{"id":12825,"date":"2024-06-12T10:19:09","date_gmt":"2024-06-12T10:19:09","guid":{"rendered":"https:\/\/dailyai.com\/?p=12825"},"modified":"2024-06-13T22:25:48","modified_gmt":"2024-06-13T22:25:48","slug":"googles-search-engine-experience-sge-threatens-to-scale-ais-environmental-impacts","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2024\/06\/googles-search-engine-experience-sge-threatens-to-scale-ais-environmental-impacts\/","title":{"rendered":"Search Engine Experience (SGE) de Google podr\u00eda acelerar el impacto medioambiental de la IA"},"content":{"rendered":"

En la \u00faltima conferencia insignia de Google, I\/O, la empresa dio un paso m\u00e1s en su Experiencia Generativa de B\u00fasqueda (SGE), que integrar\u00e1 la IA generativa en la B\u00fasqueda de Google.\u00a0<\/b><\/p>\n

SGE, cuyo objetivo es ofrecer respuestas generadas por IA a m\u00e1s de mil millones de usuarios para finales de 2024, se basa en Gemini, la familia de grandes modelos ling\u00fc\u00edsticos (LLM) de Google, para generar respuestas de tipo humano a las consultas de b\u00fasqueda.<\/span><\/p>\n

En lugar de una b\u00fasqueda tradicional en Google, que muestra principalmente enlaces, se te presentar\u00e1 un resumen generado por la IA junto con otros resultados.<\/p>\n

\"SGE\"
SGE incorpora texto generado por IA a los resultados de las b\u00fasquedas.<\/figcaption><\/figure>\n

Esta \"visi\u00f3n general de la IA\" ha sido criticada por proporcionar informaci\u00f3n sin sentido<\/a>y Google est\u00e1 trabajando r\u00e1pidamente en soluciones antes de iniciar el despliegue masivo.<\/p>\n

Pero aparte de recomendar a\u00f1adir pegamento a la pizza y decir que las pitones son mam\u00edferos, hay otro problema con la nueva estrategia de b\u00fasqueda de Google basada en la inteligencia artificial: su huella medioambiental.\u00a0<\/span><\/p>\n

Por qu\u00e9 el GEE requiere muchos recursos<\/h2>\n

Mientras que los motores de b\u00fasqueda tradicionales se limitan a recuperar informaci\u00f3n existente en Internet, los sistemas de IA generativa como SGE deben crear contenidos totalmente nuevos para cada consulta. <\/span><\/p>\n

Este proceso requiere mucha m\u00e1s potencia de c\u00e1lculo y energ\u00eda que los m\u00e9todos de b\u00fasqueda convencionales.<\/span><\/p>\n

Se calcula que cada d\u00eda se realizan entre 3.000 y 10.000 millones de b\u00fasquedas en Google. Las repercusiones de aplicar la IA a un peque\u00f1o porcentaje de esas b\u00fasquedas podr\u00edan ser incre\u00edbles.\u00a0<\/span><\/p>\n

Sasha Luccioni, investigador de la empresa de IA Hugging Face que estudia el impacto medioambiental de estas tecnolog\u00edas, habl\u00f3 recientemente del fuerte aumento del consumo de energ\u00eda que podr\u00eda desencadenar SGE. <\/span><\/p>\n

Luccioni y su equipo calculan que generar informaci\u00f3n de b\u00fasqueda con IA podr\u00eda requerir 30 veces m\u00e1s energ\u00eda que una b\u00fasqueda convencional.<\/span>\u00a0<\/span><\/p>\n

\"Tiene sentido, \u00bfverdad? Mientras que una consulta de b\u00fasqueda mundana encuentra datos existentes en Internet, aplicaciones como AI Overviews deben crear informaci\u00f3n totalmente nueva\". <\/span>declar\u00f3 a Scientific American<\/span><\/a>.\u00a0<\/span><\/p>\n

En 2023, Luccioni y sus colegas descubrieron que el entrenamiento del LLM BLOOM emit\u00eda gases de efecto invernadero equivalentes a 19 kilogramos de CO2 por d\u00eda de uso, o la cantidad generada por conducir 49 millas en un coche de gasolina medio. Tambi\u00e9n descubrieron que generar<\/span>\u00a0s\u00f3lo dos im\u00e1genes utilizando la IA puede consumir tanta energ\u00eda como la carga completa de un smartphone medio.<\/span><\/p>\n

Estudios anteriores estimaban que las emisiones de CO2 asociadas al entrenamiento de un modelo de IA podr\u00edan superar las de cientos de vuelos comerciales o las de un coche medio a lo largo de su vida \u00fatil.<\/p>\n

\"Consumo
Impacto del CO2 en la formaci\u00f3n de modelos de IA. Fuente: MIT<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span> Revista de Tecnolog\u00eda<\/a>.<\/figcaption><\/figure>\n

