How to evaluate Artificial Intelligence?

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  • Опубликовано: 25 июл 2024
  • The state of the art of language models shows that AI still has a long way to go. Researchers are designing new evaluation methods to quantify the performance of Large Language Models (LLM) and identify the limitations and strengths of AI models.
    In this video we explore the new LLM evaluation methods based on the paper "A Survey on Evaluation of Large Language Models" and answer the question of why you should not trust AI.
    Video title: How to evaluate AI?
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    Resources
    - A Survey on Evaluation of Large Language Models: arxiv.org/abs/2307.03109
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    Sections:
    0:00 Introduction
    0:52 Evaluation of AI models
    1:34 What are the tasks that LLMs perform?
    2:06 Performance in NLP tasks
    2:49 Performance in ethics and bias
    3:24 Performance in social sciences
    4:01 Performance in natural sciences and engineering
    4:29 Performance in medicine
    4:48 Performance in agent tasks
    5:23 Performance in other tasks
    6:07 Where to evaluate LLMs?
    7:17 How to evaluate LLMs?
    8:36 Summary of findings in the evaluation of LLMs
    9:58 Conclusions
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    Music:
    Legend Has It - Harris Heller
    Provided by Streambeats
    Listen: open.spotify.com/track/3UN60C...
    Lucky Stars - Harris Heller
    Provided by Streambeats
    Listen: open.spotify.com/track/70f90U...
    Stop The Clock - Harris Heller
    Provided by Streambeats
    Listen: open.spotify.com/track/2fainn...
    No Introduction - Harris Heller
    Provided by Streambeats
    Listen: open.spotify.com/track/4SMBTz...
    Rise Up - Harris Heller
    Provided by Streambeats
    Listen: open.spotify.com/track/4DqeLS...
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    Networks:
    GitHub: github.com/Tibiritabara
    LinkedIn: / ricardosantosdiaz
    Instagram: / tibiritabara90
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    Thanks for watching the video!
    #ai #llm #software
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Комментарии • 6

  • @RicardoSantosDiaz
    @RicardoSantosDiaz  11 месяцев назад +1

    Los LLMs, Large Language Models, o Grandes Modelos de Lenguaje, llegaron para quedarse, pero es necesario antes de su adopción en masa identificar sus graves fallas y riesgos en la sociedad, y dedicar un gran esfuerzo en su mejora y evaluación continua, asegurando su impacto positivo. Debemos aceptar que aún estamos demasiado lejos de ello.

  • @S4z4kku
    @S4z4kku 11 месяцев назад +1

    Muy buena información, se ha glorificado todo lo asociado a IA que no se habla de esos detalles técnicos e importantes que aún no se han cubierto

    • @RicardoSantosDiaz
      @RicardoSantosDiaz  11 месяцев назад

      Ciertamente, hay que mantener una perspectiva objetiva, pero el ruido sensacionalista de la prensa muchas veces es más fuerte

  • @adriipinto
    @adriipinto 11 месяцев назад

    🙌🏽🙌🏽🙌🏽

  • @angelicasantos568
    @angelicasantos568 11 месяцев назад

    wooow

  • @OTTOALACCION28
    @OTTOALACCION28 11 месяцев назад

    Excelente la inteligencia artificial no puede ser mas inteligente que nosotros los seres humanos