Instant NERF Sweepstakes Winners NVIDIA Developer 2022-08-12 | Some of the amazing entries, and the two random draw winners from our Instant NeRF Sweepstakes held on Twitter (@NVIDIAAIDev channel). Thank you to our amazing #InstantNeRF community for so many creative and fun NeRFs. Our Instant NeRF is a neural rendering model that learns a high-resolution 3D scene in seconds from 2D images — and can render images of that scene in a few milliseconds. Learn more about Instant NeRFs: nvda.ws/3AU5wgATutorial on how to make a 3D render from 2D photos: nvda.ws/3ciMLJIFind the code on GitHub: github.com/NVlabs/instant-ngpMore Instant NeRF creators: blogs.nvidia.com/blog/2022/08/05/instant-nerf-creators-siggraphFor business inquiries, please visit our website and submit the form on NVIDIA Research Licensing: nvidia.com/en-us/research/inquiries#InstantNeRFSweepstakes #NeRF #AI #3D #NeuralRendering #volumetric #photogrametry #syntesis #NVIDIA #NVIDIAResearch #InstantNGP #computervision #NeRFs #siggraph2022
CUDA 12 New Features and Beyond NVIDIA Developer 2022-12-15 | Learn about the newest release of CUDA and its exciting features and capabilities in this webinar and live Q&A. We will pay particular focus on release compatibility, the lazy loading feature, and how we uniquely support the new NVIDIA Hopper and Ada Lovelace GPU architectures.CUDA 12.0 toolkit release: nvda.ws/3FLUn3B00:00 - Introduction03:39 - CUDA Dynamic Parallelism09:55 - Hopper DPX Instructions12:06 - Lazy Loading16:10 - OS Support Updates17:26 - CUDA Compiler Updates33:47 - Math Libraries37:53 - Compatibility Updates49:47 - Thank You and Q&AAdditional resources:CUDA Dynamic Parallelism: developer.nvidia.com/blog/introduction-cuda-dynamic-parallelismCUDA Programming Model for Hopper Architecture: nvidia.com/en-us/on-demand/session/gtcfall22-a41095/?playlistId=playList-b5be3b9b-cc52-48ed-b83d-4352b108e766Join our developer program: nvda.ws/3BEFldpAbout our presenters:Rob Armstrong, is a principal technical product manager for the CUDA toolkit. For over 20 years he has focused on accelerating software with heterogeneous hardware platforms, and has particular interest in computer architecture and hardware/software interaction.Rob Nertney is a senior technical product manager for CUDA. He has spent nearly 15 years architecting the features and deployment of accelerator hardware into hyperscale environments for both internal and external use by developers. He has several patents in processor design relating to secure solutions that are in production today. In his spare time, he loves golfing when the weather is nice, and gaming (on RTX hardware of course!) when the weather isn’t.Arthy Sundaram is a technical product manager for the CUDA platform. She holds an MS in computer science from Columbia University. Her areas of interest are operating systems, compilers, and computer architecture.Matthew Nicely joined NVIDIA in March 2019, having previously worked at the U.S. Army Aviation and Missile Research Development and Engineering Center, Huntsville, AL, USA. There, he focused on CUDA algorithm development and optimizations on the Jetson series. At NVIDIA, he has worked in the Federal segment assisting with CUDA development and optimizations, along with education and proof of concepts for customers on various NVIDIA tool sets, before recently transitioning to math libraries product manager. In 2019, he received his Ph.D. degree in computer engineering, focusing on algorithm optimizations on GPUs.
