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Trent Fowler is a machine learning engineer, author, and co-host of the Futurati Podcast. He recently appeared on the Cutting Edge Podcast with Lee Pierson to discuss artificial intelligence, consciousness, free will, epistemology, and AI risk. For more of their content, check out their excellent show at the Ayn Rand Center UK: https://www.youtube.com/c/AynRandCentreUK
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My name is Roman Stolyarov, and for my PhD work at the Media Lab I developed a terrain-adaptive control system for robotic leg prostheses. While modern prostheses allow people with leg amputations to get around, the way that they get around is often tiring, uncomfortable, and burdensome on their intact joints. In the worst case, irregular terrain geometries—from uneven sidewalks to rugged hiking trails—can be difficult or impossible to navigate with conventional prostheses, burdening the user’s mobility, independence, and sense of being able-bodied. My work was intended to help people with amputations feel as able-bodied and mobile as possible, by allowing them to walk seamlessly regardless of the ground terrain.
GitHub Copilot, the text-to-code AI tool, has been—for the most part—revolutionary in determining how people code. Twitter has been erupting with people expressing how this new AI tool has benefitted them with organisation heads and developers alike hailing it for saving much of their time.
However, the latest discussion surrounding it suggests that things are murky.
A long-term antimatter storage device that may be energized by a low power magnetron and can function autonomously for hundreds of hours on the energy provided by batteries. An evacuated, cryogenic container is arranged with a source of positrons and a source of electrons positioned in capture relation to one another within the container so as to allow for the formation of a plurality of positronium atoms. A microwave resonator is located within the container forming a circularly polarized standing wave within which the plurality of positronium atoms rotate. Radioactive sources for small stores and low energy positron accelerators for large stores are used to efficiently fill the device with positronium in seconds to minutes. The device may also be arranged to provide for the extraction of positrons. A method for storing antimatter is also provided.
The wearable robot helps patients who are afraid of needles.
A recent study in Japan has revealed that a hand-held soft robot can improve the experience of patients while undergoing medical treatments, such as injections and other unpleasant therapies or immunizations.
Inspired by vaccinations during Covid
The research was inspired in part by the numerous needles people had to endure while being vaccinated against Covid-19. Some people had an aversion to these needles, which led to less people getting vaccinated, reducing the rates. Although there have been numerous studies explaining patients’ pain and anxiety during treatment, there have been few solutions studied or discussed to help patients.
A titanium robotic exoskeleton is helping an eight-year-old boy in Mexico learn to walk after being wheelchair-bound for most of his life.
The boy, David, suffers from cerebral palsy, a group of neurological disorders that surfaces during early childhood and hinders a child’s ability to control their muscle movements. In effect, it makes it extremely difficult for an affected child to walk and maintain their balance and posture.
As you can imagine, rehabilitating a child with cerebral palsy is a long and arduous process. But now, David’s speeding up his rehabilitation with the help of the battery-powered Atlas 2030 exoskeleton, developed by award winning Spanish roboticist Elena García Armada.
California produces about 90% of the nation’s strawberries, but severe drought and worker shortages are threatening the fruit. One company is hoping to change that with the power of robots.
Eric Adamson’s company is behind a strawberry robotic revolution. He said they’re programmed to think on their own, with cameras that sense texture and color.
“People think robots have been around forever, but they’re actually very, very new, especially robots that make decisions and are autonomous,” Adamson said.
If you’ve ever played the claw game at an arcade, you know how hard it is to grab and hold onto objects using robotics grippers. Imagine how much more nerve-wracking that game would be if, instead of plush stuffed animals, you were trying to grab a fragile piece of endangered coral or a priceless artifact from a sunken ship.
Most of today’s robotic grippers rely on embedded sensors, complex feedback loops, or advanced machine learning algorithms, combined with the skill of the operator, to grasp fragile or irregularly shaped objects. But researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have demonstrated an easier way.
Taking inspiration from nature, they designed a new type of soft, robotic gripper that uses a collection of thin tentacles to entangle and ensnare objects, similar to how jellyfish collect stunned prey. Alone, individual tentacles, or filaments, are weak. But together, the collection of filaments can grasp and securely hold heavy and oddly shaped objects. The gripper relies on simple inflation to wrap around objects and doesn’t require sensing, planning, or feedback control.
