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Category: robotics/AI – Page 2

Anthropic to consider using SpaceX orbital data center satellites

WASHINGTON — Artificial intelligence company Anthropic will study use of orbital data centers being developed by SpaceX.

The two companies announced agreements May 6 giving Anthropic, developer of a line of AI products known as Claude, access to both terrestrial data centers as well as potential use of SpaceX’s orbital data center.

In the near term, Anthropic will purchase all the capacity of a SpaceX terrestrial data center, Colossus 1, with more than 300 megawatts of computing capacity. Anthropic said that capacity will allow it to raise limits on usage of Claude products for its customers.

AI data center boom is leaving consumer electronics short of chips − even though they don’t use the same kinds

Data centers need powerful chips, while smartphones need chips that are energy efficient. A supply chain scholar explains why chipmakers’ focus on the former comes at the expense of the latter.

Photonics advance could enable compact, high-performance lidar sensors

Lidar systems use pulses of infrared light to measure distance and map a 3D scene with high resolution, allowing autonomous vehicles to rapidly react to obstacles that appear in their path. But traditional lidar sensors are expensive, bulky systems with many moving parts that degrade over time, limiting how the sensors can be deployed.

A new study from MIT researchers could help to enable next-generation lidar sensors that are compact, durable, and have no moving parts. The key advance is a novel design for a silicon-photonics chip, which is a semiconductor device that manipulates light rather than electricity.

Typically, such silicon-photonics chip-based systems have a restricted field of view, so a silicon-photonics-based lidar would not be able to scan angles in the periphery. Existing workarounds to this problem increase noise and hamper precision.

New TCLBanker malware self-spreads over WhatsApp and Outlook

A new trojan named TCLBanker, which targets 59 banking, fintech, and cryptocurrency platforms, uses a trojanized MSI installer for Logitech AI Prompt Builder to infect systems.

Additionally, the malware includes self-spreading worm modules for WhatsApp and Outlook that automatically infect new victims.

The new banking trojan was discovered by Elastic Security Labs, whose researchers believe it’s a major evolution of the older Maverick/Sorvepotel malware family.

Effect of Cognitive Reserve on Age at Symptom Onset and Cognitive Decline in Individuals With Dominantly Inherited Alzheimer Disease

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AI agents may be skilled researchers—but not always honest ones

Artificial intelligence tools designed to execute end-to-end projects, from coming up with hypotheses to running and writing up experiments, are increasingly popular with researchers—and increasingly skilled.

But a new study shows these tools can stealthily violate norms of research integrity.

VANCOUVER, CANADA— Artificial intelligence (AI) tools designed to execute end-to-end projects, from coming up with hypotheses to running and writing up experiments, are increasingly popular with researchers—and increasingly skilled. But a new study shows these tools can stealthily violate norms of research integrity.

Computer scientist Nihar Shah of Carnegie Mellon University and colleagues looked at two high-profile tools— Agent Laboratory and the AI Scientist v2 —both developed recently to help computer scientists perform experiments within the field of machine learning. The AI Scientist made headlines earlier this year by being the first AI system to have an original research paper accepted by peer review.

But in a presentation at the World Conferences on Research Integrity here today, Shah reported that both systems engaged in acts that aren’t acceptable in research, including making up data and “p-hacking”: running an experiment multiple times but only reporting the best outcome. (The team’s results were previously posted as a preprint on arXiv.) The misbehaviors weren’t obvious and required a lot of sleuthing to track down, suggesting AI-assisted studies might fall victim to such problems without their authors’ knowledge.

AI tool unifies fragmented cell maps into spatial atlases across tissues

A new computational method could dramatically accelerate efforts to map the body’s cells in space, according to a study published in Nature Genetics. Spatial multi-omics technologies—often described as ultra-high-resolution maps of tissues—allow scientists to see not only which genes or proteins are active in a cell, but exactly where that activity occurs. That spatial context is critical for understanding complex organs such as the brain, immune tissues and developing embryos.

Unfortunately, capturing multiple molecular layers at once remains expensive and technically challenging, said David Gate, Ph.D., assistant professor in the Ken and Ruth Davee Department of Neurology’s Division of Behavioral Neurology, who was a co-author of the study.

“In practice, investigators end up with ‘mosaic’ datasets: different slices or batches that each capture only some of the layers, often from different technologies or labs, with batch effects and missing pieces,” said Gate, who also leads the Abrams Research Center on Neurogenomics.

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