Experiment NVIDIA TAO Toolkit and pretrained models on Google Colab NVIDIA Developer 2022-12-13 | The #NVIDIATAO Toolkit, built on TensorFlow and PyTorch, is a low-code AI solution that abstracts away the AI and deep learning framework complexity. It lets developers use the power of transfer learning to create custom, production-ready AI models to power speech and vision AI applications. In this video, we’ll show you how you can quickly launch #NVIDIATAO toolkit notebook directly on Google Colab to train AI model without having to set up any infrastructure. Learn more about NVIDAI TAO Toolkit: nvda.ws/3YsIdEgMore about running TAO Toolkit on Google Colab: github.com/NVIDIA-AI-IOT/nvidia-taoTry TAO on Google Colab • Object Detection: colab.research.google.com/github/NVIDIA-AI-IOT/nvidia-tao/blob/main/tensorflow/yolo_v4/yolo_v4.ipynb• Image Classification: colab.research.google.com/github/NVIDIA-AI-IOT/nvidia-tao/blob/main/tensorflow/classification/classification.ipynb• Action Recognition: colab.research.google.com/github/NVIDIA-AI-IOT/nvidia-tao/blob/main/pytorch/cv_notebooks/action_recognition_net/actionrecognitionnet.ipynbAdditional TAO Toolkit developer resources: nvda.ws/3he07K2 #NVIDIATAO , #AI, #aitraining Transfer Learning, AI/ML Models, AI training, GoogleColab, pretrained models, object detection, image classification, segmentation
NVIDIA Base Command Platform NVIDIA Developer 2022-12-09 | Take a guided tour of NVIDIA Base Command Platform, a software service for enterprise-class AI training which also provides centralized control of your AI training projects and works with NVIDIA DGX SuperPOD. See some of the features and capabilities NVIDIA Base Command Platform can offer to centralize and accelerate enterprise AI development. Learn more about the enterprise-class platform for AI training here: nvda.ws/3UGRmFZ#NVIDIADGX, #NVIDIABaseCommandPlatform, #BaseCommandPlatform, #NVIDIAAINVIDIA AI, NVIDIA Base Command Platform, NVIDIA DGX Systems, NVIDIA DGX A100, Base Command Platform
Speech AI Expands Global Reach With Telugu Speech Recognition NVIDIA Developer 2022-12-08 | Built with the NVIDIA NeMo framework, automatic speech recognition model tops accuracy leaderboards for a competition hosted by IIIT-Hyderabad. Find out how NVIDIA is making useful, accurate speech AI possible for every language nvda.ws/3B5LteD#SpeechAI #AI #Telugu
Earth-2 and Blue Marble 50th Anniversary NVIDIA Developer 2022-12-07 | It's been 50 years since @NASA's original Blue Marble image. 🌍Today, @NVIDIAOmniverse is being used to create Earth's #DigitalTwin, allowing scientists to better visualize & more accurately predict #ClimateChange.Learn more: nvda.ws/3uxANBH#HPC #simulation #physics
NVIDIA Neural Brushstroke Engine NVIDIA Developer 2022-12-01 | While many AI models are generating their own art, we take the opposite approach and leverage AI to develop interactive brushes for human artists. These brushes are dynamic and diverse, even matching the style of specific artworks or a target text query. Watch the demo and visit nv-tlabs.github.io/brushstroke_engine to learn more about the model.#generativeai, #ai, #generativeart, #genAI, #aiart generative ai, neural rendering, generative art, ai, machine learning
Simplify SMPTE ST 2110 Deployment with NVIDIA Rivermax NVIDIA Developer 2022-11-30 | The transition to SMPTE ST 2110 is accelerated by NVIDIA RTX GPUs and NVIDIA networking solutions including Rivermax, which are production-proven technologies that are relied upon by modern broadcasters who are leading the industry’s adoption of IP video.Learn more about NVIDIA Solutions for the Professional Broadcast Industry nvda.ws/3XD6l6JSMPTE ST 2110, IP Video, BroadcastNVIDIA, SMPTE ST 2110, IP Video, AI, Broadcast, GPU, Networking, Rivermax, Mellanox
3D MoMa Material and Lighting Demo NVIDIA Developer 2022-11-28 | 3D MoMa converts physical objects into a 3D triangle mesh from a set of images. That mesh can be manipulated in various ways, from changing the texture and material of the 3D model to providing a new lighting environment, as shown in this demo. The model is directly compatible with traditional graphics engines.
Whats New in CUDA Developer Tools: Profiling NVIDIA Hopper and workflow enhancements NVIDIA Developer 2022-11-14 | The latest updates to CUDA developer tools include workflow enhancements, new supported environments, and profiling features for the latest NVIDIA Hopper-based platforms. This video offers an overview of the highlights, including Arm GUI support, SDK Manager improvements, and new performance metrics for CPU and GPU profiling. For more information, see the Nsight Systems and Nsight Compute product pages. developer.nvidia.com/tools-overview