En un <\/span>entrevista con Reuters el a\u00f1o pasado<\/span><\/a>El propio John Hennessy, presidente de la empresa matriz de Google, Alphabet, admiti\u00f3 el aumento de los costes asociados a las b\u00fasquedas basadas en IA.\u00a0<\/span><\/p>\n

\"Un intercambio con un gran modelo ling\u00fc\u00edstico podr\u00eda costar diez veces m\u00e1s que una b\u00fasqueda tradicional\", afirm\u00f3, aunque predijo que los costes disminuir\u00e1n a medida que se afinen los modelos.<\/span><\/p>\n

La b\u00fasqueda de inteligencia artificial sobrecarga infraestructuras y recursos<\/h2>\n

Se prev\u00e9 que los centros de datos que albergan servidores de IA dupliquen su consumo de energ\u00eda de aqu\u00ed a 2026, pudiendo llegar a utilizar tanto <\/span>poder como pa\u00eds peque\u00f1o<\/span><\/a>.\u00a0<\/span><\/p>\n

Con fabricantes de chips como NVIDIA sacando al mercado chips m\u00e1s grandes y potentes, pronto podr\u00eda tomar el <\/span>equivalente a varias centrales nucleares<\/span><\/a> para ejecutar cargas de trabajo de IA a gran escala.\u00a0\u00a0<\/span><\/p>\n

Cuando las empresas de IA responden a las preguntas sobre c\u00f3mo puede sostenerse esto, suelen citar la mayor eficiencia y capacidad de las energ\u00edas renovables y la mayor eficiencia energ\u00e9tica del hardware de IA.\u00a0<\/span><\/p>\n

Sin embargo, la transici\u00f3n a fuentes de energ\u00eda renovables para los centros de datos est\u00e1 resultando lenta y compleja.\u00a0<\/span><\/p>\n

Como explica Shaolei Ren, ingeniero inform\u00e1tico de la Universidad de California en Riverside que estudia la IA sostenible, \"hay un desajuste entre la oferta y la demanda de energ\u00edas renovables. La naturaleza intermitente de la producci\u00f3n de energ\u00eda renovable a menudo no se ajusta a la potencia constante y estable que necesitan los centros de datos.\"<\/span><\/p>\n

Debido a este desajuste, las centrales de combustibles f\u00f3siles se mantienen en funcionamiento m\u00e1s tiempo del previsto en zonas con alta concentraci\u00f3n de infraestructuras tecnol\u00f3gicas.\u00a0<\/span><\/p>\n

Otra soluci\u00f3n a los problemas energ\u00e9ticos reside en el hardware de IA de bajo consumo. NVIDIA nuevo chip Blackwell<\/a> es muchas veces m\u00e1s eficiente energ\u00e9ticamente que sus predecesores, y otras empresas como Delta<\/a> trabajan en un hardware eficiente para centros de datos.<\/p>\n

Rama Ramakrishnan, profesor de la Sloan School of Management del MIT, explic\u00f3 que, aunque es probable que aumente el n\u00famero de b\u00fasquedas que pasan por los LLM, el coste por consulta parece disminuir a medida que las empresas se esfuerzan por hacer m\u00e1s eficientes el hardware y el software.<\/span><\/p>\n

Pero, \u00bfser\u00e1 suficiente para compensar la creciente demanda de energ\u00eda?\u00a0<\/span>\"Es dif\u00edcil de predecir\", afirma Ramakrishnan. \"Mi opini\u00f3n es que probablemente subir\u00e1, pero no de forma dr\u00e1stica\".<\/span><\/p>\n

A medida que se acelera la carrera de la IA, se hace necesario mitigar el impacto ambiental. La necesidad es la madre de la invenci\u00f3n, y las empresas tecnol\u00f3gicas est\u00e1n bajo presi\u00f3n para crear soluciones que mantengan el impulso de la IA.<\/p>\n

Hardware energ\u00e9ticamente eficiente, energ\u00edas renovables y incluso la energ\u00eda de fusi\u00f3n<\/a> puede allanar el camino hacia un futuro m\u00e1s sostenible para la IA, pero el trayecto est\u00e1 plagado de incertidumbres.<\/p>\n

La SGE tambi\u00e9n podr\u00eda forzar el suministro de agua<\/h2>\n

Tambi\u00e9n podemos especular sobre las demandas de agua creadas por SGE, que podr\u00edan reflejar los enormes aumentos en el consumo de agua de los centros de datos atribuidos a la industria de la IA generativa.\u00a0<\/span><\/p>\n

