Advancing Autonomous Navigation: NC State Researchers Enhance 3D Mapping with AI

Researchers at North Carolina State University have developed an innovative technique that allows artificial intelligence (AI) programs to more accurately map three-dimensional (3D) spaces using two-dimensional (2D) images captured by multiple cameras. This advancement promises to significantly improve the navigation capabilities of autonomous vehicles while operating efficiently with limited computational resources.

“Most autonomous vehicles use powerful AI programs called vision transformers to take 2D images from multiple cameras and create a representation of the 3D space around the vehicle,” explained Tianfu Wu, Ph.D., Associate Professor of Electrical and Computer Engineering at North Carolina State University. “However, while each of these AI programs takes a different approach, there is still substantial room for improvement.”

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Neuromorphic Computing: The Future of AI Hardware

While much of the tech world remains fixated on the latest large language models (LLMs) powered by Nvidia GPUs, a quieter revolution is brewing in AI hardware. As the limitations and energy demands of traditional deep learning architectures become increasingly apparent, a new paradigm called neuromorphic computing is emerging – one that promises to slash the computational and power requirements of AI by orders of magnitude. To delve into this promising technology, VentureBeat spoke with Sumeet Kumar, CEO and founder of Innatera, a leading startup in the neuromorphic chip space.

“Neuromorphic processors are designed to mimic the way biological brains process information,” Kumar explained. “Rather than performing sequential operations on data stored in memory, neuromorphic chips use networks of artificial neurons that communicate through spikes, much like real neurons.” This brain-inspired architecture gives neuromorphic systems distinct advantages, particularly for edge computing applications in consumer devices and industrial IoT.

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Revolutionizing Software Engineering: The Impact of Large Language Models

The rapid advancement of large language models (LLMs) is transforming various fields, including software engineering. In just a few years, LLMs have evolved from advanced code autocomplete tools to AI agents capable of designing software, implementing and correcting entire modules, and enhancing software engineers’ productivity.

While some excitement around AI-powered software engineering agents is overhyped, there is undeniable value for developers who harness these new AI tools to accomplish more in less time. There are three main ways that LLMs are changing the coding experience:

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Revolutionizing Agriculture: The Transformative Power of Edge AI

The transformative power of artificial intelligence (AI) is poised to make a significant impact on one of the world’s oldest and most critical sectors: agriculture. A new study suggests that “edge AI” could revolutionize farming practices, boost productivity, and achieve sustainability goals across the global food chain.

Edge AI involves programming AI algorithms directly on local devices “at the edge” of a network rather than in a centralized data center. This technology has the potential to enhance farming practices by integrating sensors and AI into smart farm vehicles and machines, facilitating precise irrigation and agrochemical application. According to the study, this precision can reduce the use of water, fertilizers, and agrochemicals, advancing sustainability strategies on farms.

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Ray Kurzweil: The Singularity Is Nearer and AI’s Future

Ray Kurzweil, a renowned American computer scientist and techno-optimist, is a long-time authority on artificial intelligence (AI). His 2005 bestselling book, The Singularity Is Near, captivated audiences with its sci-fi-like predictions that computers would achieve human-level intelligence by 2029 and that humans would merge with computers to become superhuman by around 2045—a phenomenon he termed “the Singularity.” Now, nearly 20 years later, Kurzweil, 76, has released a sequel, The Singularity Is Nearer, and some of his predictions no longer seem so far-fetched. Kurzweil, currently a principal researcher and AI visionary at Google, shared his insights with the Observer in his personal capacity as an author, inventor, and futurist.

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Advanced AUVs: Revolutionizing Underwater Conservation with AI

Covering nearly 80% of the planet, the underwater environment is critical in maintaining ecological balance and supporting human well-being. Effective conservation relies on a thorough understanding of underwater species distribution and ecosystem dynamics, but this process can be time-consuming and costly.

A team of U.S. National Science Foundation-funded researchers at the Minnesota Interactive Robotics and Vision Laboratory is working to overcome these challenges. They are developing advanced autonomous underwater vehicles (AUVs) powered by artificial intelligence to collect vast amounts of data, provide detailed insights into species distribution, and create comprehensive habitat maps to understand environmental drivers.

