New AI Features is available now which is introduced by OpenAI

At a developer event in San Francisco, OpenAI introduced several updates to its API services aimed at enhancing customization, developing speech-based applications, reducing pricing for repetitive prompts, and improving the efficiency of smaller models. Four key updates were announced, including a new feature called RealTime and enhancements to model distillation, prompt caching, and vision fine-tuning.

One of the most notable updates is the introduction of Model Distillation, a process that fine-tunes smaller models by training them with outputs from larger models. OpenAI has streamlined this once complex, error-prone process by integrating a distillation suite within its API platform, making it easier for developers to generate datasets, fine-tune smaller models, and evaluate their performance. As an incentive, OpenAI is offering free training tokens through October to help developers get started with distillation.

Another significant update is the introduction of Prompt Caching, which aims to lower the cost of API services. Many applications use lengthy prompts that guide models on how to respond. These prefixes, while useful, can increase costs. OpenAI’s new feature will cache these common prompts for up to an hour, applying a discount when similar prompts are used within that period, helping developers cut expenses.

Additionally, OpenAI has extended the ability to fine-tune models using images in conjunction with text. This vision fine-tuning feature is expected to enhance the model’s capacity to understand and recognize images, which could be useful in fields like autonomous driving, medical image analysis, and visual search applications.

Lastly, the introduction of RealTime is a game-changer for building speech-to-speech applications. Previously, developers needed to use multiple applications to transcribe audio, process it, and convert it back into speech, which often led to latency issues. With the RealTime API, audio is now processed directly, resulting in faster and more responsive interactions, allowing developers to build advanced, real-time voice applications without sacrificing quality. This API is expected to handle more complex multimodal tasks, including video, in the future.