Seg\u00fan recientes informes medioambientales de Microsoft, el consumo de agua ha <\/span>se dispar\u00f3 hasta 50%<\/span><\/a> en algunas regiones, con el consumo de agua del centro de datos de Las Vegas duplic\u00e1ndose desde 2022. Los informes de Google tambi\u00e9n registraron un aumento de 20% en el gasto de agua de los centros de datos en 2023 en comparaci\u00f3n con 2022.\u00a0<\/span><\/p>\n

Ren atribuye la mayor parte de este crecimiento a la IA, afirmando: \"Es justo decir que la mayor parte del crecimiento se debe a la IA, incluida la fuerte inversi\u00f3n de Microsoft en IA generativa y la asociaci\u00f3n con OpenAI.\"<\/span><\/p>\n

Ren calcula que cada interacci\u00f3n con ChatGPT, consistente en entre 5 y 50 avisos, consume la asombrosa cantidad de 500 ml de agua.\u00a0<\/span><\/p>\n

En un <\/span>papel<\/span><\/a> publicado en 2023, el equipo de Ren escribi\u00f3: \"La demanda mundial de IA puede ser responsable de entre 4.200 y 6.600 millones de metros c\u00fabicos de extracci\u00f3n de agua en 2027, lo que es m\u00e1s que la extracci\u00f3n total anual de agua de entre 4 y 6 Dinamarca o la mitad del Reino Unido\".<\/span><\/p>\n

A partir de la investigaci\u00f3n de Ren, podemos hacer algunos c\u00e1lculos sobre c\u00f3mo podr\u00eda influir el SGE de Google en estas predicciones.<\/span><\/p>\n

Supongamos que Google procesa una media de 8.500 millones de b\u00fasquedas diarias en todo el mundo. Suponiendo que incluso una fracci\u00f3n de estas b\u00fasquedas, digamos 10%, utilice SGE y genere respuestas impulsadas por IA con una media de 50 palabras por respuesta, el consumo de agua podr\u00eda ser fenomenal.<\/span><\/p>\n

Utilizando la estimaci\u00f3n de Ren de 500 mililitros de agua por cada 5 a 50 b\u00fasquedas (digamos, una sola sesi\u00f3n en Google SGE), podemos calcular aproximadamente que 850 millones de b\u00fasquedas impulsadas por SGE (10% de las b\u00fasquedas diarias de Google) consumir\u00edan unos 425 millones de litros de agua al d\u00eda.\u00a0<\/span><\/p>\n

Esto equivale al diario<\/em> consumo de agua de una ciudad de m\u00e1s de 2,5 millones de habitantes.<\/span><\/p>\n

En realidad, el consumo real de agua puede variar en funci\u00f3n de factores como la eficiencia de los centros de datos de Google y la implantaci\u00f3n y escala espec\u00edficas de SGE. <\/span><\/p>\n

No obstante, es muy razonable especular con que SGE y otras formas de b\u00fasqueda de IA aumentar\u00e1n a\u00fan m\u00e1s el uso de recursos de la IA.\u00a0<\/span><\/p>\n

\u00bfSer\u00e1n sostenibles a gran escala experiencias globales de IA como SGE? Hay numerosos factores en juego, pero no ser\u00e1 nada f\u00e1cil.\u00a0\u00a0<\/span><\/p>","protected":false},"excerpt":{"rendered":"

En la \u00faltima conferencia insignia de Google, I\/O, la empresa dio un paso m\u00e1s en su Experiencia Generativa de B\u00fasqueda (SGE), que integrar\u00e1 la IA generativa en la B\u00fasqueda de Google. SGE, que pretende ofrecer respuestas generadas por IA a m\u00e1s de mil millones de usuarios para finales de 2024, se basa en Gemini, la familia de grandes modelos ling\u00fc\u00edsticos (LLM) de Google, para generar respuestas de tipo humano a las consultas de b\u00fasqueda. En lugar de una b\u00fasqueda tradicional en Google, que muestra principalmente enlaces, se te presentar\u00e1 un resumen generado por la IA junto con otros resultados. Este \"resumen de IA\" ha sido criticado por proporcionar informaci\u00f3n sin sentido, y Google est\u00e1 trabajando r\u00e1pidamente en soluciones antes de que empiece a masificarse.<\/p>","protected":false},"author":2,"featured_media":12826,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[306,102],"class_list":["post-12825","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-environment","tag-google"],"yoast_head":"\nGoogle's Search Engine Experience (SGE) could accelerate AI's environmental impacts | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/es\/2024\/06\/googles-search-engine-experience-sge-threatens-to-scale-ais-environmental-impacts\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Google's Search Engine Experience (SGE) could accelerate AI's environmental impacts | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Google\u2019s latest flagship I\/O conference saw the company double down on its Search Generative Experience (SGE) \u2013 which will embed generative AI into Google Search.\u00a0 SGE, which aims to bring AI-generated answers to over a billion users by the end of 2024, relies on Gemini, Google’s family of large language models (LLMs), to generate human-like responses to search queries. 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