{"id":4233,"date":"2023-08-12T14:19:47","date_gmt":"2023-08-12T14:19:47","guid":{"rendered":"https:\/\/dailyai.com\/?p=4233"},"modified":"2023-08-17T17:26:18","modified_gmt":"2023-08-17T17:26:18","slug":"ibm-announces-brain-like-ai-chip-with-lower-power-demands","status":"publish","type":"post","link":"https:\/\/dailyai.com\/es\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/","title":{"rendered":"IBM anuncia un chip de inteligencia artificial similar a un cerebro que consume menos energ\u00eda"},"content":{"rendered":"

IBM ha desarrollado un chip bioinspirado que puede hacer que la inteligencia artificial sea m\u00e1s ecol\u00f3gica y eficiente desde el punto de vista energ\u00e9tico.\u00a0<\/b><\/p>\n

A medida que modelos de IA superpotentes como ChatGPT se hacen omnipresentes en toda la sociedad, grandes rivales tecnol\u00f3gicos como Google, Microsoft, Meta y startups como Anthropic e Inflection han empezado a acaparar ingentes cantidades de potencia de c\u00e1lculo.\u00a0<\/span><\/p>\n

El hardware necesario para entrenar la IA consume mucha energ\u00eda, lo que contribuye a la ya enorme <\/span>impacto medioambiental de los centros de datos<\/span><\/a>.\u00a0<\/span><\/p>\n

Esto ha impulsado los esfuerzos de I+D para crear chips de IA innovadores capaces de soportar grandes cargas de trabajo con un menor consumo de energ\u00eda. El \u00faltimo <\/span>Chip GH2000<\/span><\/a> ya ha logrado una mayor eficiencia energ\u00e9tica que sus predecesores, y la empresa afirma que har\u00e1 que los centros de datos sean 12 veces m\u00e1s baratos y consuman 20 veces menos energ\u00eda.\u00a0<\/span><\/p>\n

IBM <\/span>nuevo chip anal\u00f3gico bioinspirado<\/span><\/a> se inspira en el cerebro biol\u00f3gico y ser\u00e1 eficaz en cargas de trabajo port\u00e1tiles como coches, tel\u00e9fonos y c\u00e1maras.\u00a0<\/span><\/p>\n

Thanos Vasilopoulos, cient\u00edfico del laboratorio de investigaci\u00f3n de IBM en Z\u00farich, <\/span>a la BBC<\/span><\/a>\"Comparado con los ordenadores tradicionales, el cerebro humano alcanza un rendimiento notable con un consumo de energ\u00eda m\u00ednimo\".<\/span><\/p>\n

La mayor\u00eda de los chips existentes son digitales y utilizan el binario (0 y 1) para almacenar datos. El nuevo chip de IBM es distinto, ya que utiliza componentes anal\u00f3gicos conocidos como memristores (resistencias de memoria), capaces de almacenar valores num\u00e9ricos variables. <\/span><\/p>\n

La naturaleza anal\u00f3gica de los memristores refleja las funciones sin\u00e1pticas. No es el primer chip bioinspirado: un equipo de investigaci\u00f3n indio logr\u00f3 con \u00e9xito <\/span>dise\u00f1ado uno en 2022<\/span><\/a>.\u00a0<\/span><\/p>\n

El profesor Ferrante Neri, de la Universidad de Surrey, explic\u00f3: \"Los memristores interconectados pueden crear una red que refleje un cerebro biol\u00f3gico\".\u00a0<\/span><\/p>\n

Aunque principalmente anal\u00f3gico, el chip de IBM conserva algunos componentes digitales, lo que garantiza su compatibilidad con los sistemas de IA actuales.\u00a0<\/span><\/p>\n

Estos chips ligeros ser\u00edan especialmente \u00fatiles para gadgets, veh\u00edculos y hardware IoT.\u00a0<\/span><\/p>\n

El nuevo chip anal\u00f3gico de IBM para el aprendizaje profundo<\/span><\/h2>\n

Los chips de IBM reducen el consumo de energ\u00eda al tiempo que ofrecen un rendimiento impresionante en un paquete ligero. <\/span><\/p>\n

