Given any text prompt, the API will return a text completion, attempting to match the pattern you gave it. You can “program” it by showing it just a few examples of what you’d like it to do; its success generally varies depending on how complex the task is. The API also allows you to hone performance on specific tasks by training on a dataset (small or large) of examples you provide, or by learning from human feedback provided by users or labelers.
We’ve designed the API to be both simple for anyone to use but also flexible enough to make machine learning teams more productive. In fact, many of our teams are now using the API so that they can focus on machine learning research rather than distributed systems problems. Today the API runs models with weights from the GPT-3 family with many speed and throughput improvements. Machine learning is moving very fast, and we’re constantly upgrading our technology so that our users stay up to date.
In addition to being a revenue source to help us cover costs in pursuit of our mission, the API has pushed us to sharpen our focus on general-purpose AI technology—advancing the technology, making it usable, and considering its impacts in the real world. We hope that the API will greatly lower the barrier to producing beneficial AI-powered products, resulting in tools and services that are hard to imagine today.
Interested in exploring the API? Join companies like Algolia, Quizlet, and Reddit, and researchers at institutions like the Middlebury Institute in our private beta.
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