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Category: robotics/AI

Brain-inspired AI hardware helps autonomous devices operate efficiently and independently

The human brain constantly makes decisions. It requires minimal power to move bodies in a desired direction or avoid an object. A Purdue University engineer uses the brain’s efficiency as inspiration to help autonomous vehicles, such as drones and robots, make crucial, time-sensitive decisions while operating in the field.

Kaushik Roy, the Edward G. Tiedemann, Jr. Distinguished Professor of Electrical and Computer Engineering in Purdue’s Elmore Family School of Electrical and Computer Engineering and director of the Institute of Chips and AI, is developing brain-inspired hardware that enables autonomous devices to efficiently navigate and adapt to their environment. This work is published in Communications Engineering

AI-powered machines have advanced significantly over the past several decades thanks to machine learning, which enables these devices to recognize patterns and make predictions or decisions. But the algorithms that facilitate this learning require immense amounts of energy to operate due to their intensive calculations and the design of the hardware that runs them.

Wristband enables wearers to control a robotic hand with their own movements

Massachusetts Institute of Technology (MIT) engineers have developed an ultrasound wristband that precisely tracks hand movements in real-time for robotics and virtual reality control.

The next time you’re scrolling your phone, take a moment to appreciate the feat: The seemingly mundane act is possible thanks to the coordination of 34 muscles, 27 joints, and over 100 tendons and ligaments in your hand. Indeed, our hands are the most nimble parts of our bodies. Mimicking their many nuanced gestures has been a longstanding challenge in robotics and virtual reality.

Now, MIT engineers have designed an ultrasound wristband that precisely tracks a wearer’s hand movements in real-time. The wristband produces ultrasound images of the wrist’s muscles, tendons, and ligaments as the hand moves, and is paired with an artificial intelligence algorithm that continuously translates the images into the corresponding positions of the five fingers and palm.

Individual-Level Factors Associated With 10-Year Incidence of Alzheimer Disease and Related Dementias in the VA Million Veteran Program

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Robots that refuse to fail: AI evolves ‘legged metamachines’ that reassemble and withstand injury

Northwestern University engineers have developed the first modular robots with athletic intelligence. They can be combined and recombined in the wild, recover from injury and keep moving no matter what’s thrown at them.

Called “legged metamachines,” the creations are made from autonomous, Lego-like modules that snap together into an endless number of configurations. Each module by itself is a complete robot with its own motor, battery and computer. Alone, a module can roll, turn and jump. But the real agility and indestructibility emerges when the modules combine.

The study was published in the Proceedings of the National Academy of Sciences.

Claude Extension Flaw Enabled Zero-Click XSS Prompt Injection via Any Website

Specifically, the XSS vulnerability enables the execution of arbitrary JavaScript code in the context of “a-cdn.claude[.]ai.” A threat actor could leverage this behavior to inject JavaScript that issues a prompt to the Claude extension.

The extension, for its part, allows the prompt to land in Claude’s sidebar as if it’s a legitimate user request simply because it comes from an allow-listed domain.

“The attacker’s page embeds the vulnerable Arkose component in a hidden, sends the XSS payload via postMessage, and the injected script fires the prompt to the extension,” Yomtov explained. “The victim sees nothing.”

TikTok for Business accounts targeted in new phishing campaign

Threat actors are targeting TikTok for Business accounts in a phishing campaign that prevents security bots from analyzing malicious pages.

TikTok Business accounts may be targeted due to their high potential for abuse in malvertising campaigns, ad fraud, and the distribution of malicious content.

Browser threat detection and response company Push Security links the campaign to one documented last year, which targeted Google Ad Manager accounts.

WhatsApp rolls out more AI features, iOS multi-account support

WhatsApp is rolling out multiple features designed to make the app easier to use, including AI-powered message replies and photo retouching, support for two accounts on iOS, and chat history transfer between iOS and Android devices.

Meta said that after the new updates, users will be able to touch up images in the chat before sharing them with contacts or in groups using Meta AI.

The Writing Help feature enables users to quickly draft a response based on the active conversation, with Meta saying it uses Private Processing to ensure messages are completely private.

Adversarial AI framework reveals mechanisms behind impaired consciousness and a potential therapy

Consciousness, and the ways in which it can become impaired after certain brain injuries, are not well understood, making disorders of consciousness (DOC), like coma, vegetative states and minimally conscious states difficult to treat. But a new study, published in Nature Neuroscience, indicates that AI might be able to help researchers gain some traction with this problem. The research team involved in the new study has developed an adversarial AI framework to help them determine what exactly is going on in states of reduced consciousness and how to approach a solution.

To better understand the mechanisms behind impaired consciousness, the researchers developed two types of AI models and had them play a kind of game where one model determined different levels of consciousness based on EEGs simulated to look like those of real unconscious and conscious brains. The AI agents guessing consciousness levels, called deep convolutional neural networks (DCNNs), were first trained on 680,000 ten-second recordings of brain activity from conscious and unconscious humans, monkeys, bats and rats to detect which neural signals related to differing levels of consciousness. The AI showing EEG data was a biologically plausible simulation of the human brain.

“To decode consciousness from these signals, we trained three separate DCNNs, each specialized for a different brain region, to output a continuous score from 0 (unconscious) to 1 (fully conscious): a cortical consciousness detector (ctx-DCNN), a thalamic consciousness detector (th-DCNN) and a pallidal consciousness detector (pal-DCNN). The ctx-DCNN was trained on continuous consciousness levels derived from clinical scales (GCS and CRS-R), enabling it to recognize graded states of consciousness,” the study authors explain.

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