Cloud-Native Vision AI Deployments With Metropolis Microservices and Reference Apps NVIDIA Developer 2022-11-09 | Vision AI solutions are expanding from the Edge to SaaS in the Cloud. Metropolis Microservices, based on NVIDIA Unified Compute Framework (UCF), contains a collection of cloud-native reference applications and microservices to help enterprises, systems integrators, and solution providers deliver sophisticated vision AI based services to any cloud faster and with less effort.#NVIDIAMetropolis, #AI, #VisionAILearn more about NVIDIA Metropolis Microservices and Reference Applications nvda.ws/3hrpasMLearn more about NVIDIA Unified Compute Framework (UCF) nvda.ws/3UqMzck
Use the Jetson AGX Orin Developer Kit to Emulate All Six Jetson Orin Modules NVIDIA Developer 2022-11-08 | All Jetson Orin modules and the Jetson AGX Orin Developer Kit are based on a single SoC architecture which means you can develop software for one Jetson Orin module and then easily deploy it to any of the others. You can begin development today for any Jetson Orin module using the Jetson AGX Orin Developer Kit. The developer kit’s ability to natively emulate performance for any of the modules lets you start now and shorten your time to market. The developer kit can accurately emulate the performance of any Jetson Orin module by configuring the hardware features and clocks to match that of the target module. Learn more in our blog post, “Develop for All Six NVIDIA Jetson Orin Modules with the Power of One Developer Kit”: nvda.ws/3Tq4XRf
NVIDIA Inception | Halodi Expands the Deployment of Humanoid Robots NVIDIA Developer 2022-11-02 | Learn how NVIDIA Inception program member, Halodi Robotics, expands the deployment of humanoid robots to industries such as security, logistics, healthcare, and retail. EVE, an autonomous humanoid robot, can perform mundane, repetitive, dull or dangerous tasks. In retail environments, EVE can safely collaborate with staff, working 24/7 to restock shelves and do repetitive tasks. Powered by NVIDIA Jetson AGX Xavier on a robust cloud architecture, EVE utilizes AI and machine learning, perception and VR at the edge. NVIDIA Inception is a free program designed to help your startup evolve faster through access to cutting-edge technology and NVIDIA experts, opportunities to connect with venture capitalists, and co-marketing support to heighten your company’s visibility. Learn more: nvda.ws/3gWZe8j #NVIDIAInception #Startups #AI #AIinRobotics #robotics #humanoidrobots AI, AIinRobotics, robots, humanoidrobots, Jetson, startup, startupincubator, acceleration for startups
Create and Deploy Custom AI Models with NVIDIA TAO on Azure ML NVIDIA Developer 2022-10-26 | This video shows that how you can fast-track your vision AI application development by taking a pretrained object detection model, fine-tuning it with custom data with #NVIDIATAO and deploying it for inference with NVIDIA Triton™ on Azure Machine Learning (Azure ML).Learn more about TAO Toolkit nvda.ws/3ThywFpGet started with TAO Toolkit nvda.ws/3EVdUOU
Jetson AI Labs – E10 – How students learn AI with Jetson? (University of Manchester + TEC Monterrey) NVIDIA Developer 2022-10-18 | The University of Manchester has developed the PuzzleBot, an educational robotics platform for students that makes easier the process of getting started with AI in robotics.In this video, we will watch how the University of TEC Monterrey (Mexico) has implemented the PuzzleBot platform in their main robotics programs with success. We will learn about the experience directly from their students, professors, and researchers.
Tracking objects across multiple Cameras with Metropolis Microservices NVIDIA Developer 2022-10-14 | Giving perception to smart spaces often requires applying vision AI to many cameras covering multiple physical regions. Whether it’s for monitoring packaged goods in a warehouse or vehicles on a street, it's critical to accurately and consistently track these objects as they move across camera views. We'll showcase how multi-camera tracking and re-identification of objects is made easy with NVIDIA Metropolis MicroservicesTry out the demo nvda.ws/3EC2JKZLearn more about multi-camera tracking nvda.ws/3CRN4pyLearn more about Metropolis Microservices nvda.ws/3SVwxX7
NVIDIA Jetson Orin Powered AI Solutions NVIDIA Developer 2022-10-10 | Bring your next-generation products to life with the world’s most powerful AI computers for energy-efficient autonomous machines. NVIDIA Jetson Orin modules have up to 275 Trillion Operations per Second (TOPS) and 8X the performance of the last generation for multiple concurrent AI inference pipelines, plus high-speed interface support for multiple sensors, making them the ideal solution for a new age of robotics. Get started developing with the NVIDIA Jetson AGX Orin Developer Kit. It can emulate the entire family of Jetson Orin modules, letting you create advanced robotics and edge AI applications for manufacturing, logistics, retail, service, agriculture, smart city, healthcare, and life sciences. Learn more about how Jetson Orin is powering the world’s autonomous machines and edge AI applications: www.nvidia.com/jetson-orin
