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Category: information science – Page 133

An algorithm developed by researchers from Helmholtz Munich, the Technical University of Munich (TUM) and its University Hospital rechts der Isar, the University Hospital Bonn (UKB) and the University of Bonn is able to learn independently across different medical institutions. The key feature is that it is self-learning, meaning it does not require extensive, time-consuming findings or markings by radiologists in the MRI images.

This federated was trained on more than 1,500 MRI scans of healthy study participants from four institutions while maintaining data privacy. The algorithm then was used to analyze more than 500 patient MRI scans to detect diseases such as multiple sclerosis, vascular disease, and various forms of brain tumors that the algorithm had never seen before. This opens up new possibilities for developing efficient AI-based federated algorithms that learn autonomously while protecting privacy. The study has now been published in the journal Nature Machine Intelligence.

Health care is currently being revolutionized by artificial intelligence. With precise AI solutions, doctors can be supported in diagnosis. However, such algorithms require a considerable amount of data and the associated radiological specialist findings for training. The creation of such a large, central database, however, places special demands on . Additionally, the creation of the findings and annotations, for example the marking of tumors in an MRI image, is very time-consuming.

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Why we should be performing interstellar archaeology and how Avi Loeb and his team at the Galileo Project plan to recover an interstellar object at the bottom of the ocean.

“Any chemically-propelled spacecraft sent by past civilizations into interstellar space, like the five we had sent so far (Voyager 1 & 2, Pioneer 10 & 11, and New Horizons), remained gravitationally bound to the Milky Way long after these civilizations died. Their characteristic speed of tens of kilometers per second is an order of magnitude smaller than the escape speed out of the Milky Way. These rockets would populate the Milky Way disk and move around at similar speeds to the stars in it.

This realization calls for a new research frontier of “interstellar archaeology”, in the spirit of searching our backyard of the Solar system for objects that came from the cosmic street surrounding it. The interstellar objects could potentially look different than the familiar asteroids or comets which are natural relics or Lego pieces from the construction project of the Solar system planets. The traditional field of archaeology on Earth finds relics left behind of cultures which are not around anymore. We can do the same in space.“
https://avi-loeb.medium.com/

The goal of the Galileo Project is to bring the search for extraterrestrial technological signatures of Extraterrestrial Technological Civilizations (ETCs) from accidental or anecdotal observations and legends to the mainstream of transparent, validated and systematic scientific research. This project is complementary to traditional SETI, in that it searches for physical objects, and not electromagnetic signals, associated with extraterrestrial technological equipment.

Continue reading “Why a Group of Scientists Plan to Search for Alien Technology with Avi Loeb” | >

Managing road intersections in crowded and dynamic environments, such as urban areas, can be highly challenging. The poor management of traffic at these can lead to road accidents, wastage of fuel, and environmental pollution.

Researchers at the University of Maryland have recently developed GAMEOPT, a that could help manage unsignalized road intersections with high traffic more efficiently. The research team with members, Nilesh Suriyarachchi, Rohan Chandra, John S. Baras and Dinesh Manocha introduced their method in a recent paper to be published in the proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022). This method combines optimization techniques with ideas from game theory, a mathematical construct that represents situations in which different agents are competing with one another.

“Forty percent of all crashes, 50% of serious collisions, and 20% of fatalities occur at unsignalized intersections,” Chandra, a member of the research team, told TechXplore. “Our primary objective is to improve traffic flow and in poorly regulated or unregulated traffic intersections. To achieve this objective, we propose an algorithm that combines ideas from optimization and game theory to understand how different traffic agents cooperate and negotiate with each other at traffic intersections.”

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“I believe we can train the algorithm not only to picture accurately a face you’re looking at, but also any face you imagine vividly, such as your mother’s,” explains Dado.

“By developing this technology, it would be fascinating to decode and recreate subjective experiences, perhaps even your dreams,” Dado says. “Such technological knowledge could also be incorporated into clinical applications such as communicating with patients who are locked within deep comas.”

Dado’s work is focused on using the technology to help restore vision in people who, through disease or accident, have become blind, reports the Mail Online.

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In recent years, deep learning algorithms have achieved remarkable results in a variety of fields, including artistic disciplines. In fact, many computer scientists worldwide have successfully developed models that can create artistic works, including poems, paintings and sketches.

Researchers at Seoul National University have recently introduced a new artistic framework, which is designed to enhance the skills of a sketching . Their framework, introduced in a paper presented at ICRA 2022 and pre-published on arXiv, allows a sketching robot to learn both stroke-based rendering and motor control simultaneously.

