Lifeboat Foundation

“Conditional witnessing” technique makes many-body entangled states easier to measure.

Quantum error correction – a crucial ingredient in bringing quantum computers into the mainstream – relies on sharing entanglement between many particles at once. Thanks to researchers in the UK, Spain and Germany, measuring those entangled states just got a lot easier. The new measurement procedure, which the researchers term “conditional witnessing”, is more robust to noise than previous techniques and minimizes the number of measurements required, making it a valuable method for testing imperfect real-life quantum systems.

Quantum computers run their algorithms on quantum bits, or qubits. These physical two-level quantum systems play an analogous role to classical bits, except that instead of being restricted to just “0” or “1” states, a single qubit can be in any combination of the two. This extra information capacity, combined with the ability to manipulate quantum entanglement between qubits (thus allowing multiple calculations to be performed simultaneously), is a key advantage of quantum computers.

Continue reading “New quantum entanglement verification method cuts through the noise” »

Featureless “cost functions” prevent quantum machine learning algorithms from reconstructing scrambled information.

Is the physical universe independent from us, or is it created by our minds, as suggested by scientist Robert Lanza?

Army researchers have developed a pioneering framework that provides a baseline for the development of collaborative multi-agent systems.

The framework is detailed in the survey paper “Survey of recent multi-agent reinforcement learning algorithms utilizing centralized training,” which is featured in the SPIE Digital Library. Researchers said the work will support research in reinforcement learning approaches for developing collaborative multi-agent systems such as teams of robots that could work side-by-side with future soldiers.

“We propose that the underlying information sharing mechanism plays a critical role in centralized learning for multi-agent systems, but there is limited study of this phenomena within the research community,” said Army researcher and computer scientist Dr. Piyush K. Sharma of the U.S. Army Combat Capabilities Development Command, known as DEVCOM, Army Research Laboratory. “We conducted this survey of the state-of-the-art in reinforcement learning algorithms and their information sharing paradigms as a basis for asking fundamental questions on centralized learning for multi-agent systems that would improve their ability to work together.”

Erika Woodrum/HHMI/NatureTwo tiny arrays of implanted electrodes relayed information from the brain area that controls the hands and arms to an algorithm, which translated it into letters that appeared on a screen.

New EPFL research has found that almost half of local Twitter trending topics in Turkey are fake, a scale of manipulation previously unheard of. It also proves for the first time that many trends are created solely by bots due to a vulnerability in Twitter’s Trends algorithm.

Social media has become ubiquitous in our modern, daily lives. It has changed the way that people interact, connecting us in previously unimaginable ways. Yet, where once our social media networks probably consisted of a small circle of friends most of us are now part of much larger communities that can influence what we read, do, and even think.

One influencing mechanism, for example, is “Twitter Trends.” The platform uses an algorithm to determine hashtag-driven topics that become popular at a given point in time, alerting twitter users to the top words, phrases, subjects and popular hashtags globally and locally.

The researchers started with a sample taken from the temporal lobe of a human cerebral cortex, measuring just 1 mm³. This was stained for visual clarity, coated in resin to preserve it, and then cut into about 5300 slices each about 30 nanometers (nm) thick. These were then imaged using a scanning electron microscope, with a resolution down to 4 nm. That created 225 million two-dimensional images, which were then stitched back together into one 3D volume.

Machine learning algorithms scanned the sample to identify the different cells and structures within. After a few passes by different automated systems, human eyes “proofread” some of the cells to ensure the algorithms were correctly identifying them.

Continue reading “Google and Harvard map brain connections in unprecedented detail” »

With 2700 locations across 10000 U.S. communities, YMCA is becoming a major hub for healthy living — From vaccinations and diabetes prevention programs, to healthy aging and wellness — Siva Balu, VP/Chief Information Officer — The Y of the U.S.A.

Mr. Siva Balu is Vice President and Chief Information Officer of YMCA of the U.S. (Y-USA), where he is working to rethink and reorganize the work of the organization’s information technology strategy to meet the changing needs of Y-USA and Ys throughout the country.

Continue reading “Siva Balu — VP / Chief Information Officer — YMCA of the U.S.A. — People, Potential, & Purpose” »

Deep-learning expert weighs in on getting to AGI, assessing algorithmic intelligence, autonomous vehicles,” “Mark Ryan is a Data Science Manager at Intact Insurance and the author of the recently-released “Deep Learning with Structured Data”. He holds a Masters degree in Computer Science from the University of Toronto, and is interested in chatbots and natural language processing.