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Category: information science – Page 153

Spiking neural networks (SNNs) capture the most important aspects of brain information processing. They are considered a promising approach for next-generation artificial intelligence. However, the biggest problem restricting the development of SNNs is the training algorithm.

To solve this problem, a research team led by Prof. Zeng Yi from the Institute of Automation of the Chinese Academy of Sciences has proposed backpropagation (BP) with biologically plausible spatiotemporal adjustment for training deep spiking .

The associated study was published in Patterns on June 2.

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Marketing and the need for data rules

Legislators and decision-makers worldwide have also been active in regulating data although it’s almost impossible to keep pace with change in many places. The genuine exploitation of data requires rules and regulations, as growth always increases the potential for misuse. The task of technology companies is to build data pipelines that ensure the trust and security of AI and analytics.

Data is the new currency for businesses, and the overwhelming growth rate of it can be intimidating. The key challenge is to harness data in a way that benefits both marketers and consumers who produce it. And in doing this, manage the “big data” in an ethically correct and consumer-friendly way. Luckily, there are many great services for analyzing data, effective regulation to protect consumers’ rights and a never-ending supply of information at our hands to make better products and services. The key for businesses is to embrace these technologies so that they can avoid sinking in their own data.

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Discovering and tracking asteroids is critical for planetary defense against killer asteroid impacts. The detailed astronomical data associated with it is also useful for providing new insights for astronomers. Helping with this task is a new algorithm called THOR, which has now proven to be capable of finding asteroids. It has been running on the Asteroid Institute’s cloud-based astrodynamics platform for identifying and tracking asteroids.

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A novel algorithm developed by University of Washington researchers to discover asteroids in the solar system has proved its mettle. The first candidate asteroids identified by the algorithm — known as Tracklet-less Heliocentric Orbit Recovery, or THOR — have been confirmed by the International Astronomical Union’s Minor Planet Center.

The Asteroid Institute, a program of B612 Foundation, has been running THOR on its cloud-based astrodynamics platform — Asteroid Discovery Analysis and Mapping, or ADAM — to identify and track asteroids. With confirmation of these new asteroids by the Minor Planet Center and their addition to its registry, researchers using the Asteroid Institute’s resources can submit thousands of additional new discoveries.

“A comprehensive map of the solar system gives astronomers critical insights both for science and planetary defense,” said Matthew Holman, dynamicist and search algorithm expert at the Center for Astrophysics | Harvard & Smithsonian and the former director of the Minor Planet Center. “Tracklet-less algorithms such as THOR greatly expand the kinds of datasets astronomers can use in building such a map.”

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Astronomers have used a cloud-based technique pioneered at the University of Washington to identify and track asteroids in bunches of a hundred or more. Their achievement could dramatically accelerate the quest to find potentially threatening space rocks.

The technique makes use of a cloud-based, open-source analysis platform known as Asteroid Discovery Analysis and Mapping, or ADAM; plus a recently developed algorithm called Tracklet-less Heliocentric Orbit Recovery, or THOR. The THOR algorithm was created by Joachim Moeyens, an Asteroid Institute Fellow at UW; and Mario Juric, director of UW’s DiRAC Institute.

Teaming up ADAM and THOR may sound like a cross between a Bible story and a Marvel comic, but this dynamic duo’s superpower is strictly scientific: When ADAM runs the THOR algorithm, the software can determine the orbits of asteroids, even previously unidentified asteroids, by sifting through any large database of astronomical observations.

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Recent technological advances, such as the development of increasingly sophisticated machine learning algorithms and robots, have sparked much debate about artificial intelligence (AI) and artificial consciousness. While many of the tools created to date have achieved remarkable results, there have been many discussions about what differentiates them from humans.

More specifically, computer scientists and neuroscientists have been pondering on the difference between and “consciousness,” wondering whether machines will ever be able to attain the latter. Amar Singh, Assistant Professor at Banaras Hindu University, recently published a paper in a special issue of Springer Link’s AI & Society that explores these concepts by drawing parallels with the fantasy film “Being John Malkovich.”

“Being John Malkovich” is a 1999 film directed by Spike Jonze and featuring John Cusack, Cameron Diaz, and other famous Hollywood stars. The film tells the story of a puppeteer who discovers a portal through which he can access the mind of the movie star John Malkovich, while also altering his being.

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Classifying celestial objects is a long-standing problem. With sources at near unimaginable distances, sometimes it’s difficult for researchers to distinguish between objects such as stars, galaxies, quasars or supernovae.

Instituto de Astrofísica e Ciências do Espaço’s (IA) researchers Pedro Cunha and Andrew Humphrey tried to solve this classical problem by creating SHEEP, a that determines the nature of astronomical sources. Andrew Humphrey (IA & University of Porto, Portugal) comments: “The problem of classifying is very challenging, in terms of the numbers and the complexity of the universe, and is a very promising tool for this type of task.”

The first author of the article, now published in the journal Astronomy & Astrophysics, Pedro Cunha, a Ph.D. student at IA and in the Dept. of Physics and the University of Porto, says, “This work was born as a side project from my MSc thesis. It combined the lessons learned during that time into a unique project.”

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Can quantum science supercharge genetics? | Jim Al-Khalili for Big Think.

This interview is an episode from The Well, our new publication about ideas that inspire a life well-lived, created with the John Templeton Foundation.

Up next ► Where science fails, according to a physicist https://youtu.be/4hpdKQB2ruc.

Continue reading “What if quantum physics could eradicate illness? | Jim Al-Khalili for Big Think” | >