How to Deploy HuggingFace’s Stable Diffusion Pipeline with Triton Inference Server NVIDIA Developer 2022-10-05 | This video showcases deploying the Stable Diffusion pipeline available through the HuggingFace diffuser library. We use Triton Inference Server to deploy and run the pipeline. Two models in the pipeline have been exported to ONNX and TensorRT to demonstrate use of multiple backends in the same pipeline.GitHub Code: github.com/triton-inference-server/server/tree/main/docs/examples/stable_diffusionTriton Documentation: github.com/triton-inference-server/server/tree/main/docsNote: This example doesn’t include all possible optimizations to the stable diffusion pipeline. The intent is to show ease of deployment with Triton.#ai #inference #triton #deeplearning #stablediffusion
NVIDIA Inception | Gleamer Uses AI to Help Radiologists NVIDIA Developer 2022-10-05 | Learn how NVIDIA Inception program member Gleamer helps radiologists identify fractures that are easy to miss. Powered by NVIDIA AI technologies, including NVIDIA Jetson, V100 and A100 GPUs in the cloud, and utilising the NVIDIA JetPack SDK and Clara imaging framework. NVIDIA Inception is a free program designed to help your startup evolve faster through access to cutting-edge technology and NVIDIA experts, opportunities to connect with venture capitalists, and co-marketing support to heighten your company’s visibility. Learn more: nvda.ws/3T2saJL#NVIDIAInception #Startups #AI #AIinHealthcare
NVIDIA Developer Program | The Community that Builds NVIDIA Developer 2022-10-04 | We believe that developers are the inspired, technical minds transforming the world around us with new innovations. You are key contributors to the advancement of every field—and the foundation of NVIDIA’s success. To ensure you have the best resources to do your life’s work, we’ve created an online space devoted to accelerating your work with access to over 450 SDKs and pre-trained AI models, technical documentation, domain expert help, deep learning courses and workshops, and much more. Free developer tools, training, and community.Join the Developer Program today and accelerate your work: developer.nvidia.com/developer-program?ncid=so-yout-905036#cid=dev03_so-yout_en-us#AI #Technology #DevTools #Developertools
AI-Enabled IP-Based Workflows with NVIDIA Rivermax and NVIDIA Jetson NVIDIA Developer 2022-09-28 | Learn about the next-generation IP broadcast workflow and how to simplify the adoption of SMPTE ST 2110 standards with this demo from NVIDIA and Dell Technologies. We will showcase IP-based content creation capabilities and the deployment of AI in the broadcast pipeline, from workstation to the edge. nvidia.com/en-us/industries/media-and-entertainment/professional-broadcast/?ncid=so-yout-548374-vt20#cid=ix17_so-yout_en-usNVIDIA, SMPTE ST 2110, IB-based content, Ai, Broadcast, workstations, Networking, Rivermax, Mellanox
Broadcast 8k video over ST 2110 in Real Time with RED Connect and NVIDIA Rivermax NVIDIA Developer 2022-09-28 | Explore how NVIDIA Networking technologies, including Rivermax, ConnectX, and NVIDIA BlueField DPU along with NVIDIA RTX GPU enable real-time 8K raw video over ST 2110. In this demo from NVIDIA and RED Digital Cinema, we will showcase a direct connection that allows cinema-quality RED V-RAPTOR 8K content to feed into an IP broadcast production workflow.Learn more: nvidia.com/en-us/industries/media-and-entertainment/professional-broadcast/?ncid=so-yout-548374-vt20#cid=ix17_so-yout_en-usNVIDIA, IBC, Networking, GPU, 8k video, ST 2110, IP Broadcast, Video Streaming
NVIDIA GET3D: AI Model to Populate Virtual Worlds with 3D Objects and Characters NVIDIA Developer 2022-09-23 | Trained using only 2D images, NVIDIA GET3D generates 3D shapes with high-fidelity textures and complex geometric details. These 3D objects are created in the same format used by popular graphics software applications, allowing users to immediately import their shapes into 3D renderers and game engines for further editing. blogs.nvidia.com/blog/2022/09/23/3d-generative-ai-research-virtual-worlds#ai, #3D, #deeplearning, #nvidia, #NVIDIAResearch, #GTC22deep learning, AI, 3D, triangle mesh, NVIDIA, NVDIAResearch
Building and Deploying a Multi-Stage Recommender System with NVIDIA Merlin NVIDIA Developer 2022-09-19 | Newcomers to recommender systems often face challenges related to their lack of understanding of how these systems operate in real life. In most online content related to this topic, the focus is on models and algorithms that score items based on the user’s preferences. However, the recommender model alone does not comprise everything needed for serving optimized recommender systems that meet the company’s business objectives. An industry-standard recommender system involves a number of steps, including data preprocessing, defining and training recommender models, as well as filtering and business logic for serving. In this work, we propose the four-stage recommender system, an industry-wide design pattern we have identified for production recommender systems. The four-stage pipeline includes an item retrieval step that prepares a small subset of relevant items for scoring. The filtering stage then cleans up the subset of items based on business logic such as removing out-of-stock or previously seen items. As for the ranking component, it uses a recommender model to score each item in the presented list based on the preferences of the user. In the final step, the scores are re-ordered to provide a final recommendation list aligned with other business needs or constraints such as diversity. In particular, the presented demo demonstrates how easy it is to build and deploy a four-stage recommender system pipeline using the NVIDIA Merlin open-source framework.Learn more: nvda.ws/3d6erlE#recommendersystems #ai #deeplearning #demo #GTC22
