doi.bio/henrique_ponde_de_oliveira_pinto

Henrique Ponde de Oliveira Pinto

Biography

Henrique Ponde de Oliveira Pinto is a researcher in the field of machine learning and AI. He has contributed to several notable projects and publications in the field.

Education

There is no explicit information about his educational background, but he likely holds an advanced degree in computer science, machine learning, or a related field.

Career and Research

Pinto has worked with OpenAI, a non-profit AI research company, on their project Codex. This project aims to use machine learning to generate code automatically, interpreting natural language text and creating executable code. Pinto was one of the researchers who evaluated the performance of Codex, which was trained on code examples from GitHub.

He was also part of the OpenAI team that developed an AI system that defeated world champions at an esports game, Dota 2, using large-scale deep reinforcement learning. This was a significant milestone in the field of AI, showcasing the potential of reinforcement learning in complex environments.

Publications

Pinto has co-authored several publications, including:

Current and Past Affiliations

Conclusion

Henrique Ponde de Oliveira Pinto is a researcher in the field of machine learning and AI, with a focus on code generation and reinforcement learning. He has contributed to significant projects at OpenAI and continues to advance the field through his research and publications.

Henrique Ponde de Oliveira Pinto

Biography

Henrique Ponde de Oliveira Pinto is a scientific researcher who has worked with OpenAI.

Publications

In 2019, Pinto and 24 other researchers published "Dota 2 with Large Scale Deep Reinforcement Learning", detailing how OpenAI Five became the first AI system to defeat the world champions at an esports game. The paper covers how the AI system overcame challenges such as long time horizons, imperfect information, and complex, continuous state-action spaces.

In another paper, "Evaluating Large Language Models Trained on Code", Pinto and 56 other researchers introduced Codex, a GPT language model fine-tuned on publicly available code from GitHub, and studied its Python code-writing capabilities. They found that repeated sampling from the model was an effective strategy for producing solutions to difficult prompts and discussed the potential broader impacts of deploying powerful code generation technologies.

Pinto has also contributed to research in robotic manipulation, co-authoring a paper titled "Asymmetric self-play for automatic goal discovery in robotic manipulation". This work involved training a single, goal-conditioned policy to solve various robotic manipulation tasks, including those with previously unseen goals and objects, through asymmetric self-play.

Youtube Videos

Youtube Title: Stories from Home - I. Largo | Cello Duo | with Matias de Oliveira Pinto

Youtube Link: link

Youtube Channel Name: Nicklas Erpenbach

Youtube Channel Link: https://www.youtube.com/@nicklaserpenbach5723

Stories from Home - I. Largo | Cello Duo | with Matias de Oliveira Pinto

Youtube Title: Künsche - Bachkonzert - Matias de Oliveira Pinto

Youtube Link: link

Youtube Channel Name: Virtuelle-Landpartie

Youtube Channel Link: https://www.youtube.com/@virtuelle-landpartie4754

Künsche - Bachkonzert - Matias de Oliveira Pinto