Soft robotics have several key advantages over rigid counterparts, including their inherent safety features—soft materials with motions powered by inflating and deflating air chambers can safely be used in fragile environments or in proximity with humans—as well as their flexibility that enables them to fit into tight spaces. Textiles have become a choice material for constructing many types of soft robots, especially wearables, but the traditional “cut and sew” methods of manufacturing have left much to be desired.
Now, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have established a new approach for additively manufacturing soft robotics, using a 3D knitting method that can holistically “print” entire soft robots. Their work is reported in Advanced Functional Materials.
“The soft robotics community is still in the phase of seeking alternative materials approaches that will enable us to go beyond more classical rigid robot shapes and functions,” says Robert Wood, senior corresponding author on the paper, who is the Harry Lewis and Marlyn McGrath Professor of Engineering and Applied Sciences at SEAS.
The former Apple employees Imran Chaudhri and Bethany Bongiorno developed Humane with a “future that is even more intelligent and even more personal,” according to the company’s website.
The demo is clever, questionably real, and prompts a lot of questions about how this device will actually work.
Buzz has been building around the secretive tech startup Humane for over a year, and now the company is finally offering a look at what it’s been building. At TED last month, Humane co-founder Imran Chaudhri gave a demonstration of the AI-powered wearable the company is building as a replacement for smartphones. Bits of the video leaked online after the event, but the full video is now available to watch.
The device appears to be a small black puck that slips into your breast pocket, with a camera, projector, and speaker sticking out the top.
From a designer with two decades’ experience at Apple.
You may not have heard of piezoelectric materials, but odds are, you have benefitted from them.
Piezoelectric materials are solid materials —like crystals, bone or proteins—that produce an electric current when they are placed under mechanical stress.
Materials that harvest energy from their surroundings (through light, heat and motion) are finding their way into solar cells, wearable and implantable electronics and even onto spacecraft. They let us keep devices charged for longer, maybe even forever, without the need to connect them to a power supply.
In a new study in Nature Machine Intelligence, researchers Bojian Yin and Sander Bohté from the HBP partner Dutch National Research Institute for Mathematics and Computer Science (CWI) demonstrate a significant step towards artificial intelligence that can be used in local devices like smartphones and in VR-like applications, while protecting privacy.
They show how brain-like neurons combined with novel learning methods enable training fast and energy-efficient spiking neural networks on a large scale. Potential applications range from wearable AI to speech recognition and Augmented Reality.
While modern artificial neural networks are the backbone of the current AI revolution, they are only loosely inspired by networks of real, biological neurons such as our brain. The brain however is a much larger network, much more energy-efficient, and can respond ultra-fast when triggered by external events. Spiking neural networks are special types of neural networks that more closely mimic the working of biological neurons: the neurons of our nervous system communicate by exchanging electrical pulses, and they do so only sparingly.
“Half a century since the concept of a cyborg was introduced, Jizai-bodies (digital cyborgs), enabled by the spread of wearable robotics, are the focus of much research in recent times,” states the company’s website.
