Name: Zacharie Jon Raymond
Type: User
Company: Cartel Finance DAO
Bio: B.A. B.Sc.,
Work: Technology for the betterment of humanity. I don't care about money, I get off on helping, and making people happy.
Twitter: arux_io
Location: Bouctouche
Blog: openai.dojo
Zacharie Jon Raymond's Projects
This is the official website of our work 3D Appearance Super-Resolution with Deep Learning published on CVPR2019.
Agent-LLM, a dynamic AI task management assistant, boasts adaptive memory, web browsing, code evaluation, and a versatile plugin system for seamless integration with various AI providers and models.
Efficient Augmented Reality for the Web - 60fps on mobile!
😎 Awesome list of tools and projects with the awesome LangChain framework
A collection of recent papers on building autonomous agent. Two topics included: RL-based / LLM-based agents.
"Building-Data-Driven-LLM-Applications-with-LlamaIndex, published by Packt"
A Clash GUI based on tauri. Supports Windows, macOS and Linux.
Source codes for the paper "Building Cooperative Embodied Agents Modularly with Large Language Models"
The content behind MDN Web Docs
Transformer related optimization, including BERT, GPT
Forward-Looking Active REtrieval-augmented generation (FLARE)
Code for "GaussianObject: Just Taking Four Images to Get A High-Quality 3D Object with Gaussian Splatting"
Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch
A tutorial/"our experience" in preparing a rpi 3 as a AI Security Drone Brain
Repository for pre-built dev container images published under mcr.microsoft.com/devcontainers
🦜🔗 Build context-aware reasoning applications
Harness LLMs with Multi-Agent Programming
Learn Algorithmic Trading, Published by Packt
An LLM-powered autonomous agent platform
Mastering Reinforcement Learning with Python, published by Packt
Implementation of "Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction"
Implementation of "Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents"
Snap Template
Dataset, code and models for the paper "Mind2Web: Towards a Generalist Agent for the Web".