Lifeboat Foundation

“Full exploitation of this information is a major challenge,” officials with the Defense Advanced Research Projects Agency (DARPA) wrote in a 2009 brief on “deep learning.”

“Human observation and analysis of [intelligence, surveillance and reconnaissance] assets is essential, but the training of humans is both expensive and time-consuming. Human performance also varies due to individuals’ capabilities and training, fatigue, boredom, and human attentional capacity.”

Working with a team of researchers at MIT, DARPA is hoping to take all of that human know-how and shrink it down into processing unit no bigger than your cellphone, using a microchip known as “Eyeriss.” The concept relies on “neural networks;” computerized memory networks based on the workings of the human brain.

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Just when you believe things cannot get more stranger; a “Frankenstein” fund is created for a competition in the UK to bring a brain back to life.

The Brain Preservation Foundation is offerings a cash prize of $100,000 to anyone who can successfully develop a way to preserve and reanimate a human brain.

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Meet “Unreal Engine”; VR’s friend in VR game creations.

Epic Games has been teasing “the future of VR development” recently, and the team is finally ready to tell everyone what that is: Creating virtual reality content within virtual reality itself, using the full version of its Unreal Engine 4. Epic cofounder Tim Sweeney says that while the company’s been supporting the likes of the Oculus Rift from the outset, the irony is that, up to this point, the experiences we’ve seen so far have been developed using the same tools as traditional video games. “Now you can go into VR, have the entire Unreal editor functioning and do it live,” he says. “It almost gives you god-like powers to manipulate the world.”

So rather than using the same 2D tools (a keyboard, mouse and computer monitor) employed in traditional game development, people making experiences for VR in Unreal can now use a head-mounted display and motion controllers to manipulate objects in a 3D space. “Your brain already knows how to do this stuff because we all have an infinite amount of experience picking up and moving 3D objects,” Sweeney says. “The motions you’d do in the real world, you’d do in the editor and in the way you’d expect to; intuitively.”

Continue reading “Create VR experiences within VR itself using Unreal Engine” »

More news on DARPA’s new deep learning microchip for the military.

A military-funded breakthrough in microchips opens the door to portable deep learning.

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Time triva facts that make you go hmmm.

Passage of time is faster for your face than for your feet (supposing you’re standing up). Einstein’s theory of relativity states that the nearer you are to the center of the Earth, the slower time passes – and this has been already measured. For an instance, at the top of Mount Everest, a year would be about 15 microseconds shorter than at sea level.

A second isn’t what just you consider it is. Technically, it’s not defined as 1/60th of a minute, but as “the duration of 9,192,631,770 periods of the radiation consistent to the transition between the two hyperfine levels of the ground state of the caesium 133 atom”.

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DARPA is making great progress on their research on mapping and understanding the human brain. Recently they are working on a project that break’s Stevenson’s Law. Stevenson Law states that the number of neurons that can be recorded simultaneously will double every seven years, and currently sits at about 500 neurons; however, DARPA’s goal is to take it to 1 million neurons. Which means taking Brain-Mind Interface capabilities to a level where anyone or anything with this technology can outperform and control machines like we only dream about.

This week neuroscientists met with DARPA in Arlington, Virginia, to embark on a project breaking Stevenson’s Law.

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Researchers have constructed the first comprehensive model of how neurons in the brain behave when faced with a complex decision-making process, and how they adapt and learn from mistakes.

The mathematical model, developed by researchers from the University of Cambridge, is the first biologically realistic account of the process, and is able to predict not only behaviour, but also neural activity. The results, reported in the Journal of Neuroscience, could aid in the understanding of conditions from obsessive compulsive disorder and addiction to Parkinson’s disease.

The model was compared to experimental data for a wide-ranging set of tasks, from simple binary choices to multistep sequential decision making. It accurately captures behavioural choice probabilities and predicts choice reversal in an experiment, a hallmark of complex decision making.

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Very interesting discovery about how our brain thinks; our brain isn’t always 100% error proof according to this report from Carnegie Mellon University. Therefore, when researchers are mapping the brain plus mimicking human brain functions; what is the tolerance level for error allowed then?

A study conducted at Carnegie Mellon University investigated the brain’s neural activity during learned behavior and found that the brain makes mistakes because it applies incorrect inner beliefs, or internal models, about how the world works. The research suggests that when the brain makes a mistake, it actually thinks that it is making the correct decision—its neural signals are consistent with its inner beliefs, but not with what is happening in the real world.

“Our brains are constantly trying to predict how the world works. We do this by building internal models through experience and learning when we interact with the world,” said Steven Chase, an assistant professor in the Department of Biomedical Engineering and the Center for the Neural Basis of Cognition. “However, it has not yet been possible to track how these internal models affect instant-by-instant behavioral decisions.”

Continue reading “Mental Miscues” »

Scientists were able to study brain growth using a 3D gel model in order to see how the human brain gets its folds.

New research shows that our brains are likely folded because, as they grow, a large amount of volume has to fit in a small space (AKA, our skulls). This compression is actually beneficial, the folds reduce the length of neuronal wiring, improving cognitive function.

Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences teamed up with scientists in Finland and France to find out more about the folding process.

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