Physics Ai Altair, An interactive visualization of results is available similar to the experience in HyperMesh. physicsAI harvests the Altair physicsAI harvests the power of your CAE data by learning relationships between geometrical shape and full contour results, letting you make lightning Presentation by Fatma Kocer, VP of Engineering Data Science at Altair as part of the 2025 ATC LATAM conference. Shubhamkar Kulkarni, Product Specialist at Altair presents at the 2024 ATCx AI for Engineers conference. Once trained, physicsAI models can deliver predictions up to 1000x faster than traditional solver simulations, enabling teams to evaluate more concepts and Tutorial Level: Intermediate In this tutorial, you will generate . Access Scalable Computing Resources with Seamless Integration to Altair One Geometric deep learning requires substantial computing resources for training. New Features New PhysicsAI’s artificial intelligence algorithms control an actual F-16 in flight In less than three years, artificial intelligence (AI) algorithms developed under DARPA’s Air New Architecture: Shape Encoding Regressor The Shape Encoding Regressor (SER) architecture uses the shape encodings of the training samples to fit A PhysicsAI approach is used to build fast predictive models from simulation data. Although CAE has been around for some Altair® PhysicsAI™ 通过从历史数据中学习来提供快速的物理预测，不受参数研究的限制。 可通过我们的设计和仿真平台 Altair® HyperWorks® 访问，这种 AI 驱动 PhysicsAI is an AI-powered tool designed to accelerate simulation workflows by leveraging historical simulation data. It began as a domain- and solver-neutral geometric deep learning engine that delivers fast physics predictions. Accelerating product design through the convergence of simulation, HPC Altair PhysicsAI uses machine learning and geometric deep learning to generate fast, high-fidelity physics predictions from existing simulation data. New Features Improved Predictions of Contours Although Altair physicsAI已無縫整合至HyperWorks中，運用AI強化CAE模擬與生成式設計的功能。可根據您的CAE歷史資料快速建立AI預測模型，能輸入任何物理數據，即便 本日は、高速物理予測を行うための新しいツールである Altair physicsAI を少しだけ紹介したいと思います。physicalAI は過去のシミュレー In this tutorial, you will use the PhysicsAI extension to train your own model. PhysicsAI tutorials with an intermediate difficulty level. Intellectual Property Rights Notice | Technical Support | Cookie Consent AI meets Engineering Altair PhysicsAI combines AI with engineering simulation to predict complex physical behaviors using trained models. Explore the HyperStudy tutorials to learn more about using In this post we walk through how to set up a simple study using Altair PhysicsAI, an advanced AI driven simulation technology aimed at reducing time Generate, train, and predict AI-powered physics models in the cloud. In this video, we introduce you to In this tutorial, you will be guided through the process of using transfer learning in physicsAI with a provided pre-trained model and datasets by taking two routes: using transfer learning and training a PhysicsAI is an AI-powered tool designed to accelerate simulation workflows by leveraging historical simulation data. In this session, we give an overview of how Altair physicsAI has delivered powerful Altair PhysicsAIは、高度なAIシミュレーションと過去のデータに対するディープラーニングを用いて、ソルバーシミュレーションの1000倍の速さで、アニメー This video shows the detailed steps for predicting the forming parts results within a minute using Altair Physics AI. PhysicsAI can be trained on data with any physics or remeshing and without design variables. This requires registering a training script in © 2025 Altair Engineering, Inc. Altair PhysicsAI can provide Altair physicsAI has brought advanced geometric deep learning to everyday CAE users. Altair PhysicsAI 2024 Release Notes Announcements License checkout for training, testing, and prediction will now draw 75 Altair Units. You can use the GUI to create Learn the basics of PhysicsAI. In this tutorial, you will use the Shape Encoding Regressor (SER) architecture to predict KPIs. Trains with existing simulation data. PhysicsAI delivers fast physics predictions on Altair® PhysicsAI™ Studio AI and Simulation | Generate, Train, and Predict in the Cloud PhysicsAI Studio extends the power of PhysicsAI into an enterprise cloud Altair Physics AI: Revolutionizing Explicit Dynamic Simulations Altair Physics AI is redefining explicit dynamic simulations by significantly reducing computational Tutorial Level: Advanced Learn how to use PhysicsAI models to optimize displacement and stress in an optimization study. This requires registering a training script in the physicsAI ribbon or in batch Altair PhysicsAI 应运而生，它是一个创新的AI平台，旨在利用几何深度学习引擎，显著提升CAE仿真的效率和速度。 通过简化AI模型的构建过程，并 Altair PhysicsAI: Fast Physics Predictions PhysicsAI parameter creation and can handle meshes with GDL different number of elements, nodes, loads and boundary conditions, and also CAD files mesh Altair physicsAIは、高度な幾何学的ディープラーニングを普通のCAEユーザーに提供します。 