Estos chips siguen el modelo del cerebro humano, que consume aproximadamente los mismos vatios que una bombilla.<\/span><\/p>\n

He aqu\u00ed los puntos clave:<\/span><\/p>\n

    \n
  • Limitaciones actuales del hardware de IA<\/b>: La mayor\u00eda de las arquitecturas de IA separan la memoria de las unidades de procesamiento, lo que significa que deben intercambiar datos continuamente entre ambas, ralentizando el c\u00e1lculo y comprometiendo la eficiencia energ\u00e9tica.<\/span><\/li>\n
  • Chips anal\u00f3gicos<\/b>: A imagen y semejanza de las funciones cerebrales humanas, IBM emplea la memoria de cambio de fase (PCM), que registra su estado como un espectro de valores en lugar de 0 y 1. Esto reduce la necesidad de transmisi\u00f3n de datos entre la memoria y el procesador. Esto reduce la necesidad de transmisi\u00f3n de datos entre la memoria y el procesador.<\/span><\/li>\n
  • La parte t\u00e9cnica<\/b>: El dise\u00f1o de IBM incluye 64 n\u00facleos de c\u00e1lculo anal\u00f3gico en memoria, cada uno de ellos con una matriz sin\u00e1ptica de 256 por 256. Cada n\u00facleo puede calcular una capa de modelo de red neuronal profunda (DNN). Cada n\u00facleo puede calcular una capa del modelo de red neuronal profunda (DNN). Una unidad central de procesamiento digital en el chip se encarga de otras operaciones complejas.<\/span><\/li>\n
  • M\u00e9tricas de rendimiento<\/b>: El chip alcanz\u00f3 una excelente precisi\u00f3n de 92,81% en una prueba comparativa de visi\u00f3n por ordenador (CV). Es m\u00e1s de 15 veces m\u00e1s eficiente que varios chips existentes.<\/span><\/li>\n<\/ul>\n

    Una vez perfeccionados, estos chips bioinspirados acompa\u00f1ar\u00e1n a los chips digitales en arquitecturas h\u00edbridas. Esto permitir\u00e1 crear sistemas de IA ligeros y energ\u00e9ticamente eficientes, pero capaces de soportar grandes cargas de trabajo.\u00a0<\/span><\/p>\n

    Con el tiempo, estos chips ser\u00e1n lo bastante ligeros como para desplegarse en tecnolog\u00eda aut\u00f3noma inteligente, lo que podr\u00eda dar paso a una nueva generaci\u00f3n de robots que caminen, hablen e interact\u00faen con su entorno sin un consumo excesivo de energ\u00eda.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    IBM ha desarrollado un chip bioinspirado con el potencial de hacer la IA m\u00e1s ecol\u00f3gica y eficiente desde el punto de vista energ\u00e9tico. A medida que modelos de IA superpotentes como ChatGPT se hacen omnipresentes en la sociedad, grandes rivales tecnol\u00f3gicos como Google, Microsoft, Meta y startups como Anthropic e Inflection han empezado a acaparar enormes cantidades de potencia de c\u00e1lculo. El hardware necesario para entrenar la IA consume mucha energ\u00eda, lo que contribuye al ya de por s\u00ed enorme impacto medioambiental de los centros de datos. Esto ha disparado los esfuerzos de I+D para construir chips de IA innovadores capaces de soportar cargas de trabajo pesadas con un menor consumo de energ\u00eda. El \u00faltimo chip GH2000 de Nvidia ya ha conseguido una mayor eficiencia energ\u00e9tica que sus predecesores.<\/p>","protected":false},"author":2,"featured_media":4234,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[],"class_list":["post-4233","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry"],"yoast_head":"\nIBM announces brain-like AI chip with lower power demands | DailyAI<\/title>\n<meta name=\"description\" content=\"IBM has developed a bio-inspired chip with the potential to make AI greener and more energy-efficient.\u00a0\" \/>\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\/2023\/08\/ibm-announces-brain-like-ai-chip-with-lower-power-demands\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" 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