Showing posts with label DARPA. Show all posts
Showing posts with label DARPA. Show all posts

Tuesday, January 05, 2016

DARPA's Future

1 – Human-Machine Interface ..... for true communication and machine autonomy, Artificial Intelligence must reach a level equal to or surpassing that of humans. ..... technologies that would enable machines to collaborate with humans as partners on tasks far more complex than those we can tackle today.

2 – Mind Control ...... a world where neurotechnologies could enable users to interact with their environment and other people by thought alone.

3 – Nanotech Materials .... Artificial skin, spray-on solar cells, self-repairing architecture, invisibility cloaks, and a host of DNA-level medical applications will be able to build and re-build human beings and the environment...... building substances from the atomic or molecular level up to create “impossible” materials with previously unattainable capabilities.



DARPA’s Top 3 Predictions For The Future

Monday, May 18, 2015

The Brain

Singularity is NOT near! Stop complaining about overpopulation. Why try to mimic brains when there are so many brains out there, undernourished, underutilized?
Your brain has roughly 100 billion neurons and 100 trillion neural connections, or synapses. An iPhone 6’s A8 chip has 2 billion transistors. (Though, let’s be clear, a transistor is not anywhere near the complexity of a single synapse in the brain.) .... The highest bandwidth neural interface ever placed into a human brain, on the other hand, had just 256 electrodes. Most don’t even have that. ..... The second barrier to brain interfaces is that getting even 256 channels in generally requires invasive brain surgery, with its costs, healing time, and the very real risk that something will go wrong. .............. the former editor of the journal Neuron has pointed out that carbon nanotubes are so slender that a bundle of a million of them could be inserted into the blood stream and steered into the brain, giving us a nearly 10,000-fold increase in neural bandwidth, without any brain surgery at all.


Thursday, September 11, 2014

Neuromorphic Chips

Dr. Isaac Asimov, head-and-shoulders portrait,...
Dr. Isaac Asimov, head-and-shoulders portrait, facing slightly right, 1965 (Photo credit: Wikipedia)
Is this what you see on the way to Singularity?

Neuromorphic Chips

Traditional chips are reaching fundamental performance limits. ..... The robot is performing tasks that have typically needed powerful, specially programmed computers that use far more electricity. Powered by only a smartphone chip with specialized software, Pioneer can recognize objects it hasn’t seen before, sort them by their similarity to related objects, and navigate the room to deliver them to the right location—not because of laborious programming but merely by being shown once where they should go. The robot can do all that because it is simulating, albeit in a very limited fashion, the way a brain works. ..... They promise to accelerate decades of fitful progress in artificial intelligence and lead to machines that are able to understand and interact with the world in humanlike ways. Medical sensors and devices could track individuals’ vital signs and response to treatments over time, learning to adjust dosages or even catch problems early. Your smartphone could learn to anticipate what you want next, such as background on someone you’re about to meet or an alert that it’s time to leave for your next meeting. Those self-driving cars Google is experimenting with might not need your help at all, and more adept Roombas wouldn’t get stuck under your couch. “We’re blurring the boundary between silicon and biological systems” ...... Today’s computers all use the so-called von Neumann architecture, which shuttles data back and forth between a central processor and memory chips in linear sequences of calculations. That method is great for crunching numbers and executing precisely written programs, but not for processing images or sound and making sense of it all. It’s telling that in 2012, when Google demonstrated artificial-­intelligence software that learned to recognize cats in videos without being told what a cat was, it needed 16,000 processors to pull it off. ..... “There’s no way you can build it [only] in software,” he says of effective AI. “You have to build this in silicon.” ...... Isaac Asimov’s “Zeroth Law” of robotics: “A robot may not harm humanity, or, by inaction, allow humanity to come to harm.” ..... glasses for the blind that use visual and auditory sensors to recognize objects and provide audio cues; health-care systems that monitor vital signs, provide early warnings of potential problems, and suggest ways to individualize treatments; and computers that draw on wind patterns, tides, and other indicators to predict tsunamis more accurately.


Thursday, August 18, 2011

Supercomputing + Neuroscience + Nanotechnology

This thing is looking to be pretty badass.
VentureBeat: IBM produces first working chips modeled on the human brain: so-called cognitive computing chips could one day simulate and emulate the brain’s ability to sense, perceive, interact and recognize ..... Dharmendra Modha .... is the principal investigator of the DARPA project, called Synapse (Systems of Neuromorphic Adaptive Plastic Scalable Electronics, or SyNAPSE). He is also a researcher at the IBM Almaden Research Center in San Jose, Calif. ...... “This is the seed for a new generation of computers, using a combination of supercomputing, neuroscience, and nanotechnology,” Modha said in an interview with VentureBeat. ”The computers we have today are more like calculators. We want to make something like the brain. It is a sharp departure from the past.” ...... the project could turn computing on its head, overturning the conventional style of computing that has ruled since the dawn of the information age and replacing it with something that is much more like a thinking artificial brain. The eventual applications could have a huge impact on business, science and government. The idea is to create computers that are better at handling real-world sensory problems than today’s computers can. ...... It has “neurons,” or digital processors that compute information. It has “synapses” which are the foundation of learning and memory. And it has “axons,” or data pathways that connect the tissue of the computer. ....... In von Neumann machines, memory and processor are separated and linked via a data pathway known as a bus. ....... With the human brain, the memory is located with the processor ...... The brain-like processors with integrated memory don’t operate fast at all, sending data at a mere 10 hertz, or far slower than the 5 gigahertz computer processors of today. But the human brain does an awful lot of work in parallel, sending signals out in all directions and getting the brain’s neurons to work simultaneously. Because the brain has more than 10 billion neuron and 10 trillion connections (synapses) between those neurons, that amounts to an enormous amount of computing power. ......... “We are now doing a new architecture,” Modha said. “It departs from von Neumann in variety of ways.” ...... Modha said that this new kind of computing will likely complement, rather than replace, von Neumann machines, which have become good at solving problems involving math, serial processing, and business computations. The disadvantage is that those machines aren’t scaling up to handle big problems well any more. They are using too much power and are harder to program. ........ These new chips won’t be programmed in the traditional way. Cognitive computers are expected to learn through experiences, find correlations, create hypotheses, remember, and learn from the outcomes. They mimic the brain’s “structural and synaptic plasticity.” The processing is distributed and parallel, not centralized and serial. ....... can mimic the event-driven brain, which wakes up to perform a task. ...... The goal is to create a computer that not only analyzes complex information from multiple senses at once, but also dynamically rewires itself as it interacts with the environment, learning from what happens around it. ...... neurobiology ...... IBM wants to build a computer with 10 billion neurons and 100 trillion synapses ...... will consume one kilowatt of power and will occupy less than two liters of volume ..... a cognitive computer could monitor the world’s water supply via a network of sensors and tiny motors that constantly record and report data such as temperature, pressure, wave height, acoustics, and ocean tide. It could then issue tsunami warnings in case of an earthquake. Or, a grocer stocking shelves could use an instrumented glove that monitors sights, smells, texture and temperature to flag contaminated produce. Or a computer could absorb data and flag unsafe intersections that are prone to traffic accidents. Those tasks are too hard for traditional computers.