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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

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.

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.

We’ll Soon Trust AI More Than Doctors to Diagnose Disease

It probably goes without saying, but medicine has improved a lot in modern times. No one would willingly go back to the days of sketchy anesthetics and experimental surgery.

We know a lot more about what ails the body and how to treat disease.

But could we do better? Sure. Some conditions yet confound doctors. Patients still suffer. As much as the situation has improved—some things haven’t changed a bit.

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