Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 2,183

The brain is the final frontier of our privacy, and AI is about to breach it

Lawyers and doctors are typically paid more than manual laborers because of the relative shorter supply of lawyers and doctors, which is in part due to the number of years of training required to enter those professions and the corresponding value society attributes to those skills. But what will happen to their wages once the market is faced with an abundance of skilled labor? If anyone is able to upload legal or medical know-how to their brain and know just as much as the professionals in those fields, why pay a professional a higher wage?

Of course, certain skills, such as strategic judgment and contextual understanding, may be difficult, if not impossible, to digitize. But even the games of chess and Go, both complex games that require strategic decision-making and foresight, have now been conquered by AIs that taught themselves how to play—and beat—some of the best human players.

The technology’s potential for emancipation and human advancement is immense. But we—entrepreneurs, researchers, professionals, policymakers, and industry—must not lose sight of the social risks.

The danger of AI is weirder than you think | Janelle Shane

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The danger of artificial intelligence isn’t that it’s going to rebel against us, but that it’s going to do exactly what we ask it to do, says AI researcher Janelle Shane. Sharing the weird, sometimes alarming antics of AI algorithms as they try to solve human problems — like creating new ice cream flavors or recognizing cars on the road — Shane shows why AI doesn’t yet measure up to real brains.
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Artificial intelligence is ‘enhancing’ healthcare: IHDpay Group

Chun Yuan Chiang of IHDpay Group says artificial intelligence cannot completely replace the “high-touch” nature of medical care. However, technology can be helpful in diagnosis or in situations where patients have long, complicated medical histories, he says. Chiang was speaking on a panel with Jai Verma of Cigna International and Dai Ying of GE Healthcare.

An imitation learning approach to train robots without the need for real human demonstrations

Most humans can learn how to complete a given task by observing another person perform it just once. Robots that are programmed to learn by imitating humans, however, typically need to be trained on a series of human demonstrations before they can effectively reproduce the desired behavior.

Researchers were recently able to teach robots to execute new tasks by having them observe a single human demonstration, using meta-learning approaches. However, these learning techniques typically require real-world data that can be expensive and difficult to collect.

To overcome this challenge, a team of researchers at Imperial College London has developed a new approach that enables one-shot imitation learning in robots without the need for real-world human demonstrations. Their approach, presented in a paper pre-published on arXiv, uses algorithms known as task-embedded control networks (TecNets), which allow artificial agents to learn how to complete tasks from a single or multiple demonstrations, as well as artificially generated .

Landmark Longevity Summits at King’s College London

“Demonstrate That Top Financial and Tech Corporations Are Committed to Longevity”

This week two Landmark International Longevity Summits in London attracted the attention of scientists, government officials, major financial corporations, insurance companies, investment banks, and technology companies from around the world. The Landmark AI for Longevity Summit and the First International Longevity Policy and Governance Summit at King’s College London are expected to become the world-leading forums for the Longevity Industry.

NASA Picks SpaceX, Blue Origin and More to Join Private Moon Lander Project

NASA has recruited SpaceX’s Starship, Blue Origin’s Blue Moon and three other commercial lunar lander ideas to join its Artemis moon program.

Today (Nov. 18), NASA announced the selection of SpaceX, Blue Origin, Sierra Nevada Corp., Ceres Robotics and Tyvak Nano-Satellite Systems, Inc. to join its Commercial Lunar Payload Services program (CLPS). The five companies can now vie to deliver robotic payloads to the lunar surface for NASA, helping to pave the way for the return of astronauts to the moon by 2024.

Nanoracks just booked a SpaceX launch to demo tech that turns used spacecraft into orbital habitats

SpaceX is going to launch a payload for client Nanoracks aboard one of its new rideshare missions, currently targeting late 2020, that will demonstrate a very ambitious piece of tech from the commercial space station company. Nanoracks is sending up a payload platform that will show off how it can use a robot to cut material very similar to the upper stages used in orbital spacecraft — something Nanoracks wants to eventually due to help convert these spent and discarded stages (sometimes called “space tugs” because they generally move payloads from one area of orbit to another) into orbital research stations, habitats and more.

The demonstration mission is part of Nanoracks’ “Space Outpost Program,” which aims to address the future need for in-space orbital commercial platforms by also simultaneously making use of existing vehicles and materials designed specifically for space. Through use of the upper stages of spacecraft left behind in orbit, the company hopes to show how it one day might be able to greatly reduce the costs of setting up in-space stations and habitats, broadening the potential access of these kinds of facilities for commercial space companies.

This will be the first-ever demonstration of structural metal cutting in space, provided the demo goes as planned, and it could be a key technology not just for establishing more permanent research families in Earth’s orbit, but also for setting up infrastructure to help us get to, and stay at, other interstellar destinations like the Moon and Mars.

An artificial intelligence algorithm can learn the laws of quantum mechanics

Artificial intelligence can be used to predict molecular wave functions and the electronic properties of molecules. This innovative AI method developed by a team of researchers at the University of Warwick, the Technical University of Berlin and the University of Luxembourg, could be used to speed-up the design of drug molecules or new materials.

Artificial intelligence and are routinely used to predict our purchasing behavior and to recognize our faces or handwriting. In , Artificial Intelligence is establishing itself as a crucial tool for scientific discovery.

In chemistry, AI has become instrumental in predicting the outcomes of experiments or simulations of quantum systems. To achieve this, AI needs to be able to systematically incorporate the fundamental laws of .

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