15 U.S.C. § 9204 — Generative adversarial network defined
submitted 6 years ago by Pub. L. 116-258 to r/title-15-COMMERCE-AND-TRADE · 94 words · no verdicts yet
A “generative adversarial network” is an artificial-intelligence process in which a generator and discriminator neural network compete, creating feedback that improves generated outputs and detection. This section does not define other quoted terms.
In this chapter, “generative adversarial network” means an artificial-intelligence machine-learning process in which a generator artificial neural network (the “generator”) and a discriminator artificial neural network (the “discriminator”) compete to become more accurate. Their competition creates a feedback loop: the generator produces increasingly better artificial outputs, and the discriminator increasingly improves at detecting those outputs. This section does not define the other quoted terms.
In this chapter, the term “generative adversarial network” means, with respect to artificial intelligence, the machine learning process of attempting to cause a generator artificial neural network (referred to in this section as the “generator” 1 and a discriminator artificial neural network (referred to in this section as a “discriminator”) to compete against each other to become more accurate in their function and outputs, through which the generator and discriminator create a feedback loop, causing the generator to produce increasingly higher-quality artificial outputs and the discriminator to increasingly improve in detecting such artificial outputs.
Source credit: (Pub. L. 116–258, § 6, Dec. 23, 2020, 134 Stat. 1152.)
- 2020Enacted · Pub. L. 116-258 · 134 Stat. 1152
A history note hasn’t been published yet. The record shows enactment by Pub. L. 116-258 on 2020-12-23.
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