The NVIDIA NGC catalog is a hub of GPU-optimized deep learning, machine learning and HPC applications. With highly performant software containers, pre-trained models, industry specific SDKs and Helm charts you can simplify and accelerate your end-to-end workflows.
The NVIDIA NGC team works closely with our internal and external partners to update the content in the catalog on a regular basis. Below are some of the highlights:
NVIDIA Maxine is a GPU-accelerated SDK with state-of-the-art AI features for developers to build virtual collaboration and content creation solutions, including video conferencing and streaming applications. You can add any of Maxine’s AI effects – Video, Audio, and Augmented Reality – into your existing application or develop a new pipeline from scratch.
Maxine’s Video Effects SDK and Audio Effects SDK are now available through the Maxine collection on the NGC catalog that includes a container for each SDK:
- Video Effects SDK container enables video quality enhancement such as super resolution, reducing compression artifacts and video degradation caused by low light conditions or lower-quality cameras.
- Audio Effects SDK container removes reverberations due to talking in low sound absorption spaces and reduces over 25 different unwanted background noise profiles such as keyboard typing, mouse-clicking, and fan noise.
Clara Train SDK 4.0
Clara Train v4.0 is now powered by MONAI, a domain-specialized open-source PyTorch framework, accelerating deep learning in Healthcare imaging.
The latest version also expands into Digital Pathology and introduces homomorphic encryption for server side aggregation in federated learning.
Transfer Learning Toolkit (TLT)
The NVIDIA Transfer Learning Toolkit (TLT) is the AI toolkit that abstracts away the AI/DL framework complexity and leverages high quality pre-trained models to enable you to build production quality models faster with only a fraction of data required.
Version 3.0 of TLT is now available for computer vision and conversational AI use cases. Get started today by exploring the TLT collections for:
Deep Learning and Inference
Our most popular deep learning frameworks for training and inference have also been updated to the latest 21.02 version
- PyTorch Lightning, developed by Grid.AI, allows you to leverage multiple GPUs and state-of-the-art training features such as 16-bit precision, early stopping, logging, pruning and quantization, while enabling faster iteration and reproducibility for your AI research.
- Vyasa’s suite of biomedical analytics allows users to derive insights from analytical modules including question answering, named entity recognition, PDF table extraction and image classification, irrespective of where that data resides.