"[T]he current capabilities of many AI systems closely match some of the specialized needs of disabled people.... Fortunately, there is a growing interest in applying the scientific knowledge and engineering experience developed by AI researchers to the domain of assistive technology and in investigating new methods and techniques that are required within the assistive technology domain."
– Bruce G. Buchanan; from his Foreword to Assistive Technology and Artificial Intelligence: Applications in Robotics, User Interfaces and Natural Language Processing
As a cucumber plant grows, it sprouts tightly coiled tendrils that seek out supports in order to pull the plant upward. This ensures the plant receives as much sunlight exposure as possible. Now, researchers at MIT have found a way to imitate this coiling-and-pulling mechanism to produce contracting fibers that could be used as artificial muscles for robots, prosthetic limbs, or other mechanical and biomedical applications. While many different approaches have been used for creating artificial muscles, including hydraulic systems, servo motors, shape-memory metals, and polymers that respond to stimuli, they all have limitations, including high weight or slow response times. The new fiber-based system, by contrast, is extremely lightweight and can respond very quickly, the researchers say.
Three teams have developed artificial muscles that can lift 1000 times their own weight. They hope the new fibres could be used in prosthetic limbs, robots, exoskeletons, and even in clothing. All three teams have developed their muscles according to a similar principle: that a coiled-up substance can stretch like a muscle. The idea was developed by Ray Baughman and his colleagues at the University of Texas, who found that twisting up even a simple material like sewing thread or fishing line can create a muscle-like structure that, for its size, can lift weights 100 times heavier than human muscle can manage. Now, Baughman's team have developed stronger fibres, using similarly inexpensive materials.
Earlier this month, Amazon hosted its re:MARS artificial intelligence conference that showcased emerging tech like tiny autonomous vehicles and robotic prosthetic limbs. But the event, celebrated as a glimpse into the future of technology, may have actually been a thinly-veiled advertisement for the future of Amazon, according to The Verge. After walking the floor and attending the events, The Verge's James Vincent wrote that nearly every problem facing tech developers today had the same suggested solution: use Amazon's services. No matter how sophisticated the showcased technology may have been, the glimmer of technological progress was largely overshadowed by – as ZDNet described – Amazon's attempt to position itself as an AI leader and a necessary business partner for anyone else developing AI. No matter what big, lofty goals techno-optimists have for the future -- whether its cleaning the oceans, improving crop yields, or settling the cosmos -- an attendee would walk away thinking that Amazon Web Services, the company's web developer and cloud computing package, is the best way to get there.
Closed-captioning in videos: Adding or turning on closed-captioning in all videos, including YouTube and GoNoodle, assists students in making connections between text and audio representations of language. Captioning is an assistive technology tool that is free and easy to use: simply push the CC button underneath a video. Closed-captioning provides missing information for individuals who have difficulty processing speech and auditory components of visual media. It is crucial for students who are hard of hearing and can support students' reading skills. Graphic organizers: Graphic organizers are a no-tech AT tool that offers a simple, effective way to provide writing support to elementary, middle, and high school students who have dysgraphia, executive function challenges, and other learning challenges.
Abstract: In this work, we propose a non-autoregressive seq2seq model that converts text to spectrogram. It is fully convolutional and obtains about 17.5 times speed-up over Deep Voice 3 at synthesis while maintaining comparable speech quality using a WaveNet vocoder. Interestingly, it has even fewer attention errors than the autoregressive model on the challenging test sentences. Furthermore, we build the first fully parallel neural text-to- speech system by applying the inverse autoregressive flow (IAF) as the parallel neural vocoder. Our system can synthesize speech from text through a single feed-forward pass.
A man who almost died from meningitis has revealed how he began to look forward to having his limbs amputated. Mike Davies, 60, from Brighton, spent 70 days in intensive care with meningococcal meningitis and septicaemia. During this time, he said he knew his hands and feet were "dead" and he would recover better without them. Now he says he is in a positive place and "can even hold a pint of beer". With the help of prosthetic limbs, Mr Davies can drive a specially-adapted car and said he was living life to the full.
Next-generation wheelchairs could incorporate brain-controlled robotic arms and rentable add-on motors in order to help people with disabilities more easily carry out daily tasks or get around a city. Professor Nicolás García-Aracil from the Universidad Miguel Hernández (UMH) in Elche, Spain, has developed an automated wheelchair with an exoskeleton robotic arm to use at home, as part of a project called AIDE. It uses artificial intelligence to extract relevant information from the user, such as their behaviour, intentions and emotional state, and also analyses its environmental surroundings, he says. The system, which is based on an arm exoskeleton attached to a robotised wheelchair, is designed to help people living with various degrees and forms of disabilities carry out daily functions such as eating, drinking, and washing up, on their own and at home. While the user sits in the wheelchair, they wear the robotised arm to help them grasp objects and bring them close -- or as the whole system is connected to the home automation system they can ask the wheelchair to move in a specific direction or go into a particular room.
By taking it upon itself to learn about its structure and environment, the robotic limb can then develop its own personalized gait and learn a new walking task after just five minutes of motor babbling. So much so, it can recover when being tripped in time to plant its next step safely on the ground even though it wasn't programmed to do so. The researchers believe this is the first robot to be capable of such a feat, and are excited about the possibilities the advance opens up.
Zuniga's team then began work on the device. James Pierce, a doctoral student in UNO's biomechanics program, said they scrapped the grasping hand featured in Zuniga's original design, known as the Cyborg Beast. Zuniga, who started the work at Creighton University, estimated that his team has made about 2,000 of them. He put instructions for making the 3D hand online -- free for anyone to use -- several years ago. The device can be built with 3D printing technology for about $50 in materials.