Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI

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.

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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.

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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.

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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.

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WASHINGTON — Northrop Grumman today has two Mission Extension Vehicles in orbit providing station-keeping services for two Intelsat geostationary satellites that were running low on fuel.

The company meanwhile is preparing to launch a new servicing vehicle equipped with a robotic arm that will install propulsion jet packs on dying satellites.

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“We show that focusing on genes whose expression patterns are evolutionarily conserved across species enhances our ability to learn and predict ‘genes of importance’ to growth performance for staple crops, as well as disease outcomes in animals,” explained Gloria Coruzzi, Carroll & Milton Petrie Professor in NYU’s Department of Biology and Center for Genomics and Systems Biology and the paper’s senior author.

Machine learning can pinpoint “genes of importance” that help crops to grow with less fertilizer, according to a new study published in Nature Communications. It can also predict additional traits in plants and disease outcomes in animals, illustrating its applications beyond agriculture.

Using to predict outcomes in agriculture and medicine is both a promise and challenge for . Researchers have been working to determine how to best use the vast amount of genomic data available to predict how organisms respond to changes in nutrition, toxins, and pathogen exposure—which in turn would inform crop improvement, disease prognosis, epidemiology, and public health. However, accurately predicting such complex outcomes in agriculture and medicine from genome-scale information remains a significant challenge.

In the Nature Communications study, NYU researchers and collaborators in the U.S. and Taiwan tackled this challenge using machine learning, a type of artificial intelligence used to detect patterns in data.

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The logo of Samsung Electronics is seen at its office building in Seoul, South Korea, August 25 2017. REUTERS/Kim Hong-Ji/File Photo.

SEOUL, Sept 23 (Reuters) — Samsung Electronics (005930.KS) is in talks with Tesla (TSLA.O) to make Tesla’s next-generation self-driving chips based on Samsung’s 7-nanometre chip production process, a South Korean newspaper reported on Thursday.

Since the beginning of this year, Tesla and Samsung have discussed chip design multiple times and exchanged chip prototypes for Tesla’s upcoming Hardware 4 self-driving computer, the Korea Economic Daily reported, citing sources with direct knowledge of the matter.

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A more comprehensible concept could be “multi-skilled AI.”

Multi-skilled AI is an approach to improving technologies by expanding their senses. In a similar way to how kids learn through perception and talking, multi-skilled AI systems combine senses and language to broaden their understanding of the world.

“It goes beyond image or language recognition and allows multiple tasks to be done,” Elizabeth Bramson-Boudreau, the CEO and publisher of MIT Technology Review, tells TNW.

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