Accelerating Trustworthy AI for Credit Risk Management
As AI becomes prevalent, government agencies will be advocating for citizens for transparency on why financial entities make decisions about consumers.
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Announcing the Jetson Xavier NX, World’s Smallest AI Supercomputer for Embedded Systems
NVIDIA today introduced Jetson Xavier NX, the world’s smallest, most powerful Ai supercomputer for embedded and edge systems.
Accelerating Interpretable Machine Learning for Diversified Portfolio Construction
Learn how Munich Re markets developed an interpretable machine learning to increase performance on diversified portfolio construction.
NVIDIA A100 GPUs Available on Google Cloud’s Compute Engine
NVIDIA and Google Cloud are making it possible for applications to push the boundaries of accelerated AI across a wide array of applications.
Optimizing Access to Parquet Data with fsspec
This post details how the filesystem specification’s new parquet model provides a format-aware byte-cashing optimization.
Sparse Forests with FIL
Introduction The RAPIDS Forest Inference Library, affectionately known as FIL, dramatically accelerates inference (prediction) for tree-based models, including gradient-boosted decision tree models (like those from XGBoost and LightGBM) and random forests. (For a deeper dive into the library overall, check out the original FIL blog.) Models in the original FIL are stored as dense binary … Continued
NVIDIA Captures Top Spots on World’s First Industry-Wide AI Benchmark
Today, the MLPerf consortium published its first results for the seven tests that currently comprise this new industry-standard benchmark for machine learning. For the six test categories where NVIDIA submitted results, we’re excited to tell you that NVIDIA platforms have finished with leading single-node and at-scale results for all six, a testament to our total … Continued
Deep Learning vs Machine Learning Challenger Models for Default Risk with Explainability
This post details the credit default risk prediction with deep learning and machine learning models.
Machine Learning Frameworks Interoperability, Part 3: Zero-Copy in Action using an E2E Pipeline
Part 3 of this series covers implementation of an end-to-end pipeline, demonstrating techniques for optimal data transfer across data science frameworks.
Machine Learning Frameworks Interoperability, Part 1: Memory Layouts and Memory Pools
Learn about the pros and cons of distinct memory layouts, as well as memory pools for asynchronous memory allocation to enable zero-copy functionality.
Cybersecurity Framework: An Introduction to NVIDIA Morpheus
In this tutorial, we walk through the Morpheus pipeline and illustrate how to prepare a custom model for Morpheus.
Microsoft and NVIDIA Announce June Preview for GPU-Acceleration Support for WSL
Microsoft announced a Public Preview for GPU in Windows Subsystem for Linux (WSL). WSL is a layer that enables executing Linux binaries on Microsoft Windows computing systems.
Meet the Researcher: Marco Aldinucci, Convergence of HPC and AI to Fight Against COVID
‘Meet the Researcher’ is a series in which we spotlight different researchers in academia who use NVIDIA technologies to accelerate their work. This month we spotlight Marco Aldinucci, Full Professor at the University of Torino, Italy, whose research focuses on parallel programming models, language, and tools. Since March 2021, Marco Aldinucci has been the Director … Continued
Gauss Rank Transformation Is 100x Faster with RAPIDS and CuPy
As explained in the Batch Normalization paper, training neural networks becomes way easier if its input is Gaussian. This is clear. And if your model inputs are not Gaussian, RAPIDS will just transform it to Gaussian in the blink of an eye.
NVIDIA Research: An Analytic BRDF for Materials with Spherical Lambertian Scatterers
Researchers at NVIDIA presented a new paper “An Analytic BRDF for Materials with Spherical Lambertian Scatterers” at Eurographics Symposium on Rendering 2021 (EGSR), June 29-July 2, introducing a new BRDF for dusty/diffuse surfaces. Our new Lambert-sphere BRDF (right) accurately and efficiently models the reflectance of a porous microstructure consisting of Lambertian spherical particles. Most rough … Continued