publications

Highlights of my intellectual work.

2024

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    Can AI Scaling Continue Through 2030?
    Jaime Sevilla, Tamay Besiroglu, Ben Cottier, and 4 more authors
    2024
    Accessed: 2024-10-10
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    Will we run out of data? Limits of LLM scaling based on human-generated data
    Pablo Villalobos, Anson Ho, Jaime Sevilla, and 3 more authors
    2024
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  3. compute-growth2024.png
    Training Compute of Frontier AI Models Grows by 4-5x per Year
    Jaime Sevilla, and Edu Roldán
    2024
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    Algorithmic progress in language models
    Anson Ho, Tamay Besiroglu, Ege Erdil, and 6 more authors
    2024
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  5. Revisión sistemática de taxonomías de riesgos asociados a la Inteligencia Artificial
    Guillem Bas Graells, Roberto Tinoco Devia, Luz Claudette Salinas Leyva, and 1 more author
    Analecta Política, Feb 2024

2023

  1. Informe Gestion de riesgos de la Inteligencia Artificial en España
    Guillem Bas Graells, Roberto Tinoco, Jaime Sevilla Molina, and 2 more authors
    Feb 2023
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    Please Report Your Compute
    J. Sevilla, A. Ho, and T. Besiroglu
    Communications of the ACM, Feb 2023
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  3. Power-Law Trends in Speedrunning and Machine Learning
    E. Erdil, and J. Sevilla
    arXiv, Feb 2023
  4. Seguridad alimentaria en Argentina en caso de un Escenario de Reducción Abrupta de la Luz Solar (ERALS) PROPUESTA ESTRATÉGICA
    Jorge Torres Celis, Mónica Ulloa Ruiz, Daniela Tiznado, and 6 more authors
    Feb 2023

2022

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    Parameter, Compute and Data Trends in Machine Learning
    Epoch
    Feb 2022
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  2. A Bayesian model of records
    Jaime Sevilla, and Jonathan Lindbloom
    May 2022
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  4. Machine Learning Model Sizes and the Parameter Gap
    P. Villalobos, J. Sevilla, T. Besiroglu, and 3 more authors
    arXiv, May 2022
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    Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning
    P. Villalobos, J. Sevilla, L. Heim, and 3 more authors
    arXiv, May 2022
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2021

  1. Modelling a Time Series of Records with PyMC3 ~ ~
    Jaime Sevilla, and Jonathan Lindbloom
    Sep 2021
  2. Finding, scoring and explaining arguments in Bayesian Networks
    J. Sevilla
    arXiv, Sep 2021

2020

  1. Forecasting timelines of quantum computing
    J. Sevilla, and C.J. Riedel
    arXiv, Sep 2020

2019

  1. CTLearn: Deep Learning for Gamma-ray Astronomy
    Daniel Nieto Castaño, Ari Brill, Qi Feng, and 5 more authors
    In Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019), Jul 2019
  2. Implications of quantum computing for artificial intelligence alignment research
    J. Sevilla, and P. Moreno
    arXiv, Jul 2019