OpenAI GPT-4 now accessible instantly on Azure Locations

Microsoft has recently released its GPT-4 API to all paying customers without waitlist. Post its initial launch in March, the API underwent closed testing before the final release to the public. The GPT-4 API integrates OpenAI’s large language model (LLM) into user-oriented products for various purposes like summarization, coding support, analysis, and composition.

There have been updates introduced to chat-based models and a shift has been announced from the Completions API to the Chat Completions API. Soon, OpenAI will retire older models, including the Completions API models, and replace them with newer versions.

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For detailed updates and learning resources, Microsoft has furnished information on the legacy models and GPT-3.5 models, as well as an in-depth how-to guide for interacting with GPT-4 and the Chat Completions API.

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The GPT-35-Turbo and GPT-4 models are language models that are optimized for conversational interfaces. The models behave differently than the older GPT-3 models. Previous models were text-in and text-out, meaning they accepted a prompt string and returned a completion to append to the prompt. However, the GPT-35-Turbo and GPT-4 models are conversation-in and message-out. The models expect input formatted in a specific chat-like transcript format, and return a completion that represents a model-written message in the chat. While this format was designed specifically for multi-turn conversations, you'll find it can also work well for non-chat scenarios too.+

As of now, OpenAI’s Chat Completions API models account for 97 percent of OpenAI’s API GPT usage. Microsoft plans to retire models under the Completions API in the next six months, by January 4, 2024. Manual upgrades will be required by developers who are using some of these models.

• Azure OpenAI Service is powered by a diverse cluster of models catering to various needs, at differing price points. The model availability is region-dependent.
• Wide-ranging models that the service provides includes the GPT-4 model, addressing the natural language and code understanding and generation. It is said to solve challenging problems more accurately than OpenAI's prior models.
• Other models include Embeddings, DALL-E (Preview), and Whisper (Preview). Where, the Embeddings models are designed to convert text into numerical vector form to facilitate text similarity, DALL-E can generate unique images from natural language, and Whisper can transcribe and translate speech to text.

To learn more about this topic, Microsoft and OpenAI provide a range of resources such as official API documentation, blog posts on their websites, and online tutorials.

For a deeper understanding and practical experience, developers may benefit from online training courses on platforms like Coursera or Udacity that offer courses on AI, machine learning, and API integration. Additionally, platforms like GitHub often have open-source projects and code that could provide practical implementation details.