Simplifying AI Cluster Management with NVIDIA Base Command NVIDIA Developer 2022-09-19 | AI clusters are difficult to manage. There are multiple hardware and software elements to coordinate and constant updates that can be extremely time consuming. DIY approaches also require diverse skills spanning networking, compute, and storage.NVIDIA Base Command is the operating system of the accelerated data center. It lets organizations use the full potential of their NVIDIA DGX investment with a proven platform that includes enterprise-grade orchestration and cluster management, as well as libraries that accelerate compute, storage, and network infrastructure. Plus, it features an operating system that's optimized for AI workloads.The cluster management features of Base Command automate the end-to-end management of systems, from a single node to thousands. Base Command provides a single-pane-of-glass view that gives you complete control of heterogeneous clusters of any size. To learn more about Base Command, please visit nvidia.com/base-command. To learn more about DGX systems, please visit nvidia.com/dgx#AIinfrastructure #networking #clustermanagement
Kubernetes Operator to Accelerate Production-Ready AI NVIDIA Developer 2022-09-19 | NVIDIA is making it easier to explore enterprise AI and accelerate the creation of machine learning-powered applications—called Intelligent Applications. Achieving this requires two things: best-in-class AI tooling and an intuitive user experience. With NVIDIA AI Enterprise, we deliver industry-leading AI tools from both NVIDIA and open-source communities. Now, with the AI Workspace Operator for Kubernetes, we're working to make that tooling exceptionally simple to deploy, run, and operate on your Kubernetes cluster, regardless of whether it is in the cloud, in your data center, or on the edge.To get started check out the project on GitHub:github.com/NVIDIA/ai-workspace-operator
Easily Scale AI/ML Workloads with VMware vSphere NVIDIA Developer 2022-09-19 | VMware vSphere gives you an easy way to increase training performance by scaling AI/ML workloads across multiple GPUs and servers. This demo shows an image-classification training job being executed on multiple GPUs and nodes by using Tanzu in VMware vSphere. The GPU and MPI operators are used in a custom container to easily standardize and replicate the training job across the data center. Learn how to scale AI/ML in the hands-on lab Multi-Node Training for AI on Kubernetes nvidia.com/en-us/launchpad/ai/multi-node-training-for-image-classification-on-kubernetes-with-vmware-tanzuIT admins can learn how to build this environment in the lab Optimize AI and Data Science Workloads nvidia.com/en-us/launchpad/infra-optimization/configure-optimize-and-orchestrate-resources-for-ai-and-data-science-workloads-with-vmware-tanzuEnterprises can also build and take AI/ML solutions to production with NVIDIA AI Enterprise.nvidia.com/en-us/data-center/products/ai-enterprise
Maintaining Eye Contact in a Video Conference with NVIDIA Maxine NVIDIA Developer 2022-09-19 | Maintaining eye contact is crucial to establishing engagement and trust in a conversation. This can be challenging in a video conference because it requires participants to look at the camera instead of the screen. The NVIDIA Maxine Eye Contact feature creates an in-person experience for virtual meetings. Powered by AI, Maxine Eye Contact directs your eyes to a centered position to maintain eye contact with your audience. Eye Contact is available to developers through the Maxine Augmented Reality SDK at developer.nvidia.com/maxine#ar-sdk. Learn more about Maxine at developer.nvidia.com/maxine and all of NVIDIA's AI solutions at nvidia.com/en-us/deep-learning-ai/products/solutions #AI #NVIDIA #Maxine
Building BETSY, Worlds First AI Ranch Hand NVIDIA Developer 2022-09-19 | Learn how NVIDIA tools allow OneCUP to build the world's first AI ranch hand: BETSY. Leveraging TAO Toolkit and DeepStream, a small team of dedicated developers created an application to help ranchers raise healthy animals. Learn more about NVIDIA DeepStream SDK nvda.ws/3eOctGZLearn more about NVIDIA TAO Toolkit nvda.ws/3dai9L5
