What Can You (Legally) Take From the Web?

Web sites and bloggers beware: copyright law applies to you too

5 min read

Intellectual property law has a history of clashing with new technologies. In the early 1900s, for example, when player pianos were all the rage, the U.S. Supreme Court decided that the perforated music rolls fed into player pianos were not music—essentially because they didn’t look like sheet music and performed a mechanical function. The ruling meant that sellers of the music rolls did not infringe the copyrights of the composers whose music was played by means of the rolls. The copyright law was eventually changed to address that unfair situation, but the copyright/technology clash has continued with the advent of video players, Napster, and CD burners.

The result is an unsatisfying patchwork of legislative action, court decisions, and lobbying on the part of writers, artists, photographers, publishers, and musicians who sometimes embrace and other times feel threatened by technological advances. Unfortunately, that means there is often no clear-cut answer to the question of what you can legally take from the Web: it depends on what you take, why you take it, who you are, and what technology you use. Among other factors, the fair-use defense of copyright infringement depends on whether or not the copying is commercial in nature or for nonprofit educational purposes, the amount and substantiality of the portion used, and the nature of the copyrighted work.

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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

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

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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