Exploring practical views of ChatGPT, Azure OpenAI, GPT-3
In this article we shall perform a comprehensive dissection of the buzzwords pertaining to ChatGPT, laying bare their fundamental constituents, and exploring their practical implications within the potential organizations.
Two Key points you can expect from this article
- Understanding differences between various elements of the OpenAI ecosystem,
- Will be more familiar with a version of OpenAI on Microsoft Azure,
- You will discover a difference between the engine and model in OpenAI.
Recently, there has been a lot of buzz on the internet surrounding ChatGPT and other related buzzwords. After a lengthy period of relying on keyword-based search engines like Google and chatbots based on rigidly defined FAQ databases, it is time to push the envelope with human-like experience technology. First and foremost, let us decode the buzzwords.
Buzzwords decoding
Generative AI models are a subset of deep learning models that can produce new content based on what is described in the input. These models are typically built using deep learning techniques such as neural networks, which enable them to learn from vast amounts of data and generate complex, high-dimensional outputs.
The OpenAI is an artificial intelligence research laboratory, which develops generative AI models that can produce language, code, and images. The most popular model developed by OpenAI:
- GPT: Generative Pre-trained Transformer, a family of language models that are designed to generate natural language text.
- DALL-E: A neural network-based generative model that can generate images from textual descriptions.
- Codex: A deep learning model that can generate code from natural language descriptions.
- MuseNet: A deep learning model that generates music in a variety of styles and genres.
And a few additional Deep Learning models.
ChatGPT – ChatGPT is an application/chatbot built on top of the GPT (Generative Pre-trained Transformer) language model, which was developed by OpenAI. ChatGPT is designed to simulate human-like conversations with users and can be trained to perform various tasks such as customer service, personal assistants, or educational applications. It uses natural language processing (NLP) techniques to understand and respond to user queries in a conversational manner, making it a powerful tool for various business and personal use cases.
Generative Pre-trained Transformer (GPT) is a type of language model developed by OpenAI; a research laboratory dedicated to advancing artificial intelligence. It is designed to generate human-like text by predicting the most likely next word or sequence of words based on the input text. The model is pre-trained on massive amounts of text data to develop a deep understanding of the structure and patterns of human language. This enables it to generate coherent and contextually relevant text for a variety of applications, including language translation, text summarization, and chatbot systems.
GPT models use transformer neural network architectures, which have proven to be particularly effective for natural language processing tasks. The most recent version, GPT-3.5, is one of the largest language models ever created and has demonstrated a remarkable ability to perform a wide range of natural language tasks.
Recently, OpenAI announced access to brand new API to models used by ChatGPT – GTP-3.5 models.
Specific engines/models can be selected based on requirements, expectations, and possibilities.
Source for OpenAI Platform Models
!! Currently, at the time of writing this article, GPT-3.5 is restricted to fine-tune based on your own datasets.
Usually, a decision about the algorithm will contain three dimensions – price, quality (accuracy of responses), performance (speed of response)
Azure OpenAI Service – where you can find benefits from this partnership?
The partnership between Microsoft and OpenAI started in 2019 and now is entering in 3rd phase. From the beginning, Microsoft has partnered with OpenAI to deliver on three main goals:
- To utilize Azure’s infrastructure, including security, compliance, and regional availability, to help users build enterprise-grade applications.
- To deploy OpenAI AI model capabilities across Microsoft products, including and beyond Azure AI products.
- To use Azure to power all OpenAI’s workloads.
Azure OpenAI Service is a result of the mentioned partnership. The service combines Azure’s enterprise-grade capabilities with OpenAI’s generative AI model capabilities. This service is available for Azure users and consists of four components:
- Pre-trained generative AI models,
- Customization capabilities: the ability to fine-tune AI models with your own data,
- Built-in tools to detect and mitigate harmful use cases so users can implement AI responsibly,
- Enterprise-grade security with role-based access control (RBAC) and private networks.
Using Azure OpenAI allows you to transition between your work with Azure services and OpenAI while utilizing Azure’s private networking, regional availability, and responsible AI content filtering.
More details in the official documentation:
Azure OpenAI Service supports many common AI workloads which can be categorized into three groups:
- [GPT-3] Generating Natural Language
- Text completion: generate and edit text
- Embeddings: search, classify, and compare text
- [CODEX] Generating Code: generate, edit, and explain code
- [DALL-E] Generating Images: generate and edit images
By using Azure OpenAI Cognitive service, you are building solutions by taking care of critical aspects of responsible AI out of the box.
Once the resource in Azure is created, you can use the service through REST APIs, Python SDK, or the web-based interface in the Azure OpenAI Studio.
Currently, you need to apply for access to Azure OpenAI. Once granted access, you can use the service by creating an Azure OpenAI resource as you would for other Azure services.
You can apply by using this link
One interesting application and combination of Azure OpenAI Service with other Azure services is integration with Azure Cognitive Search as a custom skill to make intelligent text summarization.
Broader description and implementation (Python) have been described and placed on GitHub.
Key Takeaways:
- ChatGPT is an application combining multiple models into one solution. An application that has been built by OpenAI
- Partnership between Microsoft and OpenAI, put the development of such solutions on various levels by delivering highly scalable infrastructure and enterprise-grade security, compliance, and responsible AI mechanism.
- GPT-3 is the latest language model available in Azure OpenAI service. Your decision about quality and performance will determine pricing by selecting the appropriate engine for your needs. GPT-3.5 will be added to the Azure service soon.
