OpenAI unveils new tools to speed up AI voice assistant creation

ChatGPT maker's new tool comes amid stiff competition from tech industry giants to stay on top in generative AI race

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Reuters
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Web Desk
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A representational picture showing the OpenAI logo displayed on a phone screen on May 20, 2024. — Reuters
A representational picture showing the OpenAI logo displayed on a phone screen on May 20, 2024. — Reuters

In a sigh of relief for developers, OpenAI unveiled a range of of new tools aimed at simplifying the development of applications based on the tech firm's artificial intelligence technology.

The latest move by the ChatGPT maker comes as it faces stiff competition from tech industry giants to stay on top in the generative AI race.

The Microsoft-backed startup said that the new tool, rolling out immediately for testing, will enable developers to create AI voice applications using a single set of instructions, Reuters reported.

This streamlined process eliminates the need for developers to transcribe audio, run a generated-text model to come up with an answer to the query and then use a separate text-to-speech model, as previously required.

The new tool comes when competition in the AI race is heating up as technology giants, including Google-parent Alphabet, have also integrated AI models capable of crunching different forms of information such as video, audio and text across their businesses.

Additionally, as part of Tuesday's rollout, the Sam Altman-owned AI startup introduced a fine-tuning tool for models after training that would allow developers to improve the responses generated by models using images and text.

This fine-tuning process can include feedback from humans who feed the model examples of good and bad answers based on its responses.

Using images to fine-tune models would give them stronger image understanding capabilities, enabling applications such as enhanced visual search and improved object detection for autonomous vehicles, OpenAI said.

The startup also unveiled a tool that would allow smaller models to learn from larger ones, along with "Prompt Caching" that cuts some development costs by half by reusing pieces of the text AI has previously processed.