The annual Interservice/Industry Training, Simulation and Education Conference (I/ITSEC), the world’s largest modeling, simulation and training event, opens today in Orlando, Florida. If you are attending I/ITSEC 2019, we invite you to meet with PNY’s Partners to discuss your NVIDIA Quadro GPU needs, including NVIDIA Quadro MXM Embedded, GPU Down and the latest NVIDIA Quadro RTX Solutions. NVIDIA Quadro GPUs provide the extreme graphics and compute performance demanded by mission-critical aerospace and defense applications.
Topics: VR, Simulation, NVIDIA Quadro, Deep Learning, AI, CAE, CAD, Technology, Embedded MXM, RT Cores, NVIDIA Turing Architecture, I/ITSEC, Modeling, nvidia quadro rtx, hpc, I/ITSEC 2019, GPU Down, AR, Interservice/Industry, NVIDIA Quadro MXM, Education, Scientific Visualization, Signal Processing, Mission Simulators
According to Data Science Central, a leading online resource for data practitioners, forecasts predict the big data market will approach $203 billion by 2020. Data science is powering the engine of modern enterprise – every industry from retail to financial services to healthcare is deriving insight from data to improve competitiveness and operational efficiency. Retailers are improving forecasting to reduce the cost of excess inventory. Financial services institutions are detecting fraudulent transactions. Healthcare providers are predicting the risk of disease more quickly. Even modest improvements in the accuracy of predictive machine learning models can translate into billions on the bottom line. The NVIDIA accelerated Data Science Workstation (DWS) solution with RAPIDS enables enterprises and data scientists to tap into GPU-accelerated machine learning (ML) and deep learning (DL) with faster model iteration, better prediction accuracy, and lowest data science total cost of ownership (TCO).
Topics: PNY, NVIDIA Quadro, Deep Learning, AI, PNYPRO, NVIDIA RTX Technology, Quadro RTX, nvidia quadro rtx, Data Science Workstation, NGC, hpc, graph analytics, data preparation, data science, RAPIDS, GPU-accelerated machine learning, NVIDIA CUDA, analytics, model training, CUDA-X