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Category: robotics/AI – Page 49

Dysphoria IoT Botnet Adds Blockchain C2 and Victim Relays After JackSkid Disruption

The lineage runs through JackSkid, one of four IoT botnets targeted in coordinated U.S., German, and Canadian law-enforcement actions on March 19. Court documents attributed more than 90,000 DDoS commands to JackSkid alone.

Within days, Nokia Deepfield and Comcast’s threat lab documented the operator falling back to an Ethereum Name Service (ENS) domain, m3rnbvs5d[.]eth, for command-and-control (C2). XLab’s Dysphoria timeline opens with a JackSkid sample captured on March 25, six days after the disruption, that resolves C2 through the same domain.

XLab found that the burrberry[.]eth record encodes distribution-node IPv4 addresses, while 24carnforth2merseyside[.]sol supplies other infrastructure records. The DDoS sample asks a distribution node over HTTP for a current server list, and the listed endpoints are infected machines relaying traffic to the real controllers. The design keeps those controllers one step removed from the addresses exposed to bots.

AI finds tiny gene editor changes that reduce unintended DNA edits

Gene editing is a highly precise and powerful technology that allows scientists to insert, delete, modify or replace DNA bases in living organisms. It has a variety of uses, including correcting disease-causing mutations and improving crops. Tools like CRISPR act as molecular scissors that target specific places in a genome to make these changes. But the technology is not perfect and can accidentally edit the wrong pieces of DNA or RNA.

In research published in Nature, scientists describe a new framework that uses AI to make these tools more accurate. Hoi Yee Chu and Alan S.L. Wong of the University of Hong Kong published a News and Views piece in the same journal on the significance of this research.

Honda and Nissan to jointly develop next-generation car operating system

Honda Motor and Nissan Motor, which have been discussing areas of cooperation, are considering jointly developing an operating system for software-defined vehicles (SDVs) based on Nissan’s technology, informed sources said Sunday.

Functionality such as autonomous driving an be added or improved in SDVs through software updates. As the vehicle’s operating system (OS) is a core technology for next-generation automobiles, standardizing it between the two Japanese automakers is expected to improve development efficiency.

In 2024, Honda and Nissan announced that they would explore collaboration in areas including SDVs, batteries and vehicle supply. They later entered talks on a potential business integration. Although those merger discussions ultimately collapsed, the companies continued to examine cooperation on a project-by-project basis.

Synthetic tumor data helps AI improve long-read cancer mutation detection

A research team at The University of Hong Kong (HKU), has developed ClairS—a deep-learning algorithm that significantly improves the detection of cancer mutations using long-read sequencing. Tested on breast cancer, lung cancer and melanoma cell line datasets, ClairS has demonstrated high accuracy across various cancer types and sequencing conditions.

The team was led by Professor Ruibang Luo, assistant director of Learning Experience & Student Enrichment and associate head of the Department of AI & Data Science at the School of Computing and Data Science (CDS) at HKU. The findings are published in the journal Nature Methods. ClairS is open source and available on GitHub.

Daydreaming algorithm helps AI remember what matters

During the day, our brain acquires new memories; at night, during sleep, it consolidates the important ones and eliminates the useless ones. A similar principle has been applied to Hopfield networks, one of the classic models of artificial intelligence inspired by the workings of the brain. In 2025, Federico Ricci-Tersenghi and colleagues developed Daydreaming, an algorithm that combines the learning of new memories with the elimination of spurious ones, drastically improving the network’s capacity.

One limitation remained, however. These networks lose effectiveness when they work with real-world data, which are rarely perfectly balanced—for example, very bright or very dark images, in which white or black pixels overwhelmingly dominate. In a new study published in the Journal of Statistical Mechanics: Theory and Experiment (JSTAT), Ricci-Tersenghi and Japanese colleagues present a new version of the algorithm capable of effectively handling realistic, strongly biased data.

A “classical” neuralnetwork The networks proposed by John Hopfield in 1982—work that would earn him the Nobel Prize in 2024—consist of artificial neurons connected to one another and are among the simplest models of associative memory. “Whenever we see any tree, our brain recalls the concept of a tree. This ability to associate many different representations with the same concept is what we call associative memory,” explains Ricci-Tersenghi, professor of theoretical physics at Sapienza University of Rome and one of the authors of the new study.

Kevin Warwick: Be/Come the Cy/Borg

In February 2011, IBM’s Watson had just beaten two human champions at Jeopardy, and most people filed it under party trick.

A few days later, I sat down with Prof. Kevin Warwick for the second time. He had already run a wire into the median nerve of his own left arm and sent a signal from his nervous system straight into his wife’s. The press called him an eccentric. A few of his colleagues used a less generous word.

So I asked him where the line between genius and madness actually sits. We also got into the magnetic implants and sensory substitution devices his students were building, the trouble his rat-brain-cell robot kept running into, and why Alan Turing was owed far more than Britain ever gave him.

Fifteen years on, #BCI implants have moved from stunt to clinical trial, #AI writes the code that writes the code, and the open question is no longer whether we merge with our machines. It is on whose terms, and who gets a vote.

Kevin’s answer back in 2011 was three words: be/come the #cyborg.

Prophecy or warning? Watch it and tell me which one you hear.

Continue reading “Kevin Warwick: Be/Come the Cy/Borg” | >

AI-powered system offers unprecedented insight into the forces shaping Earth’s climate

The world’s oceans may appear calm from space, but beneath the surface, an intricate web of fast-moving currents drives Earth’s climate. Now, a new study led by Tel Aviv University has unveiled a breakthrough that allows scientists to observe these hidden motions with unprecedented clarity.

The researchers developed GOFLOW, an artificial intelligence-powered system that can reconstruct high-resolution ocean current patterns directly from satellite images. The technology provides scientists with an entirely new way to study the small-scale ocean dynamics that influence weather, climate change and the exchange of heat and gases between the ocean and atmosphere.

The study was led by Roy Barkan, a professor, physical oceanographer and fluid dynamics expert in Tel Aviv University’s Department of Geophysics at the Faculty of Exact Sciences. The research was conducted in collaboration with scientists from the Scripps Institution of Oceanography, UCLA and the University of Rhode Island, and published in Nature Geoscience.

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