Lifeboat Foundation

“We should plan ahead,” warned physicist Stephen Hawking who died last March, 2018, and was buried next to Isaac Newton. “If a superior alien civilization sent us a text message saying, ‘We’ll arrive in a few decades,’ would we just reply, ‘OK, call us when you get here, we’ll leave the lights on’? Probably not, but this is more or less what has happened with AI.”

The memorial stone placed on top of Hawking’s grave included his most famous equation describing the entropy of a black hole. “Here Lies What Was Mortal Of Stephen Hawking,” read the words on the stone, which included an image of a black hole.

Continue reading “Stephen Hawking --‘Treating AI as Science Fiction Would Potentially Be Our Worst Mistake Ever‘” »

Using algorithms, scientists can simulate how different nanoparticles interact with the antigen component—and how well they activate the immune system.

Obstacle avoidance is a crucial piece of technology for drones, but commercially-available systems just aren’t fast enough for some situations. Now, engineers at the University of Zurich have developed a new system that gives drones such fast reflexes that they can play – and win at – dodgeball.

According to the researchers, most current obstacle avoidance systems take about 20 to 40 milliseconds to process changes in their surroundings. That’s fine for a drone gently approaching a building and finding its way inside, but it’s no match for fast-moving obstacles like birds or other drones. That makes navigation a problem in certain situations, like when there are a lot of drones together or in dynamic environments like disaster zones, or when a drone just needs to move fast.

Continue reading “Drone plays dodgeball to demo fast new obstacle detection system” »

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A research team from ITMO University, with the help of colleagues from MIPT (Russia) and Politecnico di Torino (Italy), has predicted a novel type of topological quantum state of two photons. Scientists have also applied a new, affordable experimental method for testing this prediction. The method relies on an analogy: Instead of expensive experiments with quantum systems of two or more entangled photons, the researchers have used resonant electric circuits of higher dimensionality described by similar equations. The obtained results can be useful for the engineering of optical chips and quantum computers without the need for expensive experiments. The research was published in Nature Communications.

Light plays a key role in modern information technologies: With its help, information is transmitted over large distances via optical fibers. In the future, scientists anticipate the invention of optical chips and computers that process information with the help of photons—light quanta—instead of electrons, as it is done today. This will decrease energy consumption, while also increasing the capabilities of computers. However, to turn these predictions into reality, fundamental and applied research of light behavior at the micro- and nanoscale is needed.

Continue reading “The imitation game: Scientists describe and emulate new quantum state of entangled photons” »

Clause density is something new to me but seems interesting as I know shores algorithm is the only thing that can hack systems.

Google is racing to develop quantum-enhanced processors that utilize quantum mechanical effects to one day dramatically increase the speed at which data can be processed.

In the near term, Google has devised new quantum-enhanced algorithms that operate in the presence of realistic noise. The so-called quantum approximate optimization algorithm, or QAOA for short, is the cornerstone of a modern drive towards noise-tolerant quantum-enhanced algorithm development.

Continue reading “Russian Scientists Break Google’s Quantum Algorithm” »

More than 2,000 papers have been published about the virus since December. It will take some smart algorithms to mine insights from them.

Over the past decade or so, researchers worldwide have developed increasingly advanced techniques to enable robot navigation in a variety of environments, including on land, in the air, underwater or on particularly rough terrains. To be effective, these techniques should allow robots to move around in their surroundings both safely and efficiently, saving as much energy as possible.

Researchers at the Indian Institute of Technology Kharagpur in India have recently developed a new approach to achieve efficient path planning in mobile robots. Their method, presented in a paper published in Springer Link’s Nature-Inspired Computation in Navigation and Routine Problems, is based on the use of a flower pollination algorithm (FPA), a soft computing-based tool that can identify ideal solutions to a given problem by considering a number of factors and criteria.

“Flower pollination algorithms (FPAs) have shown their potential in various engineering fields,” Atul Mishra, one of the researchers who carried out the study, told TechXplore. “In our study, we used the algorithm to solve the problem of path planning for mobile robots. Our prime objective was to plan, in the least time possible, the most optimal path in terms of minimum path length and energy consumption, with maximum safety.”

Google announced Monday that it is making available an open-source library for quantum machine-learning applications.

TensorFlow Quantum, a free library of applications, is an add-on to the widely-used TensorFlow toolkit, which has helped to bring the world of machine learning to developers across the globe.

“We hope this framework provides the necessary tools for the quantum computing and machine learning research communities to explore models of both natural and artificial quantum systems, and ultimately discover new quantum algorithms which could potentially yield a quantum advantage,” a report posted by members of Google’s X unit on the AI Blog states.

Intel Israel announced that the project is the first of its kind which uses AI to create “female intelligence.” The experts who worked on the project, led by data scientist and researcher Shira Guskin, analyzed thousands of insights from “veteran career women.” Once the initial advice was submitted by many women across the Israeli work force, the researchers passed the data through three algorithm models: Topic Extraction, Grouping and Summarization. This led to an algorithm which “processed the tips pool and extracted the key tips and guidelines.”

The AI said that women should fully invest in their careers, be confident, network, love, and trust their guts.