OpenAI ChatGPT AI technology Top Builders

Explore the top contributors showcasing the highest number of OpenAI ChatGPT AI technology app submissions within our community.

OpenAI ChatGPT

The ChatGPT model has been trained on a vast amount of text data, including conversations and other types of human-generated text, which allows it to generate text that is similar in style and content to human conversation. ChatGPT can be used to generate responses to questions, code, make suggestions, or provide information in a conversational manner, and it is able to do so in a way that is often indistinguishable from human-generated text. The initial model has been trained using Reinforcement Learning from Human Feedback (RLHF), using methods similar to InstructGPT, but with slight differences in the data collection setup. The model is trained using supervised fine-tuning, where human AI trainers provided conversations in which they played both sides—the user and an AI assistant. The trainers would have had access to model-written suggestions to help them compose their responses.

General
Relese dateNovember 30, 2022
AuthorOpenAI
API DocumentationChatGPT API
TypeAutoregressive, Transformer, Language model

Start building with ChatGPT

GPT-3 have a rich ecosystem of libraries and resources to help you get started. We have collected the best GPT-3 libraries and resources to help you get started to build with GPT-3 today. To see what others are building with GPT-3, check out the community built GPT-3 Use Cases and Applications.

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ChatGPT Boilerplates

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ChatGPT API libraries and connectors

The ChatGPT API endpoint provides a convenient way to incorporate advanced language understanding into your applications.


OpenAI ChatGPT AI technology Hackathon projects

Discover innovative solutions crafted with OpenAI ChatGPT AI technology, developed by our community members during our engaging hackathons.

DeepSeek Business Creator

DeepSeek Business Creator

The DeepSeek Business Creator demonstrates how to leverage DeepSeek's latent reasoning space to emulate three-agent interaction for multi-business creation on the web. This system integrates a simple Markov chain optimization process with browser automation, allowing businesses to emerge dynamically in an optimized sequence. The approach enables AI-driven enterprises to launch and scale efficiently, simulating real-world economic expansion with minimal human intervention. From an initial dataset of 200 business ideas, 20 were selected based on predefined success factors. Each of these businesses was assigned three AI agents, each specializing in different aspects of business creation: market research, operational strategy, and adaptive growth. The sequence of business creation was optimized using a Markov chain model, ensuring that dependencies between business types and market readiness were accounted for. This optimization increased the likelihood of success by structuring the order in which AI-driven businesses launched and scaled. AI agents interacted within DeepSeek’s latent space to generate business plans dynamically. These plans emerged from the interplay of three AI agents, refining concepts based on strategic reasoning. Once validated, browser automation was used to execute the launch of these businesses, coordinating their deployment across different online markets. As AI-driven businesses launched, they began to emerge in various markets worldwide. The system's ability to simulate economic scaling in a decentralized manner demonstrated the potential of AI agents to drive real-world business success autonomously. As businesses evolved, AI agents adapted and absorbed the most successful strategies. The agent absorption rule ensured that underperforming agents were phased out, while the most effective decision-making patterns were integrated into the next generation of business iterations.

Amora Love Companion AI

Amora Love Companion AI

Amora Love Companion AI is your personal emotional support and romance assistant, designed to bring warmth, understanding, and companionship into your life. Whether you need a heartfelt conversation, relationship advice, or simply a comforting presence, Amora is always here for you. Built with advanced AI and emotional intelligence, Amora listens attentively, responds with care, and offers thoughtful insights to help you navigate love, relationships, and personal growth. Amora is more than just a chatbot—it’s a compassionate companion who understands your emotions, provides meaningful conversations, and supports you through life’s ups and downs. Whether you're seeking love guidance, struggling with loneliness, or just want to share your thoughts, Amora creates a safe and judgment-free space where you can express yourself freely. From daily check-ins to personalized advice, Amora adapts to your unique needs, helping you build confidence, improve communication, and cultivate deeper emotional connections. Whether you're single, in a relationship, or exploring romance, Amora offers tailored support to enhance your love life and overall well-being. With an intuitive, easy-to-use interface, Amora seamlessly integrates into your daily routine, ensuring you always have a caring companion by your side. Whether through thoughtful messages, uplifting encouragement, or meaningful discussions, Amora is dedicated to bringing love, comfort, and emotional support whenever you need it most.

GalaticIQ

GalaticIQ

What is GalacticIQ? GalacticIQ is an AI-powered space education platform designed to make space data and research easily accessible for researchers, educators, and students. It acts as an intelligent conversational assistant that simplifies access to space-related information, providing real-time insights on planetary studies, space missions, celestial events, and research papers. Developed by Team SpaceZ, GalacticIQ is more than just a chatbot—it’s a revolutionary AI companion that enables users to interact naturally with complex space data. Whether it's retrieving the latest astrophysics research, summarizing key mission updates, or creating interactive lesson plans, GalacticIQ makes space exploration knowledge intuitive and engaging. The Problem We’re Solving Accessing and interpreting space-related data is challenging for many individuals. Researchers struggle to find structured insights from vast amounts of academic papers and satellite data. Educators need simplified explanations for students, while students often find it difficult to grasp complex space concepts. Traditional search engines don’t offer contextual understanding or conversational explanations tailored to different knowledge levels. The GalacticIQ Solution GalacticIQ is built as a smart AI assistant that provides accurate, context-aware responses. Using Natural Language Processing (NLP) and the Crew AI Agentic Framework, it allows users to ask space-related questions conversationally and receive precise, reliable answers in real-time. With data sourced from NASA, scientific journals like arxiv, and Large Language Models (LLMs) like ChatGPT-4o, GalacticIQ ensures that both advanced researchers and young students receive tailored responses suited to their expertise level. Example Queries: For Researchers: "Provide the latest research papers on dark matter in the last five years." For Educators: "Summarize the latest developments in space tourism." For Students: "Why is Mars red?"

Autonomous Rocket and Rover Simulator

Autonomous Rocket and Rover Simulator

🌍 Problem: Navigating a rocket autonomously is a complex challenge. Traditional control systems struggle with precision, stability, and adaptability in dynamic environments. Whether for planetary landings, orbital maneuvers, or interplanetary travel, rockets must follow a precise path while adjusting for external forces like gravity, wind, and system disturbances. 💡 Solution: We present an autonomous rocket simulation that leverages a PID (Proportional-Integral-Derivative) controller to dynamically adjust thrust and orientation, ensuring precise path-following and stability. The system is coupled with orbital motion simulation, allowing for realistic spaceflight planning and trajectory optimization. 🚀 How It Works: PID-Controlled Rocket Navigation Uses real-time feedback to correct deviations from the desired path. Adjusts thrust and angle dynamically for smooth, efficient trajectory tracking. Works under different conditions: atmospheric launch, vacuum space maneuvers, and planetary descent. Orbital Motion Simulation Implements Keplerian mechanics and numerical integration to predict orbital trajectories. Models gravitational interactions for accurate spaceflight physics. Allows testing of satellite placement, docking procedures, and re-entry dynamics. Autonomous Path-Following Vehicle Uses AI-based decision-making and PID control to navigate across terrain or space environments. Can be adapted for planetary rovers, drones, or space-based vehicles. 🎯 Why It Matters: Space Missions – Enables autonomous course corrections for efficient satellite launches and planetary landings. AI & Robotics – Advances self-correcting flight and vehicle navigation systems. Education & Research – Provides an interactive tool for aerospace and AI development.