How do people like to interact with robots when navigating a crowded environment? And what algorithms should roboticists use to program robots to interact with humans? These are the questions that a team of mechanical engineers and computer scientists sought to answer in a recent study.
Artificial intelligence (AI) chatbots have frequently shown signs of an 'empathy gap' that puts young users at risk of distress or harm, raising the urgent need for 'child-safe AI', according to a new study. The research urges developers and policy actors to prioritize AI design that take greater account of children's needs. It provides evidence that children are particularly susceptible to treating chatbots as lifelike, quasi-human confidantes, and that their interactions with the technology can go awry when it fails to respond to their unique needs and vulnerabilities. The study links that gap in understanding to recent reports of cases in which interactions with AI led to potentially dangerous situations for young users.
Engineers have developed a new soft, flexible device that makes robots move by expanding and contracting -- just like a human muscle. To demonstrate their new device, called an actuator, the researchers used it to create a cylindrical, worm-like soft robot and an artificial bicep. In experiments, the cylindrical soft robot navigated the tight, hairpin curves of a narrow pipe-like environment, and the bicep was able to lift a 500-gram weight 5,000 times in a row without failing.
With a new surgical intervention and neuroprosthetic interface, researchers restored a natural walking gait in people with amputations below the knee. Seven patients were able to walk faster, avoid obstacles, and climb stairs more naturally than people with a traditional amputation.
Researchers have developed nanorobots that kill cancer cells in mice. The robot's weapon is hidden in a nanostructure and is exposed only in the tumour microenvironment, sparing healthy cells.
Researchers have developed a novel deep learning algorithm that outperformed existing computer-based osteoporosis risk prediction methods, potentially leading to earlier diagnoses and better outcomes for patients with osteoporosis risk.
Scientists have developed a new, more energy-efficient way for AI algorithms to process data. His model may become the basis for a new generation of AI that learns like we do. Notably, these findings may also lend support to neuroscience theories surrounding memory's role in learning.
The rise of advanced artificial intelligence (edge AI) could well mark the beginning of a new era for sustainable agriculture. A recent study proposes a roadmap for integrating this technology into farming practices. The aim? To improve the efficiency, quality and safety of agricultural production, while addressing a range of environmental, social and economic challenges.
A technique can plan a trajectory for a robot using only language-based inputs. While it can't outperform vision-based approaches, it could be useful in settings that lack visual data to use for training.
Researchers have succeeded in developing a DNA-based molecular controller. Crucially, this controller enables the autonomous assembly and disassembly of molecular robots, as opposed to manually directing it.
Including 'tactile emoticons' into social media communications can enhance communication, according to a new study.
Researchers have successfully used a new robot system to improve treatment for debilitating eye disease.
Flexible piezoelectric sensors are essential to monitor the motions of both humans and humanoid robots. However, existing designs are either are costly or have limited sensitivity. In a recent study, researchers tackled these issues by developing a novel piezoelectric composite material made from electrospun polyvinylidene fluoride nanofibers combined with dopamine. Sensors made from this material showed significant performance and stability improvements at a low cost, promising advancements in medicine, healthcare, and robotics.
Researchers have demonstrated a new method that leverages artificial intelligence (AI) and computer simulations to train robotic exoskeletons to autonomously help users save energy while walking, running and climbing stairs.
Researchers have demonstrated miniature soft hydraulic actuators that can be used to control the deformation and motion of soft robots that are less than a millimeter thick. The researchers have also demonstrated that this technique works with shape memory materials, allowing users to repeatedly lock the soft robots into a desired shape and return to the original shape as needed.