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Netflix explica cómo interviene la IA para el éxito de sus series

diciembre 13, 2020

Ningún título de Netflix es fortuito, tiene detrás una gran investigación y el uso del aprendizaje automático para determinar su éxito, así lo dice la misma compañía de Los Gatos, California.

Reconoce que en el proceso hay mucho en juego, ya que las producciones o el contenido original no son nada baratos. “Los ejecutivos de la industria del entretenimiento siempre han consultado datos históricos para ayudar a caracterizar a la posible audiencia de un título utilizando producciones comparables, si existen”, precisa.

Netflix indica que dos preguntas clave en este esfuerzo son:

  • ¿Qué títulos existentes son comparables y de qué manera?
  • ¿Qué tamaño de audiencia se puede esperar y en qué regiones?

La plataforma de streaming se basa en el aprendizaje por transferencia, en el que los parámetros aprendidos de una “tarea de origen” mejoran el rendimiento de una “tarea de destino”. Las tareas de origen están representadas por las dos anteriores preguntas.

La firma crea un “mapa de similitud” en el que la inteligencia artificial utiliza los metadatos, las etiquetas y los resúmenes de un programa, los cuales ayudan a determinar los enlaces a otros títulos.

Con los tamaños de audiencia, el servicio tiene un modelo de inteligencia artificial que compara los tamaños de público de trabajos similares en un país determinado. Si es probable que un drama tenga un buen desempeño en España, no solo se incrementará la publicidad en la región, sino que preparará doblajes y subtítulos antes.

Los sistemas se supervisan por sí mismos, lo que les permite acceder a una gama de títulos mucho más amplia.

Al final, reconoce Netflix, el éxito de sus títulos lo determinan sus miembros, aunque se debe hacer todo lo posible para satisfacer sus necesidades, dadas las herramientas y los datos con los que cuenta.

“Identificamos dos formas de apoyar a los tomadores de decisiones de contenido: sacar a la luz títulos similares y predecir el tamaño de la audiencia, al tomar en cuenta diversas área como el aprendizaje por transferencia, la incorporación de representaciones, el procesamiento de lenguaje natural y el aprendizaje supervisado”, resume el servicio.

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