Robotics/AI – Lifeboat News: The Blog

Oct 15
2016

Google Creates New, Smarter AI

My guess is there is some QC help in this picture.

Artificial neural networks — systems patterned after the arrangement and operation of neurons in the human brain — excel at tasks that require pattern recognition, but are woefully limited when it comes to carrying out instructions that require basic logic and reasoning. This is a problem for scientists working toward the creation of Artificial Intelligence (AI) systems capable of performing complex tasks with minimal human supervision.

In a step toward overcoming this hurdle, researchers at Google’s DeepMind — the company that developed the Go-playing computer program AlphaGo — announced earlier this week the creation of a neural network that can not only learn, but can also use data stored in its memory to “logically reason” and make inferences to answer questions.

DeepMind’s new system — called a Differentiable Neural Computer (DNC) — combines deep learning, wherein it can learn from examples and make sense of complex input it has never received before, with an external memory, which, as the DeepMind researchers Alexander Graves and Greg Wayne explain in a blog post, allows it to “store knowledge quickly and reason about it flexibly.”

Oct 15
2016

How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?

For decades the efficient coding hypothesis has been a guiding principle in determining how neural systems can most efficiently represent their inputs. However, conclusions about whether neural circuits are performing optimally depend on assumptions about the noise sources encountered by neural signals as they are transmitted. Here, we provide a coherent picture of how optimal encoding strategies depend on noise strength, type, location, and correlations. Our results reveal that nonlinearities that are efficient if noise enters the circuit in one location may be inefficient if noise actually enters in a different location. This offers new explanations for why different sensory circuits, or even a given circuit under different environmental conditions, might have different encoding properties.

Citation: Brinkman BAW, Weber AI, Rieke F, Shea-Brown E (2016) How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits? PLoS Comput Biol 12(10): e1005150. doi:10.1371/journal.pcbi.1005150

Editor: Jeff Beck, Duke University, UNITED STATES

Oct 15
2016

Google’s AI can now learn from its own memory independently

The DeepMind artificial intelligence (AI) being developed by Google’s parent company, Alphabet, can now intelligently build on what’s already inside its memory, the system’s programmers have announced.

Their new hybrid system – called a Differential Neural Computer (DNC) – pairs a neural network with the vast data storage of conventional computers, and the AI is smart enough to navigate and learn from this external data bank.

What the DNC is doing is effectively combining external memory (like the external hard drive where all your photos get stored) with the neural network approach of AI, where a massive number of interconnected nodes work dynamically to simulate a brain.

Oct 14
2016

Not Everyone Agrees On the Future of Uber Drivers When Self-Driving Cars Arrive

As Uber pushes ahead with plans for self-driving cars, there are differing views on the roles of drivers in that future.

Oct 14
2016

Robots Are Beginning To Learn The Same Way As Humans

The robot uses trial and error to perfect complex tasks.

Oct 14
2016

A Computer That Stores Memories Like Humans Do

A new mathematical model of memory could accelerate the quest to build super-powered, brain-inspired hardware systems.

Oct 14
2016

Yes, Robots Really Are Going To Take Your Job And End The American Dream

The American Dream is ending, and its automated software and hardware technology that’s ending it.

Now that machines can diagnose cancer, trade stocks, and write symphonies, they’re not just going to make humans more efficient as they have in the past—they are replacing them entirely and wrecking the economy along the way.

Oct 14
2016

Brain Implant Allows Paralyzed Man to Feel Objects With a Prosthetic Limb

Researchers from the University of Pittsburgh and UPMC have developed a system that’s enabling a man with quadriplegia to experience the sensation of touch through a robotic arm that he controls with his brain.

Oct 14
2016

This Monkey is Controlling a Wheelchair With its Mind

Researchers have developed a wireless brain interface that allows monkeys to control the movements of a robotic wheelchair using their thoughts alone. The breakthrough suggests that similar interfaces could allow severely paralyzed individuals to navigate all sorts of robotic devices with their minds.

Oct 14
2016

Anki’s Cozmo robot is the new, adorable face of artificial intelligence

Human beings have an uneasy relationship with robots. We’re fascinated by the prospect of intelligent machines. At the same time, we’re wary of the existential threat they pose, one emboldened by decades of Hollywood tropes. In the near-term, robots are supposed to pose a threat to our livelihood, with automation promising to replace human workers while the steady march of artificial intelligence puts a machine behind every fast food counter, toll booth, and steering wheel.

In comes Cozmo. The palm-sized robot, from San Francisco-based company Anki, is both a harmless toy and a bold refutation of that uneasy relationship so loved by film and television. The $180 bot, which starts shipping on October 16th, is powered by AI, and the end result is a WALL-E -inspired personality more akin to a clever pet than a do-everything personal assistant.