Artificial Intelligence News

Researchers are blurring the lines between robotics and materials, with a proof-of-concept material-like collective of robots with behaviors inspired by biology.

Groundbreaking study shows machine learning can decode emotions in seven ungulate species. A game-changer for animal welfare? Can artificial intelligence help us understand what animals feel? A pioneering study suggests the answer is yes. Researchers have successfully trained a machine-learning model to distinguish between positive and negative emotions in seven different ungulate species, including cows, pigs, and wild boars. By analyzing the acoustic patterns of their vocalizations, the model achieved an impressive accuracy of 89.49%, marking the first cross-species study to detect emotional valence using AI.

A novel system that chases larval zebrafish around an arena with predator robots is enabling scientists to understand how these days-old fish quickly learn in the real world.

Engineers have developed a versatile swimming robot that nimbly navigates cluttered water surfaces. Inspired by marine flatworms, the innovative device offers new possibilities for environmental monitoring and ecological research.

Researchers find large language models process diverse types of data, like different languages, audio inputs, images, etc., similarly to how humans reason about complex problems. Like humans, LLMs integrate data inputs across modalities in a central hub that processes data in an input-type-agnostic fashion.

Ballbots are versatile robotic systems with the ability to move around in all directions. This makes it tricky to control their movement. In a recent study, a team has proposed a novel proportional integral derivative controller that, in combination with radial basis function neural network, robustly controls ballbot motion. This technology is expected to find applications in service robots, assistive robots, and delivery robots.

A research team has developed two new autonomous navigation systems for cyborg insects to better navigate unknown, complex environments. The algorithms utilized only simple circuits that leveraged natural insect behaviors, like wall-following and climbing, to navigate challenging terrain, such as sandy, rock-strewn surfaces. For all difficulties of terrain tested, the cyborg insects were able to reach their target destination, demonstrating the potential of cyborg insects for surveillance, disaster-site exploration, and more.

Researchers have developed a new AI algorithm, called Torque Clustering, that significantly improves how AI systems independently learn and uncover patterns in data, without human guidance.

A study showed that chatbots alone outperformed doctors when making nuanced clinical decisions, but when supported by artificial intelligence, doctors performed as well as the chatbots.

Artificial Intelligence of Things (AIoT) is becoming immensely popular because of its widespread applications. In a groundbreaking study, researchers present a new AIoT framework called MSF-Net for accurately recognizing human activities using WiFi signals. The framework utilizes a novel approach that combines different signal processing techniques and a deep learning architecture to overcome challenges like environmental interference and achieve high recognition accuracy.

Researchers developed an automated system to help programmers increase the efficiency of their deep learning algorithms by simultaneously leveraging two types of redundancy in complex data structures: sparsity and symmetry.

AI agents trained in simulations that differ from the environments where they are deployed sometimes perform better than agents trained and deployed in the same environment, research shows.

Can a computer learn a language the way a child does? A recent study sheds new light on this question. The researchers advocate for a fundamental revision of how artificial intelligence acquires and processes language.

In the same way that terrestrial life evolved from ocean swimmers to land walkers, soft robots are progressing, too, thanks to recent research in battery development and design.

Scientists have developed a computing chip that can learn, correct errors, and process AI tasks.

The robotics industry should be creating robots that could be reprogrammed and repurposed for other tasks once its life span is completed, researchers have advised.

Researchers have developed a novel 6D pose dataset designed to improve robotic grasping accuracy and adaptability in industrial settings. The dataset, which integrates RGB and depth images, demonstrates significant potential to enhance the precision of robots performing pick-and-place tasks in dynamic environments.

New insect-scale microrobots can fly more than 100 times longer than previous versions. The new bots, also significantly faster and more agile, could someday be used to pollinate fruits and vegetables.

A new initiative is challenging the conversation around the direction of artificial intelligence (AI). It charges that the current trajectory is inherently biased against non-Western modes of thinking about intelligence — especially those originating from Indigenous cultures. Abundant Intelligences is an international, multi-institutional and interdisciplinary program that seeks to rethink how we conceive of AI. The driving concept behind it is the incorporation of Indigenous knowledge systems to create an inclusive, robust concept of intelligence and intelligent action, and how that can be embedded into existing and future technologies.

Are humans or machines better at recognizing speech? A new study shows that in noisy conditions, current automatic speech recognition (ASR) systems achieve remarkable accuracy and sometimes even surpass human performance. However, the systems need to be trained on an incredible amount of data, while humans acquire comparable skills in less time.