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    [publishedTime] => 2025-01-28 15:31:12
    [idp] => 3039
    [resumen] => DeepSeek V3 y DeepSeek-R1 son modelos de IA que logran resultados similares a GPT-4 y GPT-3.5 de OpenAI, pero con menos recursos. Utilizan técnicas como DeepSeekMoE, DeepSeekMLA, Auxiliary-Loss-Free Load Balancing, Multi-token Prediction Training Objective, FP8 Mixed Precision Training y Cross-Node All-to-All Communication. El entrenamiento se realizó con 14,8 billones de tokens y se utilizó aprendizaje por refuerzo y destilación de modelos. Los precios de la API de DeepSeek son hasta 35 veces inferiores a los de OpenAI.
    [title] => DeepSeek hace lo mismo que los modelos más avanzados de OpenAI con mucho menos recursos. La clave: "reinforcement learning"
    [respuesta] => La clave es el uso de reinforcement learning
    [what] => eficiencia de DeepSeek
    [image] => 
    [lang] => es
    [uid] => 38989fbf81b20ffc828863667de636e4
    [status] => 8
    [respuesta_en_titulo] => 8
    [conceptos_principales_resumen] => Array
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            [0] => DeepSeekMoE
            [1] => DeepSeekMLA
            [2] => reinforcement learning
            [3] => destilación de modelos
            [4] => 14,8 billones de tokens
            [5] => 35 veces inferiores
        )

    [categoria] => Informática
    [prompt_DALLY] => Illustration of an AI model with a brain and a robot in the background
    [prompt] => Ilustración de un modelo de IA con un cerebro y un robot en el fondo
    [clickbait] => 6
    [im_gen] => KO
    [a_urlDominio] => 
vía  www.xataka.com
    [dominio] => www.xataka.com
    [urlDominio] => https://www.xataka.com/robotica-e-ia/deepseek-hace-modelos-avanzados-openai-mucho-recursos-clave-reinforcement-learning#:~:text=reinforcement%20learning
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