drones rely on 3D sensors that, although powerful, do not always keep up with the fast-paced, unpredictable movement of the real world. These systems often struggle to measure speed instantly or are too bulky and expensive for everyday use. Now, in a paper published in the journal Nature, scientists report how they have developed a 4D imaging sensor on a chip that creates 3D maps of an environment while simultaneously tracking the speed of moving objects.

The researchers built a focal plane array (FPA), a physical grid of 61,952 stationary pixels etched onto a single silicon chip. Each one is a tiny sensor that emits laser light toward a scene and detects the reflected signal.

To “see” its surroundings, laser light from an external source is fed into the chip. This light is routed across the chip through a network of optical switches that sequentially direct it to groups of pixels. Each pixel then uses a technique called FMCW LiDAR to measure the returning signal, which is later processed to determine distance and speed. In many LiDAR systems, one set of pixels sends the light, and another receives it, but here, all pixels both send and receive, making the system much more compact.

How much do nontargeted analyses really see? A model maps chemical blind spots

In a study published in Analytical Chemistry, researchers from the University of Amsterdam’s Van ‘t Hoff Institute for Molecular Sciences (HIMS) reveal a sobering reality regarding nontargeted chemical analysis. Although widely used for screening the environment for chemicals, this concept isn’t nearly as broad as its name suggests, leaving massive blind spots in the data.

Cosmic microwave background

(CMB, CMBR), or relic radiation, is microwave radiation that fills all space in the observable universe. With a standard optical telescope, the background space between stars and galaxies is almost completely dark. However, a sufficiently sensitive radio telescope detects a faint background glow that is almost uniform and is not associated with any star, galaxy, or other object. This glow is strongest in the microwave region of the electromagnetic spectrum. Its energy density exceeds that of all the photons emitted by all the stars in the history of the universe. The accidental discovery of the CMB in 1964 by American radio astronomers Arno Allan Penzias and Robert Woodrow Wilson was the culmination of work initiated in the 1940s.

The CMB is the key experimental evidence of the Big Bang theory for the origin of the universe. In the Big Bang cosmological models, during the earliest periods, the universe was filled with an opaque fog of dense, hot plasma of sub-atomic particles. As the universe expanded, this plasma cooled to the point where protons and electrons combined to form neutral atoms of mostly hydrogen. Unlike the plasma, these atoms could not scatter thermal radiation by Thomson scattering, and so the universe became transparent. Known as the recombination epoch, this decoupling event released photons to travel freely through space. However, the photons have grown less energetic due to the cosmological redshift associated with the expansion of the universe. The surface of last scattering refers to a shell at the right distance in space so photons are now received that were originally emitted at the time of decoupling.

The CMB is very smooth and uniform, but maps by sensitive detectors detect small but important temperature variations. Ground and space-based experiments such as COBE, WMAP and Planck have been used to measure these temperature inhomogeneities. The anisotropy structure is influenced by various interactions of matter and photons up to the point of decoupling, which results in a characteristic pattern of tiny ripples that varies with angular scale. The distribution of the anisotropy across the sky has frequency components that can be represented by a power spectrum displaying a sequence of peaks and valleys. The peak values of this spectrum hold important information about the physical properties of the early universe: the first peak determines the overall curvature of the universe, while the second and third peak detail the density of normal matter and so-called dark matter, respectively.

Mass spectrometry imaging: principles and applications in plant research

A Research review by Sun et al. 👇

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Mass spectrometry imaging (MSI) is an advanced analytical technique that combines mass spectrometry with spatial mapping, enabling the direct, label-free detection and visualization of molecular distributions within biological tissues. This review comprehensively outlines the fundamental principles, major technological platforms, and recent applications of MSI in plant science. We detail key ionization techniques – matrix-assisted laser desorption/ionization (MALDI), desorption electrospray ionization (DESI), and secondary ion mass spectrometry (SIMS) – focusing on their ionization mechanisms and instrumental characteristics.

How AI could unlock deep-sea secrets of marine life

The reef is a home and feeding ground for dozens of species that depend on it the way a woodland creature depends on trees. It has survived ice ages – but whether it will survive increasing pressures from industrial fishing, deep-sea mining and climate change is, in part, a question about data. If we don’t know it exists, how can we protect it?