Deploying AI at the Edge with NVIDIA Fleet Command NVIDIA Developer 2022-09-19 | Learn how NVIDIA Fleet Command simplifies the deployment and management of AI in existing edge environments. Try Fleet Command today for free on NVIDIA LaunchPad developer.nvidia.com/blog/managing-edge-ai-with-fleet-command-and-launchpad#EdgeAI
Getting Started with NVIDIA Triton Inference Server NVIDIA Developer 2022-09-07 | Triton Inference Server is an open-source inference solution that standardizes model deployment and enables fast and scalable AI in production. Because of its many features, a natural question to ask is, where do I begin? Watch the video to find out!GitHub: github.com/triton-inference-server/serverDocumentation: github.com/triton-inference-server/server/tree/main/docs#ai #inference #nvidiatriton
NVIDIA RecSys Summit 2022 - China Day NVIDIA Developer 2022-08-29 | Watch on-demand: Hear learnings and best practices from fellow experts from NVIDIA, Alibaba, Tencent, and Meituan on how they built and deployed effective modern recommender systems. 0:00:00 - [NVIDIA] Merlin RecSys on GPU0:18:50 - HugeCTR for Training0:32:00 - HugeCTR for Inference0:40:31 - NVIDIA Customer Testimonial0:41:50 - [Alibaba Cloud] DeepRec: GPU Training and Prediction in Search Promotion Scenarios1:08:10 - [Meituan] Large-Scale RecSys on GPU at Life-Service Scenario1:40:45 - [Tencent] Large-Scale Machine Learning Framework - Wu Liang Speakers: Wenwen Gao, Senior Product Manager, NVIDIAJoey Wang, Senior Developer Manager, NVIDIATongxuan Liu, Senior Tech Engineer, Alibaba CloudJiaheng Rang, Machine Learning Engine Technical Expert, MeituanZhuo Chen, Machine Learning Engine Technical Expert, MeituanZhaokai Luo, Machine Learning Engine Technical Expert, Tencent
NVIDIA FLARE 101: Overview and Getting Started NVIDIA Developer 2022-08-11 | Learn the basics of NVIDIA FLARE, including key components and installation options. NVIDIA FLARE™ (NVIDIA Federated Learning Application Runtime Environment) is a domain-agnostic, open-source, and extensible SDK for Federated Learning. It allows researchers and data scientists to adapt existing ML/DL workflow to a federated paradigm and enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration.Learn more: nvda.ws/3JOuUak#AI #federatedlearning #SDK #ML
NVIDIA GauGAN360 NVIDIA Developer 2022-08-09 | 3D artists can customize AI art for backgrounds with a simple web interface. As the next evolution of NVIDIA GauGAN -- an AI model that turns rough doodles into photorealistic masterpieces -- GauGAN360 generates 8K, 360-degree panoramas that can be ported into Omniverse scenes. Try the technology and see how AI can bring 360-degree images to life.Learn More: blogs.nvidia.com/blog/2022/08/09/neural-graphics-sdk-metaverse-contentInteractive Demo: http://imaginaire.cc/gaugan360#AI #GauGAN #nvidiaomniverse #siggraph2022 #siggraph
NVIDIA NeuralVDB Brings AI and GPU Optimization to OpenVDB NVIDIA Developer 2022-08-09 | NeuralVDB delivers up to 100x reduction in memory footprint for smoke, clouds and other sparse volumetric data.Over the past decade, OpenVDB has become the Academy Award-winning, industry- standard library for sparse dynamic volumes. NVIDIA is now further expanding the capabilities of OpenVDB with the power of AI. NeuralVDB builds on top of the GPU acceleration of NanoVDB, adding machine learning to introduce compact neural representations that dramatically reduce its memory footprint.Learn more at nvda.ws/3vKmNWg. CONNECT WITH US ON SOCIALTwitter: twitter.com/NVIDIADesign LinkedIn: linkedin.com/showcase/nvidia-design-and-visualization
Performance Capture Possible With Any Camera with NVIDIA AI NVIDIA Developer 2022-08-09 | Performance Capture with Vid2Vid Cameo:With NVIDIA Vid2Vid Cameo, creators can harness AI to capture their facial movements and expressions from standard 2D video taken with a professional camera or a smartphone. The performance can be applied in real time to animate an avatar, character or painting. And with 3D body pose estimation software, creators can capture full body movements like walking, dancing or performing martial arts, using them to bring virtual characters to life with AI. Read more: blogs.nvidia.com/blog/2022/08/09/ai-performance-capture#AI #Vid2vid #NVIDIAResearch #avatar
Optimizing Model Deployments with Triton Model Analyzer NVIDIA Developer 2022-07-28 | How do you identify the batch size and number of model instances for the optimal inference performance? Triton Model Analyzer is an offline tool that can be used to evaluate 100’s of configurations to meet the latency, throughput & memory requirements of your application.Get started with model analyzer here: github.com/triton-inference-server/model_analyzer#Triton #Inference #ModelAnalyzer #AI
How to Run Multiple Applications on the Same Edge Device with Fleet Command NVIDIA Developer 2022-07-18 | Partition GPUs to give dedicated resources to applications at the edge with Multi-Instance GPU (MIG) on Fleet Command. Check out how to bring GPU resources to every application in this short demo. Get a full walkthrough here: nvda.ws/3AJ0VxO#edgeAI #edgecomputing #MIGKubernetes cloud services, cloud application deployment, cloud deployment platforms, cloud deployment technologies, cloud software deployment, deploy to container, openshift deployment, software deployment platform, Kubernetes management, container management, container orchestration, ai application deployment, ai container orchestration
