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Edge Impulse unveils generative AI tools for synthetic data creation on edge devices

Edge Impulse unveils generative AI tools for synthetic data creation on edge devices

Edge Impulse has introduced new generative AI features aimed at creating and managing synthetic data on edge devices, including images, speech, and audio data.

According to the company, the new Synthetic Data integration offers a method for using Edge Impulse for large language model (LLM)-based data creation. It utilizes tools like DALL-E for image generation, Whisper for speech element creation for keyword spotting, and ElevenLabs for generating audible events.

Using the new features, the company says enterprise customers will have the opportunity to incorporate custom LLM sources, including other data providers or self-hosted LLMs. Additional LLM toolkits are expected to be added in the coming months.

These features complement Edge Impulse’s existing integration with NVIDIA Omniverse Replicator, a framework for developing synthetic data generation pipelines for training computer vision models.

The new toolset is currently available for enterprise-tier users, with the company mentioning plans to extend availability to professional plan users. Located in the “data acquisition” section of Edge Impulse, it is found alongside options like Dataset, Data Explorer, and Data Sources.

Additionally, the company boasts the integration allows users to add and refine prompts, with outputs such as images and audio fragments displayed for evaluation.

Key features include creating image datasets using the DALL-E model, generating keyword-spotting datasets for speech recognition applications using the Whisper model, and producing audible events like glass breaking or alarm sounds using the ElevenLabs Sound Effects model.

The features also connect to other LLM data providers or self-hosted LLMs using transformation blocks, including Edge Impulse’s integration with GPT-4o for labeling image data.

This iterative workflow simplifies the process of generating the right prompts and ensures that any data not deleted is automatically added to the project for seamless management.

These new features aim to streamline the workflow for building models using synthetic data, with the goal of making it easier for developers to create high-quality datasets with generative AI.

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