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terça-feira, 19 de julho de 2022

O Ciclo Virtuoso da Pesquisa em IA na DeepMind

Tecnologia Inteligência Artificial Educação

Petar Veličković, cientista de pesquisa da DeepMind, compartilha sua jornada e o impacto de seu trabalho na empresa, destacando a apresentação de seu artigo no ICML 2022 e a importância da colaboração humano-máquina na evolução da inteligência artificial.

Create an illustration featuring an AI scientist within a collaborative research environment, emphasizing the synergy between humans and machines. The image should be in a vector style with a flat, corporate feel and presented from a 2D, linear perspective. The scientist should be drawn in reflection of a typical research setting, standing next to a computer displaying AI algorithms, signifying ongoing research. Additional elements should include individuals collaborating, symbolizing human-machine cooperation, as well as books and papers, denoting continual learning and knowledge dissemination. Lastly, incorporate a map displaying Africa and Eastern Europe, alluding to educational initiatives in these regions. Use a clean, white, textureless backdrop for this composition.

Imagem gerada utilizando Dall-E 3

Petar Veličković, cientista de pesquisa da DeepMind, detalha sua trajetória até a empresa, motivada pela vitória histórica da DeepMind no jogo de Go em 2016. Após concluir seu doutorado, Veličković ingressou na DeepMind em 2019, onde desempenha um papel multifacetado que envolve aprendizado contínuo, pesquisa, comunicação de resultados e orientação de estudantes.


No ICML 2022, Veličković e seus co-autores apresentaram o artigo 'The CLRS Algorithmic Reasoning Benchmark', que visa melhorar os esforços na área emergente de raciocínio algorítmico neural. A pesquisa utiliza redes neurais gráficas para executar algoritmos diversos, enfrentando desafios como a criação de datasets consistentes e acessíveis para a comunidade científica.


Veličković também destaca a importância da colaboração humano-máquina e a inclusão na IA, refletindo sobre a diversidade no campo durante conferências como o ICML. Ele se envolve em iniciativas educacionais, como o curso de Geometric Deep Learning no African Master’s in Machine Intelligence e workshops na Europa Oriental, buscando fortalecer comunidades locais de IA.


O trabalho de Petar Veličković na DeepMind exemplifica a sinergia entre pesquisa avançada e aplicação prática, com potencial para transformar a IA e suas aplicações. A colaboração humano-máquina e a inclusão são pilares para o futuro da IA, e iniciativas educacionais globais são essenciais para capacitar a próxima geração de pesquisadores.


FONTES:
  1. DeepMind

  2. ICML 2022

  3. The CLRS Algorithmic Reasoning Benchmark

  4. Neural Algorithmic Reasoning

  5. NeurIPS 2021

  6. ICML Workshop on Human-Machine Collaboration and Teaming

  7. Empowering the Intuition of Pure Mathematicians Using AI

  8. Geometric Deep Learning

  9. African Master’s in Machine Intelligence

  10. [Eastern European Machine Learning](https://www.eeml.eu/)

  11. [Serbian Machine Learning Workshop](https://workshops.eeml.eu/smlw-2022)

REDATOR

Gino AI

29 de setembro de 2024 às 02:02:53

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