How to Use Remote Management on Fleet Command NVIDIA Developer 2022-07-18 | Remotely accessing systems and applications on Fleet Command is easy. Learn how you can troubleshoot systems and applications with remote management in this demo. Get a full walkthrough here: nvda.ws/3uMpciH#edgeAI #edgecomputing #remotemanagement Kubernetes cloud services, cloud application deployment, cloud deployment platforms, cloud deployment technologies, cloud software deployment, deploy to container, openshift deployment, software deployment platform, Kubernetes management, container management, container orchestration, ai application deployment, ai container orchestration
Instant NeRF Sweepstakes NVIDIA Developer 2022-07-15 | Our Instant NeRF is a neural rendering model that learns a high-resolution 3D scene in seconds — and can render images of that scene in a few milliseconds.Winners posted here: youtu.be/RyEVh1Orv2YLearn more about Instant NeRFs: nvda.ws/3AU5wgATutorial on how to make a 3D render from 2D photos: nvda.ws/3ciMLJIFind the code on GitHub: github.com/NVlabs/instant-ngpMore Instant NeRF creators: blogs.nvidia.com/blog/2022/08/05/instant-nerf-creators-siggraphFor business inquiries, please visit our website and submit the form on NVIDIA Research Licensing: nvidia.com/en-us/research/inquiriesThe sweepstakes has now closed: full details are here: nvda.ws/3N5kL9Q. #InstantNeRFSweepstakes #NeRF #AI #3D #NeuralRendering #volumetric #photogrametry #syntesis #NVIDIA #NVIDIAResearch #InstantNGP #computervision #NeRFs
NVIDIA Research StyleGAN-NADA NVIDIA Developer 2022-07-15 | Sketch-to-Drawing ... Check out new NVIDIA Research that generates artistic images with only a text prompt and few minutes of training.Neural rendering algorithms learn from real-world data to create synthetic images — and NVIDIA research projects are developing state-of-the-art tools to do so in 2D and 3D.In 2D, the StyleGAN-NADA model, developed in collaboration with Tel Aviv University, generates images with specific styles based on a user’s text prompts, without requiring example images for reference. Learn more about our #SIGGRAPH2022 accepted papers: https://nvidia.com/en-us/events/siggraph and blogs.nvidia.com/blog/2022/05/04/siggraph-ai-graphics-research-collaboration
NVIDIA FLARE Tutorial for Beginners NVIDIA Developer 2022-07-14 | This video introduces how to install NVIDIA FLARE (NVIDIA Federated Learning Application Runtime Environment) and how to start your first Federated Learning project with NVFlare on Cifar10 dataset.Reference: github.com/NVIDIA/NVFlare and nvflare.readthedocs.io/en/main/index.html Continue learning with NVFLARE documentation: nvidia.github.io/NVFlare NVFlare, Federated Learning, Cifar10, NVIDIA FLARE
Get Started with Edge AI on NVIDIA LaunchPad NVIDIA Developer 2022-07-13 | See how you can provision edge infrastructure, deploy and manage the lifecycle of AI applications, and monitor your edge fleet with NVIDIA Fleet Command. Get Started: nvda.ws/3cfESVv#edgeai #edgecomputing #freetrial Kubernetes cloud services, cloud application deployment, cloud deployment platforms, cloud deployment technologies, cloud software deployment, deploy to container, openshift deployment, software deployment platform, Kubernetes management, container management, container orchestration, ai application deployment, ai container orchestration
NVIDIA Riva Automatic Speech Recognition for AudioCodes VoiceAI Connect Users NVIDIA Developer 2022-07-05 | Check out this demo on how NVIDIA Riva automatic speech recognition (ASR) integrates with AudioCodes VoiceAI Connect. Similarly, you can deploy Riva’s text-to-speech (TTS) out-of-the-box female or male professional voice, or your unique brand voice created with only 30 min of data.Learn more:NVIDIA Riva: nvda.ws/3tf1GKjNVIDIA Riva Quickstart Guide: nvda.ws/3azmSVbNVIDIA Riva Documentation: nvda.ws/3miAzu6NVIDIA Riva WebSocket Bridge: github.com/nvidia-riva/websocket-bridge#AI #speechAI #speechrecognition #texttospeech #asr #tts
Isaac Stereo Camera Depth Perception NVIDIA Developer 2022-07-01 | See how Isaac ROS provides multiple diverse and independent stereo camera depth perception functions for the development of autonomous robots. In this example, video sequences of real and simulator data showcase machine perception with the ESS DNN for depth prediction, BI3D DNN for proximity detection, and SGM (semi-global matching) for depth feature matching.Download:github.com/NVIDIA-ISAAC-ROSLearn more on Isaac ROS:developer.nvidia.com/isaac-rosPost queries or comments on the Isaac Forum:forums.developer.nvidia.com/c/agx-autonomous-machines/isaac/isaac-ros/600
