DEEP LEARNING SOFTWARE
NVIDIA provides optimized software stacks to accelerate training and inference phases of the deep learning workflow. Deep learning is a branch of machine learning.
DEEP LEARNING CODE
With a single programming model for all GPU platform - from desktop to datacenter to embedded devices, developers can start development on their desktop, scale up in the cloud and deploy to their edge devices - with minimal to no code changes. With Tensor Cores enabled, FP32 and FP16 mixed precision matrix multiply dramatically accelerates your throughput and reduces AI training times.įor developers integrating deep neural networks into their cloud-based or embedded application, Deep Learning SDK includes high-performance libraries that implement building block APIs for implementing training and inference directly into their apps. When models are ready for deployment, developers can rely on GPU-accelerated inference platforms for the cloud, embedded device or self-driving cars, to deliver high-performance, low-latency inference for the most computationally-intensive deep neural networks.įor AI researchers and application developers, NVIDIA Volta and Turing GPUs powered by tensor cores give you an immediate path to faster training and greater deep learning performance. With NVIDIA GPU-accelerated deep learning frameworks, researchers and data scientists can significantly speed up deep learning training, that could otherwise take days and weeks to just hours and days. Recommendation systems use images, language, and a user’s interests to offer meaningful and relevant search results and services.ĭeep learning has led to many recent breakthroughs in AI such as Google DeepMind’s AlphaGo, self-driving cars, intelligent voice assistants and many more. Durch Kombination von künstlicher Intelligenz. Die grafische Benutzeroberfläche vereinfacht das Trainieren des neuronalen Netzwerks ohne Beeinträchtigung der Leistung. Ihre industrieerprobten Algorithmen wurden besonders für die industrielle Bildverarbeitung optimiert. Conversational AI apps help computers understand and communicate through natural language. Cognex Deep Learning wurde für die automatische Fertigung entwickelt.
Computer vision apps use deep learning to gain knowledge from digital images and videos. Their highly flexible architectures can learn directly from raw data and can increase their predictive accuracy when provided with more data.ĭeep learning is commonly used across apps in computer vision, conversational AI and recommendation systems.
Deep learning differs from traditional machine learning techniques in that they can automatically learn representations from data such as images, video or text, without introducing hand-coded rules or human domain knowledge.
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