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It should be possible to build a silicon version of the human cerebral cortex with the transistor technology that was in production in 2013. The resulting machine would take up less than a cubic meter of space and consume less than 100 watts, not too far from the human brain. This article is summarizing the work of Jennifer Hasler and Bo Marr writing in Frontiers of Neuroscience – Finding a roadmap to achieve large neuromorphic hardware systems.

Computational power efficiency for biological systems is 8–9 orders of magnitude higher (better) than the power efficiency wall for digital computation. Analog techniques at a 10 nm node can potentially reach this same level of biological computational efficiency. Figure 1 show huge potential for neuromorphic systems, showing the community has a lot of room left for improvement, as well as potential directions on how to achieve these approaches with technology already being developed; new technologies only improve the probability of this potential being reached.

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Teaches artificial intelligence superhuman relational reasoning.

A key challenge in developing artificial intelligence systems with the flexibility and efficiency of human cognition is giving them a similar ability — to reason about entities and their relations from unstructured data. Solving this would allow these systems to generalize to new combinations of entities, making infinite use of finite means.

Modern deep learning methods have made tremendous progress solving problems from unstructured data, but they tend to do so without explicitly considering the relations between objects.

In two new papers, we explore the ability for deep neural networks to perform complicated relational reasoning with unstructured data. In the first paper — A simple neural network module for relational reasoning — we describe a Relation Network (RN) and show that it can perform at superhuman levels on a challenging task. While in the second paper — Visual Interaction Networks — we describe a general purpose model that can predict the future state of a physical object based purely on visual observations.

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A Kiwi company developing artificial intelligence has delivered its latest digital human, called Rachel.

Rachel can see, hear and respond to you.

She is an avatar created by two-time Oscar winner Mark Sagar, who worked on the blockbuster movie of the same name.

Mr Sagar, of Auckland-based company Soul Machines, says his aim is to make man socialise with machine, by putting a human face on artificial intelligence.

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A total of 34 works were submitted as part of Hankook Tires’ Design Insight forum, with five winners chosen.

Mr Seung Hwa Suh, Vice Chairman and CEO of Hankook Tire said: ‘The Design Insight Forum to be held at Hankook Technodome is truly meaningful that one can witness fine works of young designers of the future tire innovation at the new and state-of-the art R&D center, Hankook Technodome.

‘Hankook Tire expects to create further synergies with the future leaders in collaboration with Hankook Tire’s technology leadership through the Design Insight Forum.’

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A company is developing a device that can allow people to see inside their brains or bodies in great detail.

The technology, developed by Openwater, works via a piece of clothing such as ski-hat lined with LCDs – and, illuminated with infrared, it can see into your body to look for things such as tumors and bleeding or clogged arteries.

While the technology has significant potential for disease detection, the company’s ultimate aim is to develop it for communication via thought — in just eight years.

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Facial paralysis suffered by thousands of Britons is being treated by pioneering NHS specialists with virtual-reality computer game-style technology.

The therapy could be used to help patients who find it too traumatic to look at their own ‘changed’ reflections after the paralysis.

The virtual-reality (VR) goggles encourage sufferers to carry out the regular facial exercises needed to regain muscle function – with the wearer watching an avatar’s face doing the exercises rather than their own.

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Increasing the level of autophagy might be the key to effective treatment of heart disease.

Today we will be looking at a new study that is attempting to treat atherosclerosis, one of the biggest age-related killers globally. As we age, our risk of developing atherosclerosis rises along with related conditions, such as hypertension.

We will be taking a look at new research that has reversed atherosclerosis in mice and is on the road to clinical trials in the future. Before we do that, let’s talk a little bit about how the disease develops and how macrophages work.

What is Atherosclerosis?

Atherosclerosis is an age-related disease where toxic, oxidized cholesterol deposits in the blood stream causes inflammation in the artery wall. This causes macrophages to swarm to the toxic cholesterol deposits, and become either M1 inflammatory or M2 healing cell types depending on the signals there.

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