Lexset’s Seahaven and NVIDIA TAO Toolkit accelerate transfer learning
The biggest challenge to creating data-hungry computer vision systems is the acquiring, cleaning, and labeling of data. Today, data is collected and labeled all over the world in a slow, error-prone, and insecure process that looks more like the global supply chain for goods than for software development. By 2024, synthetically generated data will comprise 60 percent of the data used for AI development, according to Gartner Research.
Lexset, a pioneer in synthetic data creation, announced the release of Seahaven, a new data generation platform. Scheduled for release later this month, it will give AI developers a powerful new tool in the race to revolutionize the data supply chain.
Lexset’s Seahaven offers high-quality training data and eliminates delays associated with human-in-the-loop data sourcing and labeling. This rapid method of on-demand data delivery helps solve problems traditionally associated with collecting training data. With Seahaven, customers can quickly create high-quality training data that can be used with the NVIDIA TAO Toolkit to accelerate the creation of vision AI applications.
Drawing from its massive 3D model library, Lexset uses procedural algorithms to create fully annotated synthetic datasets. The process makes it possible to generate datasets 12X faster than conventional methods, while matching or exceeding the performance of models trained on traditional data. Gathering data is just one of the steps in the model creation process. The next step involves creating a model that fits a given use, which can be a time-consuming process.
NVIDIA TAO Toolkit is the CLI and Jupyter Notebook version of NVIDIA TAO, an AI model adaptation framework. With it, users can create custom, production-ready AI models for their use case in a fraction of the time without needing AI expertise. The toolkit leverages the power of transfer learning and applies the knowledge gained from solving one model to another in the same domain.
With transfer learning, data scientists and engineers still need easy access to data to teach a model the nuances of the related problem. Because Lexset’s Seahaven enables on-demand creation of data, users can adapt AI models across domains in a mere fraction of the time.
With Lexset’s Seahaven and the NVIDIA TAO Toolkit, users can go from a dataset to a trained model at high velocity. Rapid access to training data, coupled with transfer learning, helps companies of all sizes and in all stages of development to enter and compete in the global vision AI race by removing complexity and accelerating development.
“We are excited to combine NVIDIA’s world-class GPU-accelerated hardware and model training tools with Lexset synthetic data and provide a great accelerant to companies across the industry, “ said Lexset CEO Francis Bitonti.
Models trained with Lexset data often achieve more than 90 percent precision and recall scores and improve baseline performance by 15 percent when compared to models trained on real-world data alone. Lexset doesn’t use an army of highly trained technical artists to make datasets, but generates simulations algorithmically, increasing speed and diversity.