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Introducing ChatGPT and Whisper APIs

Builders can now easily embed state-of-the-art conversational and speech capabilities into their own products, reducing development time and operational overhead.

OpenAI Blog··1 min readrelease
releaseIntroducing ChatGPT and Whisper APIs
openai.com

What happened

OpenAI has launched commercial APIs for its ChatGPT and Whisper models, as announced on their blog. The ChatGPT API makes the GPT-3.5-turbo model available to developers, enabling them to integrate conversational AI into their applications without managing infrastructure. The Whisper API provides speech-to-text capabilities using the Whisper large-v2 model, supporting multiple languages. This move lowers the barrier for developers to add natural language and audio processing features. For builders, the key takeaway is the ability to embed powerful AI interactions directly into workflows, with pay-as-you-go pricing. The ChatGPT API's competitive cost compared to previous models offers an accessible entry point for experimentation. Developers should consider how these APIs can enhance user interfaces, automate customer support, or transcribe meeting notes. While OpenAI has offered models before, the dedicated API for ChatGPT streamlines integration and opens new possibilities for AI-driven applications.

Key takeaways

  • OpenAI released dedicated APIs for ChatGPT (GPT-3.5-turbo) and Whisper (speech-to-text).
  • The ChatGPT API allows developers to integrate conversational AI into apps with a managed endpoint.
  • Whisper API supports transcription in multiple languages from audio clips.
  • Pricing is per-token for ChatGPT and per-minute for Whisper, making it cost-effective for scaling.
  • This expands the toolset for building AI workflows that need natural language processing or audio transcription.

Why it matters

Builders can now easily embed state-of-the-art conversational and speech capabilities into their own products, reducing development time and operational overhead.

This is an original editorial digest by AI Workflow Pro. Full reporting at the source:

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