A new project called Deep Vision could fundamentally transform our understanding of the deep ocean by digging into pictures and videos sat largely unexamined in research archives around the world. By using AI, thousands of hours of seafloor footage can be analysed to produce the first comprehensive maps of vulnerable marine ecosystems across the entire Atlantic basin.

Over the past two decades, robotic and autonomous underwater vehicles have collected vast quantities of footage from the deep sea. This represents an extraordinary resource – a record of ecosystems that most humans will never see.

Electron microscopy maps protein landscapes that drive photosynthesis

Research led by scientists at Washington State University has revealed insights on how plants form a microscopic landscape of proteins crucial to photosynthesis, the basis of Earth’s food and energy chain. The discovery provides a new view of the molecular engine that converts sunlight into bioenergy and could enable future fine-tuning of crops for higher yields and other useful traits.

Colleagues at WSU, the University of Texas at Austin, and the Weizmann Institute of Science in Israel used a novel, technology-powered approach to peer inside plant leaf cells and visualize the landscape of the photosynthetic membrane—the ribbon-like structure where plants harvest sunlight. The findings were recently published in the journal Science Advances.

“These membranes are highly efficient biological solar cells,” said the study’s principal investigator and corresponding author, Helmut Kirchhoff. “They convert sunlight energy into chemical energy that fuels not only the plant’s metabolism but that of most life on Earth.”

Largest ever radio sky survey maps the universe in unprecedented detail

An international collaboration using the Low Frequency Array (LOFAR) has published an exceptionally detailed radio sky map, revealing 13.7 million cosmic sources and delivering the most complete census yet of actively growing supermassive black holes. It showcases an extraordinary variety of systems powered by these black holes, whose radio emission can extend for millions of light-years.

The newly released LOFAR Two-meter Sky Survey (LoTSS-DR3) marks a major milestone in radio astronomy and international scientific collaboration. The results will be published in Astronomy & Astrophysics.

By observing the sky at low radio frequencies, the survey reveals a dramatically different view of the universe than that seen at optical wavelengths. Much of the detected emission arises from relativistic particles moving through magnetic fields, allowing astronomers to trace energetic phenomena such as powerful jets from supermassive black holes and galaxies undergoing extreme star formation across cosmic time.

Expanded Seq-Scope method boosts gene-mapping resolution within tissues

In 2021, a technology developed at University of Michigan, called Seq-Scope, revolutionized the ability to map gene activity within intact tissue at microscopic resolution, enabling researchers to measure all expressed mRNA molecules and determine precisely where they are located within the tissue, using an Illumina sequencer machine.

The team behind the Seq-Scope method, led by Jun Hee Lee, Ph.D., has recently taken the technology even further.

Their findings are described in Nature Communications.

JWST Just Found Something That Shocked Scientists

The release of the 2026 dark matter map marks a definitive shift in how we approach the cosmos. For decades, we were in the hunting phase, trying to prove that dark matter existed and attempting to catch a single particle in a laboratory. While we still haven’t touched a dark matter particle, we have moved into the surveying phase. We are no longer asking if it is there; we are busy measuring its dimensions, its density, and its influence on the growth of everything we can see. This map of the Sextans field is essentially the first page in a new atlas of the invisible universe.

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Timestamps:
0:00 Dark Matter.
1:05 The Cosmic Lens.
4:20 The COSMOS-Web Survey.
7:15 Mapping the Filaments.
10:22 Beyond the Standard Model.
13:15 The Architect of Life.

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Fexl Spanish: / @fexl_es.
Fexl Portuguese: / @fexlpt.
Fexl Ukraine: / @fexl_ua.

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References:
Nature Astronomy (January 2026): An ultra-high-resolution map of (dark) matter: https://www.nature.com/articles/s4155… Pre-print (Technical Breakdown): COSMOS-Web: The ultra-deep weak lensing survey: https://arxiv.org/abs/2601.17239 NASA Webb Mission Page: Webb Unveils the Dark Matter Scaffolding of the Universe: https://www.nasa.gov/missions/webb/na… COSMOS-Web Collaboration Official Site: https://cosmos.astro.caltech.edu/ NASA JPL Press Release: Seeing the Unseen: 800,000 Galaxies Mapped: https://www.jpl.nasa.gov/news/nasa-re… #fexl #space #jwst.

ArXiv Pre-print (Technical Breakdown): COSMOS-Web: The ultra-deep weak lensing survey: https://arxiv.org/abs/2601.

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