“The primary motivation for our research was to make something cool with non-rule-based mechanisms such as deep learning; we thought drawing is a cool thing to show if the drawing performer is a learned robot instead of human,” Ganghun Lee, the first author of the paper, told TechXplore. “Recent deep learning techniques have shown astonishing results in the artistic area, but most of them are about generative models which yield whole pixel outcomes at once.”

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Millions of children log into chat rooms every day to talk with other children. One of these “children” could well be a man pretending to be a 12-year-old girl with far more sinister intentions than having a chat about “My Little Pony” episodes.

Inventor and NTNU professor Patrick Bours at AiBA is working to prevent just this type of predatory behavior. AiBA, an AI-digital moderator that Bours helped found, can offer a tool based on behavioral biometrics and algorithms that detect sexual abusers in online chats with children.

And now, as recently reported by Dagens Næringsliv, a national financial newspaper, the company has raised capital of NOK 7.5. million, with investors including Firda and Wiski Capital, two Norwegian-based firms.

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Most materials—from rubber bands to steel beams—thin out as they are stretched, but engineers can use origami’s interlocking ridges and precise folds to reverse this tendency and build devices that grow wider as they are pulled apart.

Researchers increasingly use this kind of technique, drawn from the ancient art of , to design spacecraft components, medical robots and antenna arrays. However, much of the work has progressed via instinct and trial and error. Now, researchers from Princeton Engineering and Georgia Tech have developed a general formula that analyzes how structures can be configured to thin, remain unaffected, or thicken as they are stretched, pushed or bent.

Kon-Well Wang, a professor of mechanical engineering at the University of Michigan who was not involved in the research, called the work “elegant and extremely intriguing.”

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An art collective is trying to get an AI-supported candidate into Danish Parliament in 2023. Could we have a fully virtual candidate one day?

With all the political rancor that has become a part of our everyday reality, maybe it’s time to admit that humans may not be the best at forging agreements. Our egos are always in play, and emotions often rule our political choices more than reason. Maybe artificial intelligence (AI) could do a better job, or at least that’s what the creators of The Synthetic Party, the world’s first AI-based political party, think. The party hopes to run an AI candidate in Denmark’s general election in 2023.

Full Story:

Imaginima/iStock.

Continue reading “An AI-based party vows to win Denmark’s general election in 2023. Can it succeed?” | >

This is Episode 7 in a series of videos discussing the General Theory of General Intelligence as overviewed in the paper.
Goertzel, Ben. “The General Theory of General Intelligence: A Pragmatic Patternist Perspective.“
https://arxiv.org/pdf/2103.15100
This episode overviews ideas regarding how the particular nature and requirements of *human-like-ness* can be used guide the design and education of AGI systems. This is where cognitive science and computer science richly intersect. Core architectural ideas of OpenCog along with numerous other AGI systems (MicroPsi, LIDA, Aaron Sloman’s work,…) are reviewed in this context.
Some additional references relevant to this episode are:
Goertzel, Ben. “The Embodied Communication Prior: A characterization of general intelligence in the context of Embodied social interaction.” In 2009 8th IEEE International Conference on Cognitive Informatics, pp. 38–43. IEEE, 2009.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.352…1&type=pdf.
Bengio, Yoshua. “The consciousness prior.” 2017
https://arxiv.org/pdf/1709.08568
Goertzel, Ben, Matt Iklé, and Jared Wigmore. “The architecture of human-like general intelligence.” In Theoretical foundations of artificial general intelligence, pp. 123–144. Atlantis Press, Paris, 2012.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.1548
Ben Goertzel, Cassio Pennachin, and Nil Geisweiller. Engineering.
General Intelligence, Part 1: A Path to Advanced AGI via Embodied Learning and Cognitive Synergy. Springer: Atlantis Thinking Machines, 2013.
https://1lib.us/book/2333263/7af06e?id=2333263&secret=7af06e.
Ben Goertzel, Cassio Pennachin, and Nil Geisweiller. Engineering.
General Intelligence, Part 2: The CogPrime Architecture for Integrative, Embodied AGI. Springer: Atlantis Thinking Machines, 2013.
https://1lib.us/book/2333264/207a57?id=2333264&secret=207a57
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Hyperparameter tuning is important for algorithms. It improves their overall performance of a machine learning model and is set before the learning process and happens outside of the model. If hyperparameter tuning does not occur, the model will produce errors and inaccurate results as the loss function is not minimized.

Hyperparameter tuning is about finding a set of optimal hyperparameter values which maximizes the model’s performance, minimizes loss and produces better outputs.

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