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Dec 25, 2019

Human Brain-Like Functions Emerge in Neuromorphic Metallic Nanowire Network

Posted by in categories: biotech/medical, nanotechnology, robotics/AI

An international joint research team led by NIMS succeeded in fabricating a neuromorphic network composed of numerous metallic nanowires. Using this network, the team was able to generate electrical characteristics similar to those associated with higher-order brain functions unique to humans, such as memorization, learning, forgetting, becoming alert and returning to calm. The team then clarified the mechanisms that induced these electrical characteristics.

The development of artificial intelligence (AI) techniques has been rapidly advancing in recent years and has begun impacting our lives in various ways. Although AI processes information in a manner similar to the human brain, the mechanisms by which human brains operate are still largely unknown. Fundamental brain components, such as neurons and the junctions between them (synapses), have been studied in detail. However, many questions concerning the brain as a collective whole need to be answered. For example, we still do not fully understand how the brain performs such functions as memorization, learning, and forgetting, and how the brain becomes alert and returns to calm. In addition, live brains are difficult to manipulate in experimental research. For these reasons, the brain remains a mysterious organ.

Dec 25, 2019

A Young Mississippi Woman’s Journey Through A Pioneering Gene-Editing Experiment

Posted by in categories: bioengineering, biotech/medical, genetics, health

Sickle Cell Therapy With CRISPR Gene Editing Shows Promise : Shots — Health News NPR tells the exclusive, behind-the-scenes story of the first person with a genetic disorder to be treated in the United States with the revolutionary gene-editing technique CRISPR.

Dec 25, 2019

Brain Connections: Neuromorphic Devices Emulate the Brain’s Hardware

Posted by in categories: engineering, information science, robotics/AI

Nowadays, there is an imperative need for novel computational concepts to manage the enormous data volume produced by contemporary information technologies. The inherent capability of the brain to cope with these kinds of signals constitutes the most efficient computational paradigm for biomimicry.

Representing neuronal processing with software-based artificial neural networks is a popular approach with tremendous impacts on everyday life; a field commonly known as machine learning or artificial intelligence. This approach relies on executing algorithms that represent neural networks on a traditional von Neumann computer architecture.

An alternative approach is the direct emulation of the workings of the brain with actual electronic devices/circuits. This emulation of the brain at the hardware-based level is not only necessary for overcoming limitations of conventional silicon technology based on the traditional von Neumann architecture in terms of scaling and efficiency, but in understanding brain function through reverse engineering. This hardware-based approach constitutes the main scope of neuromorphic devices/computing.

Dec 25, 2019

Tencent details how its MOBA-playing AI system beats 99.81% of human opponents

Posted by in categories: entertainment, robotics/AI

Researchers at Tencent recently detailed an AI system capable of defeating teams of professionals in Honor of Kings, a MOBA game with a large fanbase.

Dec 25, 2019

A new deep learning model for EEG-based emotion recognition

Posted by in category: robotics/AI

Recent advances in machine learning have enabled the development of techniques to detect and recognize human emotions. Some of these techniques work by analyzing electroencephalography (EEG) signals, which are essentially recordings of the electrical activity of the brain collected from a person’s scalp.

Most EEG-based emotion classification methods introduced over the past decade or so employ traditional (ML) techniques such as support vector machine (SVM) models, as these models require fewer training samples and there is still a lack of large-scale EEG datasets. Recently, however, researchers have compiled and released several new datasets containing EEG brain recordings.

The release of these datasets opens up exciting new possibilities for EEG-based emotion recognition, as they could be used to train deep-learning models that achieve better performance than traditional ML techniques. Unfortunately, however, the low resolution of EEG signals contained in these datasets could make training deep-learning models rather difficult.

Dec 25, 2019

New engine tech could get us to Mars faster

Posted by in category: space travel

NASA wants to send humans to Mars one day, but do we have the engines to get us there?

Dec 25, 2019

The complicated ethics of genetic engineering

Posted by in categories: bioengineering, ethics, genetics

With new technology to edit genes, scientists are now working on things that once seemed impossible. But what are the boundaries? See the full 60 Minutes interview with Church, here: https://cbsn.ws/34ZhuTs

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Dec 25, 2019

Amazing Facts About Our Gut Microbiome

Posted by in category: biotech/medical

Over 35,000 bacterial species live in your gut!

Dec 25, 2019

To Make Robots Perform Better, Make Them Constantly Fear Death

Posted by in category: robotics/AI

So to increase productivity, neuroscientists propose giving IAs self preservation sense.

Robots that fear death 😂😅🤣.


Finally, robots that are actually lifelike.

Dec 24, 2019

Best News From 2019

Posted by in category: futurism

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