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.
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.
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.
Pinto has co-authored several publications, including:
Henrique Ponde de Oliveira Pinto is a scientific researcher who has worked with OpenAI.
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 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