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Comment Re:Results As Expected (Score 1) 170

They took the same reinforcement learning techniques from the Atria 2600 AI and applied them to Doom. It worked. Next they plan to do it on Quake. Let me give you a hint for the future: It'll work.

It is still noteworthy, since the Atari visual frames are built up from sprites of limited size that are very convenient for a convolutional model: once it has learned to detect the sprites, it has an accurate representation of the location of the relevant objects in the scene. In doom, since it is a 3D scene, there is no such one-to-one correspondence between object identities and visual appearance. The fact that the method still works is not at all trivial.

Comment Re:Destroys Raspberry Pi? (Score 1) 205

It costs more than $117, from TFA:

Yes, you are reading that correctly. The board itself, which starts at $117, will not operate on its own. To make it a full-fledged usable device for projects and other uses, you must add the SolidPC Q4 single-board 'carrier' computer which is $40. In other words, you are looking at a minimum of $157

Submission + - Sometimes a Bug Is More Than a Nuisance (

sproketboy writes: All it took to explode the European Space Agency's 10 year and $7 billion Ariane 5 less than a minute into its maiden voyage last June, was a small computer program trying to stuff a 64-bit number into a 16-bit space.

One bug, one crash. Of all the careless lines of code recorded in the annals of computer science, this one may stand as the most devastatingly efficient. From interviews with rocketry experts and an analysis prepared for the space agency, a clear path from an arithmetic error to total destruction emerges.

Submission + - Could a neuroscientist understand a microprocessor?

mugurel writes: The Atlantic reviews a thought-provoking article just published (but not yet peer-reviewed), in which neuroscientists try to gain understanding in the MOS 6502 microchip (containing 3510 transistors), using methodologies commonly applied in neuroscience. More specifically, they study typical behaviors of the chip, running games like "Space Invaders" and "Donkey Kong". A lesion study of the system, lesioning a single transistor at a time, fails to reveal functional areas of the chip that are uniquely involved in a single game. Even a big data approach like applying dimension reduction techniques on a recording the complete state of the system over time, only gives very superficial insight in the functional roles of the different parts of the chip.

With this work, the authors aim to put into perspective our hopes of understanding the brain with current neuroscientific methods.

Comment Questionable assumption (Score 1) 110

Understanding how the brain works by modeling one cubic mm of cortical matter? It sounds like: "We want to understand the global ecosystem, and we start by simulating what's happening on this square meter of soil". First of all, there is likely going to be a huge diversity in terms of the structures and behavior of a cubic mm of cortical matter, depending on what part of the brain you look at. Secondly, it is relatively undisputed that the functional behavior of the brain is determined by structures at scales far larger than that cubic mm, which that cubic mm is not going to tell you anything about.

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