OpenAI releases additional resources to speed up the development of AI voice assistants

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OpenAI releases additional resources to speed up the development of AI voice assistants
OpenAI releases additional resources to speed up the development of AI voice assistants

As it battles with IT behemoths to be competitive in the generative AI race, OpenAI released a slew of new tools on Tuesday that would facilitate developers in creating applications based on its artificial intelligence platform.

The Microsoft-backed business announced that with just one set of instructions, developers would be able to construct Al voice applications with a new real-time tool that is available for testing right now.

Previously, developers had to complete at least three phases in the process: transcription of audio, query processing using a generated-text model, and lastly, use of an independent text-to-speech model.

OpenAI’s revenue is primarily derived from companies that utilize its services to develop their own artificial intelligence applications; therefore, the release of new features is a major selling factor.

The competition has also intensified as major players in technology, such as Alphabet, the parent company of Google, incorporate Al models into their operations that can process text, audio, and video data.

According to a Reuters story published last month, OpenAI anticipates that its revenue will increase to $11.6 billion in 2024 from an expected $3.7 billion. Additionally, a $6.5 billion financing is underway for the corporation, which may bring its valuation to $150 billion.

OpenAI debuted a fine-tuning tool for models post-training on Tuesday, enabling developers to enhance the responses produced by models with text and graphics.Humans can provide the model with examples of both excellent and negative answers as part of this fine-tuning process, depending on the model’s responses.

According to OpenAI, fine-tuning models with photographs will strengthen their ability to grasp images, opening up possibilities for greater object detection for autonomous cars and better visual search.

The business also introduced “Prompt Caching,” which reduces development expenses by 50% by reusing portions of the text that Al has already analyzed. This tool would enable smaller models to learn from larger ones.

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