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.
The offerings range from software development kits for conversational AI and ray tracing, to hands-on courses from the NVIDIA Deep Learning Institute.
They’re available to all members of the NVIDIA Developer Program, a free-to-join global community of over 2.5 million technology innovators who are revolutionizing industries through accelerated computing.
Training for Success
Learning new and advanced software development skills is vital to staying ahead in a competitive job market. DLI offers a comprehensive learning experience on a wide range of important topics in AI, data science and accelerated computing. Courses include hands-on exercises and are available in both self-paced and instructor-led formats.
The five courses cover topics such as deep learning, data science, autonomous driving and conversational AI. All include hands-on 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 participant.
New self-paced courses, which are available now:
- Getting Started with Deep Learning
- Accelerating End-to-End Data Science Workflows
- Integrating Sensors with NVIDIA DRIVE
New full-day, instructor-led workshops for live virtual classroom delivery (coming soon):
These instructor-led workshops will be available to enterprise customers and the general public. DLI recently launched public workshops for its popular instructor-led courses, increasing accessibility to individual developers, data scientists, researchers and students.
To extend training further, DLI is releasing a new book, “Learning Deep Learning,” that provides a complete guide to deep learning theory and practical applications. Authored by NVIDIA Engineer Magnus Ekman, it explores how deep neural networks are applied to solve complex and challenging problems. Pre-orders are available now through Amazon.
New and Accelerated SDKs, Plus Updated Technical 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 meet virtually any challenge. Updated tools are also in place to help developers accelerate 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 accelerate workflows from end to end. 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. Enterprises can fine-tune pre-trained 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 multimodal conversational AI services. It includes state-of-the-art models pre-trained for thousands of hours on NVIDIA DGX systems, the Transfer Learning Toolkit for adapting those models to domains with zero coding, and optimized end-to-end speech, vision and language pipelines that run in real time. Learn more.
- Maxine, a GPU-accelerated SDK with state-of-the-art AI features for developers to build 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 into end-to-end pipelines to deliver the highest performance possible on GPUs, both on PCs and in data centers. Learn more.
- Merlin, an 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. Read more about Merlin.
- DeepStream, an AI streaming analytics toolkit for building high-performance, low-latency, complex video analytics apps and services.
- Triton Inference Server, which lets teams deploy trained AI models 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 that delivers low latency and high throughput for deep learning inference applications. TensorRT 8 is 2x faster for transformer-based models and new techniques to achieve accuracy similar to FP32 while using high-performance INT8 precision.
- RTX technology, which helps developers harness and bring realism to their games:
- DLSS is a deep learning neural network that helps graphics developers boost frame rates and generates beautiful, sharp images for their projects. It includes performance headroom to maximize ray-tracing settings and increase output resolution. Unity has announced that DLSS will be natively supported in Unity Engine 2021.2.
- RTX Direct Illumination (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) leverages the power of ray tracing to scalably compute multi-bounce indirect lighting without bake times, light leaks or expensive per-frame costs.
- Real-Time Denoisers (NRD) is a spatio-temporal API-agnostic denoising library that’s designed to work with low ray-per-pixel signals.
Joining the NVIDIA Developer Program is easy, check it out today.
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