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OpenAI GPT-3.5

GPT-3.5 is a set of models that improve on GPT-3 and can understand as well as generate natural language or code. It is an autoregressive language model (LLM) from OpenAI that uses deep learning to produce human-like text. It is a fine-tuned version of GPT-3, the third-generation language prediction model in the GPT series created by OpenAI. GPT-3.5 has garnered significant attention and acclaim for its unparalleled ability to understand and generate human-like text. With an astounding 175 billion parameters at its disposal, GPT-3.5 stands as one of the most expansive and powerful language models ever constructed at the time of its release.

GPT-3.5's exceptional performance is not only limited to its sheer size but also stems from its highly refined architecture. Harnessing the power of deep learning, GPT-3.5 delivers consistently accurate and relevant results, elevating the standard for language models and establishing itself as a trailblazer in the field of artificial intelligence.

General
Relese dateMarch 15, 2022
AuthorOpenAI
TypeAutoregressive, Transformer, Language model

Start building with OpenAI GPT-3.5

OpenAI GPT-3 has a rich ecosystem of libraries and resources to help you get started. We have collected the best GPT-3.5 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.

OpenAI GPT-3.5 Tutorials

OpenAI GPT-3.5 Boilerplates

Kickstart your development with a GPT-3.5 based boilerplate. Boilerplates is a great way to headstart when building your next project with GPT-3.


OpenAI GPT-3.5 Libraries

A curated list of libraries and technologies to help you build great projects with GPT-3.5.


OpenAI GPT-3.5 AI technology Hackathon projects

Discover innovative solutions crafted with OpenAI GPT-3.5 AI technology, developed by our community members during our engaging hackathons.

Chatty Shoes

Chatty Shoes

Chatty Shoes is designed with a highly responsive, scalable and robust backend, leveraging state-of-the-art technology to facilitate user-friendly online shoe shopping via natural language interactions. The backbone of the system is a serverless architecture based on Cloud Functions. This decentralised structure comprises three primary functions: Session Creation, Message Management and Information Retrieval. Session Creation: This function is responsible for initiating conversations with customers. Every conversation represents a unique session, providing the framework for interactive and dynamic dialogues. The data from these sessions, including the conversation history, is securely stored in Firestore, ensuring a persistent and seamless user experience across different sessions. Message Management: Powering the heart of the conversation is a GPT-3.5-turbo, a language model renowned for its ability to understand and generate human-like text. This feature enables Chatty Shoes to handle Frequently Asked Questions (FAQs) within the context of the conversation, thereby giving users instant responses to their queries. Additionally, it provides the AI agent with the ability to perform information retrieval operations on products when the system deems it necessary, making it proactive and more engaging. Information Retrieval: The last key component of the backend is the Semantic Search function, which operates over Pinecone's vectorial database. This feature enhances Chatty Shoes' product recommendation abilities by retrieving product data based on the contextual understanding of user inputs rather than merely keyword matching. This means the AI can effectively understand and respond to nuanced customer preferences, thus improving their overall shopping experience. Together, these elements synergise to create a powerful backend that underpins Chatty Shoes' mission: to revolutionize online shoe shopping by facilitating better, deeper and more intuitive conversations.