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NVIDIA GeForce RTX Laptops for STEM Degrees

NVIDIA GeForce RTX laptops do so much more than boost high-performance gaming applications – they also supercharge studies for STEM degrees. Powerful Graphics Processing Units (GPUs) help students work faster, with acceleration for top student applications in engineering, computer science, data science and economics. NVIDIA Broadcast uses AI to improve audio and video quality, making it easier to engage in lectures delivered online and to collaborate with lab group members from anywhere. And now, NVIDIA’s world-leading AI software stack comes to Windows 10, helping students studying artificial intelligence and data science learn on the same tools that they will use in the industry.

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Study Faster With GPU Acceleration

GeForce RTX laptops provide GPU acceleration for dozens of STEM tools and applications, allowing you to work faster and complete coursework sooner

Engineering

More interactive, realtime rendering for 3D design and modeling. Faster solutions and visualisation for mechanical, structural, and electrical simulations.

Computer Science, Data science, Economics

Faster data analytics for processing large data sets. Faster training for deep learning and traditional machine learning models for computer vision, natural language processing, and tabular data.

With GeForce RTX laptops you’ll have more time to explore the topics that interest you.

Top STEM Software Applications Accelerated By GeForce Laptops

STEM Application Performance

Engineering

RTX 3080 Laptop GPU

RTX 3060 Laptop GPU

Average Laptop

SOLIDWORKS
Up to 20x faster

ANSYS Discovery
Up to 4x faster

MATLAB
Up to 5x faster

SOLIDWORKS: SPECviewperf 2020 Solidworks viewset 4K score ANSYS Discovery Live Requires CUDA-enabled GPU and will not run on iGPU MATLAB Geomean of GPUbench tests CPU/iGPU is Intel Core Core i7-10750H@2.60GHz

Computer, Data Science and Economics

(Lower is Better)

RTX 3080 Laptop GPU

RTX 3070 Laptop GPU

Average Laptop

TensorFlow/ResNet50 Training
Up to 47x faster

RAPIDS
Up to 5x faster

TensorFlow ResNet50 training is mixed precision on cuDNN v8.1 batch size 128, single epoch training time calculated from measured images/sec. RAPIDS is random forest classifier trained on 2.2 GB NYC Taxi dataset. CPU is Intel Core Core i7-10750H@2.60GHz

Learn from Anywhere with AI-powered Remote Learning

NVIDIA Broadcast uses artificial intelligence to improve remote learning and collaboration. AI noise reduction works on both incoming and outgoing audio, making it easier to listen to and engage in online lectures. Background blur, background replacement and low-light noise removal let you turn your camera on no matter where you are, helping you collaborate with lab partners and study groups. And best of all, it works with all top remote learning video conferencing apps.

RUN WORLD-LEADING ARTIFICIAL INTELLIGENCE SOFTWARE

Interested in artificial intelligence or data science? Learn the same technology that you will use in industry with NVIDIA’s GPU-accelerated AI and data science software stack. Use cuDNN with GPU acceleration to train neural networks with TensorFlow, PyTorch, WinML, or MxNet. Run NVIDIA RAPIDS for data science, with cuDF, cuML, and cuGraph (GPU-accelerated alternatives to Pandas, SciKit-Learn, and NetworkX). NVIDIA software helps you train models faster and process more samples to get better accuracy and more insightful results. And, thanks to CUDA on Windows Subsystem for Linux (WSL2), it’s now available on Windows 10. This capability allows Windows users to run Linux applications simultaneously. A true multi-OS environment for future data scientists!

GeForce RTX Laptops are the Best Computers for STEM Students

No longer do students have to choose between a computer for school or a computer for fun. With GeForce RTX laptops you can study, create, and play, all on the same platform.

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