Run Jupyter Notebooks from the NVIDIA NGC Catalog with a Single Click NVIDIA Developer 2022-06-24 | The NGC catalog now provides a one-click deploy approach to run Jupyter notebooks on Google Cloud's Vertex AI Workbench. This allows data scientists and developers to focus on building AI instead of setting up a development environment.Visit the NGC catalog today to browse our collection of Jupyter notebook examples and run it using Click Deploy. nvda.ws/3sOtT9Z #nvidia #ai #googlecloud #jupyternotebook #jupyter #artificialintelligence
AI in the Big Easy: NVIDIA Research Lets Content Creators Improvise With 3D Objects NVIDIA Developer 2022-06-21 | Jazz is all about improvisation — and NVIDIA is paying tribute to the genre with AI research that could one day enable graphics creators to improvise with 3D objects created in the time it takes to hold a jam session. The method, NVIDIA 3D MoMa, could empower architects, designers, concept artists and game developers to quickly import an object into a graphics engine to start working with it, modifying scale, changing the material or experimenting with different lighting effects. nvda.ws/3QnNJnt #NeRF #AI #CVPR
The Rise of DeBERTa for NLP Downstream Tasks – Grandmaster Series, E7 NVIDIA Developer 2022-06-17 | In episode seven of the Grandmaster Series, you’ll learn from four members of the Kaggle Grandmasters of NVIDIA (KGMON) team. Watch this video to learn how they used natural language processing to analyze argumentative writing elements from students and identified key phrases in patient notes from medical licensing exams. Subscribe to our Youtube channel to see new Grandmaster Series episodes. If you have any questions during the video, you can submit them through chat. We will try to provide answers throughout and at the end of the episode.About our presenters: Chris Deotte, senior data scientist at NVIDIA. Chris has a Ph.D. in computational science and mathematics with a thesis on optimizing parallel processing. Chris is a 4x Kaggle grandmaster.Dr. Christof Henkel, a Ph.D. in mathematics with a focus on probability theory and stochastic processes and is a senior deep learning scientist at NVIDIA. He is a 3x Kaggle grandmasterJean-Francois Puget, holds a Ph.D. in machine learning and has published over 70 scientific papers in peer-reviewed conferences and journals. He is a 2x Kaggle grandmaster.Ahmet Erdem is currently a Senior Data Scientist at NVIDIA with a background in Computer Engineering and Artificial Intelligence. Additional Resources: 1. Get Started on NLP and Conversational AI with NVIDIA DLI Courses: developer.nvidia.com/blog/get-started-on-nlp-and-conversational-ai-with-free-courses-from-nvidia-dli2. Instructor-led Workshop - Building Transformer-Based Natural Language Processing Applications: nvidia.com/en-us/training/instructor-led-workshops/natural-language-processing3. Applying Natural Language Processing Across the World’s Languages: developer.nvidia.com/blog/applying-natural-language-processing-across-the-worlds-languagesFollow us on Twitter: twitter.com/NVIDIAAI
NVIDIA DeepStream Technical Deep Dive : Multi-Object Tracker NVIDIA Developer 2022-06-16 | NVIDIA’s DeepStream SDK delivers a complete streaming analytics toolkit for AI-based multi-sensor processing, video, audio and image understanding. This video covers the fundamentals of NVIDIA’s new tracker unified architecture. From the video, you will:• Learn how to select from the 3 object tracker alternatives (NvDCF, DeepSORT or IOU) or bring your own tracker to DeepStream for vision AI app development.• Get to know the state machine behind the tracker and what parameters can be configured to optimize the tracker for your specific application. • Understand how NVIDIA’s state-of-the-art tracker (NvDCF) can compare different configuration parameters, along with the different results and tradeoffs that come from different optimization strategies.More information about DeepStream tracker: • Review the DeepStream Low-Level Tracker Comparisons and Tradeoffs for help choosing the best tracker for your application: docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_plugin_gst-nvtracker.html#low-level-tracker-comparisons-and-tradeoffs• Read the NvMultiObjectTracker Parameter Tuning Guide to learn how to troubleshoot and fine-tune tracker configurations: nvda.ws/3NZmbTG• Check out the Gst-nvtracker plugin documentation for detailed information on how to work with the low-level tracking libraries and how to implement your own: nvda.ws/3xyZnTI• DeepStream get Started resources: nvda.ws/39vuk3u
Jetson AI Labs – E09 – JetMax robotic arm & Leukemia detection NVIDIA Developer 2022-06-13 | In this episode, we have Sylvia from Hiwonder showing us the fantastic capabilities they achieved with their robotic arm, which is powered by a Jetson Nano. We also have invited Adam, who is running a project to detect Leukemia by using a Jetson Nano to do the inference over images of real cells. If you have a project with Jetson, and you want to participate in one of these episodes please contact us.