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Revolutionizing Balance Assessment: AI and Wearable Sensors Lead the Way

Traditionally, physicians have relied on subjective observations and specialized equipment to gauge balance in individuals with conditions such as Parkinson’s disease, neurological injuries, and age-related decline. These methods, especially the subjective ones, can lack precision, be difficult to administer remotely, and often prove inconsistent. Addressing these limitations, researchers from Florida Atlantic University have developed a novel approach using wearable sensors and advanced machine learning algorithms that could redefine balance assessment practices.

The researchers utilized wearable Inertial Measurement Unit (IMU) sensors placed on five body locations: ankle, lumbar, sternum, wrist, and arm. Data collection followed the Modified Clinical Test of Sensory Interaction on Balance (m-CTSIB) protocol, testing four sensory conditions: eyes open and closed on stable and foam surfaces. Each test lasted roughly 11 seconds, simulating continuous balance scenarios.

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New AI Model Enhances Understanding of Human Decision-Making

Human beings often behave irrationally—or as an artificially intelligent robot might say, “sub-optimally.” Data, the emotionless yet affable android from Star Trek: The Next Generation, frequently struggled to understand humans’ flawed decision-making processes. If he had been programmed with a new model developed by researchers at MIT and the University of Washington, he might have had an easier time.

In a paper published last month, Athul Paul Jacob, a Ph.D. student in AI at MIT, Dr. Jacob Andreas, his academic advisor, and Abhishek Gupta, an assistant professor in computer science and engineering at the University of Washington, described a novel approach to modeling an agent’s behavior. They employed their method to predict human goals and actions.

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AI-Powered Smartphone Tool from RMIT University Enhances Early Stroke Detection

Biomedical engineers at RMIT University have unveiled a groundbreaking smartphone tool equipped with AI capabilities that could revolutionize the early detection of strokes. This innovative technology uses AI to analyze facial expressions, assisting paramedics in quickly identifying stroke symptoms, which could save lives and prevent long-term disability.

Strokes occur when blood flow to the brain is obstructed, depriving brain cells of oxygen and nutrients. As a leading cause of disability and death worldwide, timely intervention during a stroke is critical. Every minute counts and can significantly influence a patient’s recovery.

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University of Bonn Develops AI Software to Predict Crop Growth

Researchers at the University of Bonn have developed innovative software that simulates the growth of field crops using artificial intelligence. By feeding thousands of photos from field experiments into a learning algorithm, the software can predict the future development of cultivated plants based on a single initial image. This technology allows for accurate estimation of parameters such as leaf area and yield.

This breakthrough offers significant benefits for farmers, helping them determine optimal plant combinations and fertilizer choices to maximize yield. In the future, farmers will increasingly rely on computer support to answer critical questions about crop management.

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New AI Framework Revolutionizes Wearable Exoskeletons for Enhanced Human Mobility

“This work proposes and demonstrates a new machine-learning framework that bridges the gap between simulation and reality to autonomously control wearable robots to improve mobility and health of humans,” says Hao Su, an associate professor of mechanical and aerospace engineering at North Carolina State University.

“Exoskeletons have enormous potential to improve human locomotive performance,” Su, the corresponding author of a new study published in Nature, explains. “However, their development and broad dissemination are limited by the requirement for lengthy human tests and handcrafted control laws.”

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AI Breakthrough: UK Company Develops Rare-Earth-Free Magnet

As the demand for rare earth materials continues to grow, innovative solutions are emerging to address this need. UK deep-tech company Materials Nexus has announced the development of a new rare-earth-free permanent magnet, created using its advanced AI platform. This AI-driven process was 200 times faster than traditional methods, offering a promising alternative in a world increasingly reliant on powerful magnets.

With the shift from internal combustion engines to electric mobility, the need for compact, high-power motors is skyrocketing. Currently, permanent magnet motors are the dominant choice in the automotive industry, powering over 80% of modern electric vehicles (EVs). Materials Nexus projects that the demand for permanent magnets in the EV sector alone will increase tenfold by 2030. Beyond automotive applications, these magnets are essential in robotics, drones, wind turbines, and HVAC systems.

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