A Bit of Theory: Consciousness as Integrated Information

It's essential that we determine to what extent different neural architectures can generate integrated information

5 min read

If the level of consciousness has to do with how much integrated information a conscious entity generates, it is essential that we determine to what extent different neural architectures can generate integrated information. The integrated-information theory of consciousness, or IIT, is an attempt to do so, and to approach consciousness from first principles.

IIT introduces a measure of integrated information, represented by the symbol ο and given in bits, that quantifies the reduction of uncertainty (that is, the information generated when a system enters a particular state through causal interactions among its parts) This measure is above and beyond the information generated independently within the parts themselves. The parts should be chosen in such a way that they can account for as much nonintegrated (independent) information as possible.

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The Future of Deep Learning Is Photonic

Computing with light could slash the energy needs of neural networks

10 min read
Image of a computer rendering.

This computer rendering depicts the pattern on a photonic chip that the author and his colleagues have devised for performing neural-network calculations using light.

Alexander Sludds
DarkBlue1

Think of the many tasks to which computers are being applied that in the not-so-distant past required human intuition. Computers routinely identify objects in images, transcribe speech, translate between languages, diagnose medical conditions, play complex games, and drive cars.

The technique that has empowered these stunning developments is called deep learning, a term that refers to mathematical models known as artificial neural networks. Deep learning is a subfield of machine learning, a branch of computer science based on fitting complex models to data.

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