Lifeboat Foundation

As developers unlock new AI tools, the risk for perpetuating harmful biases becomes increasingly high — especially on the heels of a year like 2020, which reimagined many of our social and cultural norms upon which AI algorithms have long been trained.

A handful of foundational models are emerging that rely upon a magnitude of training data that makes them inherently powerful, but it’s not without risk of harmful biases — and we need to collectively acknowledge that fact.

Recognition in itself is easy. Understanding is much harder, as is mitigation against future risks. Which is to say that we must first take steps to ensure that we understand the roots of these biases in an effort to better understand the risks involved with developing AI models.

The challenge of getting high-quality real-world data.

Tesla is combining manual labeling, auto labeling, and simulation to create real-world datasets for fully self-driving cars.

Continue reading “Tesla AI Day 2021 Review — Part 2: Training Data. How Does a Car Learn?” »

LG Energy Solutions, a partner in the research, has plans for mass production of solid-state batteries by 2027.

While the transition to renewable energies is a high priority, there is also a need to develop energy storage equipment to tide over low production cycles. Lithium-ion batteries are currently our best bet but can’t serve very high energy requirements. Researchers at the University of California, San Diego, in collaboration with LG Energy Solutions, may have solved our requirement of energy-dense batteries by developing a solid-state battery with a silicon anode.

Lithium-ion batteries use graphite coated in copper foil, as their anodes or negative electrode. While this system does work well, future applications such as electric-powered flight and energy storage for grids require batteries with high energy densities. Scientists around the globe are working to resolve this issue and ubiquitous silicon is a potential answer.

Continue reading “New Research Could Usher in a New Age of Solid-State Batteries” »

A deepening understanding of the brain has created unprecedented opportunities to alleviate the challenges posed by disability. Scientists and engineers are taking design cues from biology itself to create revolutionary technologies that restore the function of bodies affected by injury, aging, or disease — from prosthetic limbs that effortlessly navigate tricky terrain to digital nervous systems that move the body after a spinal cord injury.

With the establishment of the new K. Lisa Yang Center for Bionics, MIT is pushing forward the development and deployment of enabling technologies that communicate directly with the nervous system to mitigate a broad range of disabilities. The center’s scientists, clinicians, and engineers will work together to create, test, and disseminate bionic technologies that integrate with both the body and mind.

Intelligent sensing and tele-presence robotic technology, enabling health practitioners to remotely assess a person’s physical and cognitive health from anywhere in the world, is being pioneered in research co-led at the University of Strathclyde.

The technology could aid cost-effective diagnosis, more regular monitoring and health assessments alongside assistance, especially for people living with conditions such as Alzheimer’s disease and other cognitive impairments.

The system was demonstrated for the first time to the UK Government Minister, Iain Stewart during a visit to the construction site of the National Robotarium, hosted at Heriot-Watt University, which is co-leading the research with Strathclyde.

The space station has been showing its age, with new damage and other signs of wear being found in various modules. Most recently, Russian cosmonauts spotted about half a dozen new cracks in their Zarya module. And while both NASA and Roscosmos say the cracks don’t pose a threat to crewmembers, Insider reports that Shepherd spoke to a House of Representatives committee on Tuesday, telling the lawmakers that they need to pay attention to the possible hazard, which he called a “serious problem.”

NASA is currently trying to secure another four years’ worth of funding for the ISS, which would allow it to keep the orbital outpost running until 2,028 according to Insider. But Shepherd says NASA would be unwise to do so before actually investigating these cracks to determine not only how bad they are today but whether they’ll continue to get worse, as Russian officials have warned they might.

“Getting to the bottom of this is a fairly serious issue,” Shepherd told Congress. “I don’t think the station’s in any immediate danger. But before we clear the station for another so many years of operational use, we should better understand this.”

Engineers battle the limits of deep learning for battlefield bots.

Leading defense company Baykar has unveiled for the first time its newly designed drone that can hover, take off and land vertically at Turkey’s largest technology and aviation event, Teknofest.

The flight tests of the vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) are due to be completed soon. Mass production and delivery phases are expected to start in 2022.

The new UAV does not need a landing track and can take off from several different places, including naval or mobile platforms, said Burak Özbek, an air vehicle design engineer at Baykar, which is already known worldwide for its landmark Bayraktar TB2 and Akıncı drones.

Researchers recently showed that a computer could “learn” from many examples of protein folding to predict the 3D structure of proteins with great speed and precision. Now a recent study in the journal Science shows that a computer also can predict the 3D shapes of RNA molecules [1]. This includes the mRNA that codes for proteins and the non-coding RNA that performs a range of cellular functions.

This work marks an important basic science advance. RNA therapeutics—from COVID-19 vaccines to cancer drugs—have already benefited millions of people and will help many more in the future. Now, the ability to predict RNA shapes quickly and accurately on a computer will help to accelerate understanding these critical molecules and expand their healthcare uses.

Like proteins, the shapes of single-stranded RNA molecules are important for their ability to function properly inside cells. Yet far less is known about these RNA structures and the rules that determine their precise shapes. The RNA elements (bases) can form internal hydrogen-bonded pairs, but the number of possible combinations of pairings is almost astronomical for any RNA molecule with more than a few dozen bases.