ClearML, the provider of an open-source, unified, end-to-end MLOps platform, is announcing a recent integration of its platform with the latest NVIDIA TAO Toolkit 4.0 release. Aimed toward improving AI models, this integration leverages the TAO Toolkit’s visualizations of training, experimentation, and evaluation processes to improve model creation.
The NVIDIA Tao Toolkit is a low-code AI model development solution centered around easing the extent of labor involved in generating custom, production-ready AI models.
ClearML’s platform, which is purpose-built for unifying MLOps processes with little code, employs the TAO Toolkit to enhance the following:
- Experiment comparison
- Training result visualization
- Simple experiment comparison
- Remote execution of experiments without infrastructure setup
- Customization and automation of training processes with external triggers
- Deployment of NVIDIA TensorRT binaries in NVIDIA Triton with ClearML Serving
“ClearML is working to significantly shorten the time it takes for customers to see value from their investment in ML projects and deliver them to the market,” said Moses Guttmann, CEO and co-founder of ClearML. “By integrating the NVIDIA TAO Toolkit into the ClearML platform, we are able to significantly reduce the barriers of entry by offering state-of-the-art models available for training on custom data. Moreover, ClearML adds a visibility layer that provides TAO users with the extra information they need.”
ClearML offers its solution as free tier servers as well as personal hosting.
For more information about ClearML’s recent integration, please visit https://clear.ml/.