Un-assuming The Singularity

Given the current state of computer science and robotics, it’s hard to understand how ”the singularity” meme has become lodged in the serious discourse of the technosphere

3 min read

Given the current state of computer science and robotics, it’s hard to understand how ”the singularity” meme has become lodged in the serious discourse of the technosphere. This is the idea that, as a consequence of exponentially accelerating technological innovation and continuously self-improving artificial intelligence, computer power will outstrip human brainpower, leading to the end of human culture as we know it. Not a century from now, mind you, but somewhere between 2030 and 2045, depending on whom you talk to.

The concept was framed in its most tech-savvy form by computer scientist and science-fiction writer Vernor Vinge in 1983 in Omni magazine. It has since morphed into a complicated ”theory” that for some, notably prolific inventor Ray Kurzweil, includes a posthuman after­life in which we abandon our biological selves and are uploaded into digital and possibly robotic vessels, there to spend eternity as cybernetic Methuselahs. It is also thought by its followers to be inevitable, not merely one of many possible future scenarios.

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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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