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Category: robotics/AI – Page 1,196

Scientists Pump Up Lab-Grown Muscles for Robots With a New Magnetic Workout

Unfortunately, these precise cell arrangements are also why artificial muscles are difficult to recreate in the lab. Despite being soft, squishy, and easily damaged, our muscles can perform incredible feats—adapt to heavy loads, sense the outside world, and rebuild after injury. A main reason for these superpowers is alignment—that is, how muscle cells orient to form stretchy fibers.

Now, a new study suggests that the solution to growing better lab-grown muscles may be magnets. Led by Dr. Ritu Raman at the Massachusetts Institute of Technology (MIT), scientists developed a magnetic hydrogel “sandwich” that controls muscle cell orientation in a lab dish. By changing the position of the magnets, the muscle cells aligned into fibers that contracted in synchrony as if they were inside a body.

The whole endeavor sounds rather Frankenstein. But lab-grown tissues could one day be grafted into people with heavily damaged muscles—either from inherited diseases or traumatic injuries—and restore their ability to navigate the world freely. Synthetic muscles could also coat robots, providing them with human-like senses, flexible motor control, and the ability to heal after inevitable scratches and scrapes.

Tesla shares hands-free Full Self-Driving demo in Austin

Tesla has shared a video of a hands-free drive demonstration of its Full Self-Driving suite in Austin. The FSD suite is not available to customers in a hands-free nature, but Tesla disabled the requirement for a new video it shared on X, formerly known as Twitter.

Tesla shared the video to demonstrate the capabilities of Software Version 11.4.7, which is the current version of the FSD Beta program.

The automaker describes in the Tweet in put up how the Full Self-Driving suite improves through data-driven techniques that refine the capabilities through analysis of other drivers’ behavior and normal navigation habits.

Why scientists are reanimating spider corpses for research

That spider you squished? It could have been used for science!

At least, that’s what Faye Yap and Daniel Preston think. Yap is a mechanical engineering PhD student in Preston’s lab at Rice University, where she co-authored a paper on reanimating spider corpses to create grippers, or tiny machines used to pick up and put down delicate objects. Yap and Preston dubbed this use of biotic materials for robotic parts “necrobotics” – and think this technique could one day become a cheap, green addition to the field.

Driving companywide efficiencies with AI

Autonomous shopping carts that follow grocery store customers and robots that pick ripe cucumbers faster than humans may grab headlines, but the most compelling applications of AI and ML technology are behind the scenes. Increasingly, organizations are finding substantial efficiency gains by applying AI-and ML-powered tools to back-office procedures such as document processing, data entry, employee onboarding, and workflow automation.

The power of automation to augment productivity in the back office has been clear for decades, but the recent emergence of advanced AI and ML tools offers a step change in what automation can accomplish, including in highly regulated industries such as health care.

A Hebbian memory that achieves human-like results on sequential processing tasks

Transformers are machine learning models designed to uncover and track patterns in sequential data, such as text sequences. In recent years, these models have become increasingly sophisticated, forming the backbone of popular conversational platforms, such as ChatGPT.

While existing transformers have achieved good results in a variety of tasks, their performance often declines significantly when processing longer sequences. This is due to their limited storage capacity, or in other words the small amount of data they can store and analyze at once.

Researchers at Sungkyunkwan University in South Korea recently developed a new memory system that could help to improve the performance of transformers on more characterized by longer data sequences. This system, introduced in a paper published on the arXiv preprint server, is inspired by a prominent theory of human memory, known as Hebbian theory.

Marines Test Fire Robot Dog Armed With Rocket Launcher

Dogs of War bots.

Armed with a rocket launcher or other kinds of weapons, including small arms, a quadrupedal robot could also just be used to scout ahead of friendly forces, and then have the ability to immediately engage any threats it finds.

Uncrewed ground systems like this have the ability to get in and out of spaces where a person might not be able to at all, as well, which could again be particularly useful when maneuvering through dense urban environments. The U.S. military sees operations in large built-up areas as a key component of any future major conflict.

This is, of course, not the first time that the U.S. military has explored the idea of a small armed uncrewed ground vehicle that could accompany even very small units. Designs based on tracked robots primarily designed for explosive ordnance disposal work have been and continue to be developed.

Creating Sapient Technology and Cyborg Rights Should Happen Soon

Here’s my latest Opinion piece just out for Newsweek…focusing on cyborg rights.

Over the past half-century, the microprocessor’s capacity has doubled approximately every 18–24 months, and some experts predict that by 2030, machine intelligence could surpass human capabilities. The question then arises: When machines reach human-level intelligence, should they be granted protection and rights? Will they desire and perhaps even demand such rights?

Beyond advancements in microprocessors, we’re witnessing breakthroughs in genetic editing, stem cells, and 3D bioprinting, all which also hold the potential to help create cyborg entities displaying consciousness and intelligence. Notably, Yale University’s experiments stimulating dead pig brains have ignited debates in the animal rights realm, raising questions about the ethical implications of reviving consciousness.

Amid these emerging scientific frontiers, a void in ethical guidelines exists, akin to the Wild West of the impending cyborg age. To address these ethical challenges, a slew of futurist-oriented bills of rights have emerged in the last decade. One of the most prominent is the Transhumanist Bill of Rights, which is in its third revision through crowdsourcing and was published verbatim by Wired in 2018.

These cyborg bills encompass a broad array of protections, including safeguards for thinking robots, gender recognition for virtual intelligences, regulations for genetically engineered sapient beings, and the defense of freedoms for biohackers modifying their bodies. Some also incorporate tech-driven rules to combat environmental threats like asteroids, pandemics, and nuclear war.

Scientists develop deep learning-based biosensing platform to better count viral particles

Recent studies have found that Gires-Tournois (GT) biosensors, a type of nanophotonic resonator, can detect minuscule virus particles and produce colorful micrographs (images taken through a microscope) of viral loads. But they suffer from visual artifacts and non-reproducibility, limiting their utilization.

In a recent breakthrough, an international team of researchers, led by Professor Young Min Song from the School of Electrical Engineering and Computer Science at Gwangju Institute of Science and Technology in Korea, has leveraged artificial intelligence (AI) to overcome this problem. Their work was published in Nano Today.

Rapid and on-site diagnostic technologies for identifying and quantifying viruses are essential for planning treatment strategies for infected patients and preventing further spread of the infection. The COVID-19 pandemic has highlighted the need for accurate yet decentralized that do not involve complex and time-consuming processes needed for conventional laboratory-based tests.

Researchers use measurements to generate quantum entanglement and teleportation

Quantum mechanics is full of weird phenomena, but perhaps none as weird as the role measurement plays in the theory. Since a measurement tends to destroy the “quantumness” of a system, it seems to be the mysterious link between the quantum and classical world. And in a large system of quantum bits of information, known as “qubits,” the effect of measurements can induce dramatically new behavior, even driving the emergence of entirely new phases of quantum information.

This happens when two competing effects come to a head: interactions and measurement. In a quantum system, when the qubits interact with one another, their information becomes shared nonlocally in an “entangled state.” But if you measure the system, the is destroyed. The battle between measurement and interactions leads to two : one where interactions dominate and entanglement is widespread, and one where measurements dominate, and entanglement is suppressed.

As reported in the journal Nature, researchers at Google Quantum AI and Stanford University have observed the crossover between these two regimes—known as a “measurement-induced phase transition”—in a system of up to 70 qubits. This is by far the largest system in which measurement-induced effects have been explored.

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