NVIDIA Unveils Over 50 New Updated AI Tools and Training for Developers
April 20, 2021 — To help developers hone their craft, NVIDIA this week introduced more than 50 new and updated tools and training materials for data scientists, researchers, students, and developers of all kinds.
Offerings range from software development kits for conversational AI and ray tracing, to hands-on courses in NVIDIA Deep Learning Institute.
They are available to all members of the NVIDIA Developer Programa free global community of over 2.5 million technology innovators who are revolutionizing industries with accelerated computing.
Learning new, advanced software development skills is essential to staying ahead of a competitive job market. DLI provides a comprehensive learning experience on a wide range of important topics in AI, data science, and accelerated computing. Classes include hands-on exercises and are available in self-paced and instructor-led formats.
The five courses cover topics such as deep learning, data science, autonomous driving, and conversational AI. All include practical exercises that accelerate learning and mastery of the material. DLI workshops are led by NVIDIA-certified instructors and include access to fully configured GPU-accelerated servers in the cloud for each attendee.
New self-paced courses available now:
New full-day, instructor-led workshops for delivering live virtual classes (coming soon):
These instructor-led workshops will be available to corporate clients and the general public. The IDD has recently launched public workshops for its popular instructor-led courses, increasing accessibility for individual developers, data scientists, researchers, and students.
To further extend the training, the IDD publishes a new book, “Learning Deep Learning”, which provides a comprehensive guide to the theory and practical applications of deep learning. Written by NVIDIA engineer Magnus Ekman, it explores how deep neural networks are applied to solve complex and difficult problems. Pre-orders are available now through Amazon.
New and accelerated SDKs, plus updated tech tools
SDKs are a key component that can make or break an application’s performance. Dozens of new and updated kits for high-performance computing, computer vision, data science, conversational AI, recommender systems, and real-time graphics are available so developers can tackle virtually any challenges. Updated tools are also in place to help developers speed up application development.
Updated tools available now:
- NGC is a GPU-optimized hub for AI and HPC software with a catalog of hundreds of SDKs, AI, ML, and HPC containers, pre-trained models, and Helm charts that simplify and speed up end-to-end workflow. Pre-trained models help developers jump-start their AI projects for a variety of use cases, including computer vision and speech.
New SDK (coming soon):
- TAO (Train, Adapt, Optimize) is a GUI-based, workflow-driven framework that simplifies and accelerates the creation of enterprise AI applications and services. Companies can refine pretrained models using transfer learning or federated learning to produce domain-specific models in hours rather than months, eliminating the need for large training runs and deep AI expertise. Learn more about TAO.
New and updated SDKs and frameworks available now:
- Jarvis, a fully accelerated application framework for building multi-modal conversational AI services. It includes state-of-the-art models pre-trained over thousands of hours on NVIDIA DGX systems, the Transfer Learning Toolkit to adapt these models to zero-coding domains and optimized end-to-end voice, vision, and language pipelines that run in real time. Learn more.
- Maxine, a GPU-accelerated SDK with state-of-the-art artificial intelligence features enabling developers to create virtual collaboration and content creation applications such as video conferencing and live streaming. Maxine’s AI SDKs (video effects, audio effects, and augmented reality) are highly optimized and include modular features that can be chained together in end-to-end pipelines to deliver the best possible performance on GPUs, both on PCs and in data centers. Learn more.
- Merlinan application framework, currently in open beta, enables the development of deep learning recommender systems – from data preprocessing to model training and inference – all accelerated on NVIDIA GPUs. Learn more about Merlin.
- deep flowan AI stream analysis toolkit for building complex, high-performance, low-latency video analysis applications and services.
- Triton Inference Serverwhich allows teams to deploy AI models trained from any framework, from local storage or cloud platform on any GPU or CPU based infrastructure.
- TensorRT, for high-performance deep learning inference, includes a deep learning inference optimizer and runtime environment that provides low latency and high throughput for deep learning inference applications. TensorRT 8 is 2x faster for transformer-based models and new techniques to achieve FP32-like accuracy while using high-performance INT8 precision.
- RTX Technologywhich helps developers exploit and bring realism to their games:
- DLSS is a deep learning neural network that helps graphics developers increase frame rates and generate beautiful, crisp images for their projects. It includes performance headroom to maximize ray tracing parameters and increase output resolution. Unity announced that DLSS will be natively supported in Unity Engine 2021.2.
- RTX Direct Lighting (RTXDI) makes it possible to render, in real time, scenes with millions of dynamic lights without worrying about performance or resource constraints.
- RTX Global Illumination (RTXGI) harnesses the power of ray tracing to scalably compute multi-bounce indirect illumination without baking time, light leaks, or high costs per frame.
- Real-time denoisers (NRD) is an API independent spatiotemporal denoising library designed to work with low radius per pixel signals.
More information is available here: NVIDIA Developer Program
Source: WILL RAMEY, NVIDIA