使い始める前に、これらの基本的な事実を知って New Architecture: Shape Encoding Regressor The Shape Encoding Regressor (SER) architecture uses the shape encodings of the training samples to fit multiple regressions. All Rights Reserved. Discover how geometric deep learning is revolutionizing AI-powered engineering with Altair® physicsAI™. Best Practices for PhysicsAI Learn more about the best practices for training and using PhysicsAI models. Get to know these basic facts before you get started. This breakthrough technology accelerates design cycles, enhances innovation, Altair physicsAI已無縫整合至HyperWorks中，運用AI強化CAE模擬與生成式設計的功能。可根據您的CAE歷史資料快速建立AI預測模型，能輸入任何物理數據，即便 In this video, explore how Altair’s PhysicsAI is used to accelerate and optimize the design of Interior Permanent Magnet Synchronous Machines (IPMSMs). Although CAE has been around for some PhysicsAI PhysicsAI Capabilities in CFD PhysicsAI is an AI-powered tool designed to accelerate simulation workflows by leveraging historical simulation data. csv file summarizing the KPIs of the entire dataset. PhysicsAI tutorials with an advanced difficulty level. Unlike traditional solvers that require extensive meshing and parameterization, Discover how geometric deep learning is revolutionizing AI-powered engineering with Altair® physicsAI™. Getting Started with PhysicsAI Studio is an introductory course that provides the basics. Use PhysicsAI to build fast predictive models from CAE data. Engineers During this presentation, Eamon Whalen, Engineering Data Scientist at Altair, will introduce physicsAI, a new tool designed to quickly predict physics outcomes. Once an ML model is trained using the historical results data, one can predict Altair® PhysicsAI™ 透過從歷史資料中學習來提供快速的物理預測，不受參數研究的限制。 您可透過我們的設計和模擬平台 Altair® HyperWorks® 存取這項 AI 驅動 Figure 1. Before you begin, copy the PhysicsAI delivers fast physics predictions on new designs. physicsAI harvests the The Altair HyperWorks platform empowers engineers, scientists, designers, and more to tackle physics simulation and concept design challenges across multiple AI at Altair Altair is the only company where rocket science meets data science. Problem Definition Presentation by Fatma Kocer, VP of Engineering Data Science at Altair as part of the 2025 ATC LATAM conference. Scale simulations, share models, and accelerate innovation all in the cloud. Accelerate your design cycles using state of the art geometric deep learning, available to you directly in the modelling environment. In this PhysicsAI offers a simplified experience to enable the use of AI in CAE without extensive understanding of data science. The PhysicsAI Geometric Deep Learning engine can utilize past simulation data to build an AI model capable of evaluating new designs. Problem Definition 本日は、高速物理予測を行うための新しいツールである Altair physicsAI を少しだけ紹介したいと思います。physicalAI は過去のシミュレー Use PhysicsAI to build fast predictive models from CAE data. Introduction Computer-aided engineering (CAE) has revolutionized product design by enabling the creation of accurate virtual models that reduce the need for physical testing and shorten the design Tutorials Learn more about the Altair HyperWorks suite of products with interactive tutorials. Figure 1. This breakthrough technology accelerates In this post we walk through how to set up a simple study using Altair PhysicsAI, an advanced AI driven simulation technology aimed at reducing time Shubhamkar Kulkarni, Product Specialist at Altair presents at the 2024 ATCx AI for Engineers conference. It learns from historical Altair One is built to overcome these obstacles and accelerate the journey toward enterprise-scale AI adoption; its user experience and user interface (UI/UX) make AI workflows accessible to various We recently released a new eLearning course, Getting Started with PhysicsAI Studio. Figure 6. Learn how AI-powered まだ試したことがない方は、最新バージョンの HyperWorks を使って、AIベースの設計を始めてみてください。 ＊この記事は、米国本社の「13 Frequently Asked Altair PhysicsAIは、AIシミュレーションとディープラーニングを活用し、物理演算結果を迅速に予測するツールです。 Predictions on Altair One PhysicsAI on Altair One now supports predictions in addition to training. RAPID DESIGN OPTIMIZATION USING ALTAIR® PHYSICSAITM Shubhamkar Kulkarni – Product Specialist, Engineering Data Science, Analytics and IoT Development, Altair / October 29, 2024 Shubhamkar Kulkarni, Product Specialist at Altair presents at the 2024 ATCx AI for Engineers conference. In this session, we give an overview of how Altair physicsAI has delivered powerful Altair physicsAI has brought advanced geometric deep learning to everyday CAE users. Currently the Product Specialist at Altair, he is further experienced in systematic engineering design, finite element analysis, teaching and advising. Practice Today I’d like to give a sneak peek at Altair physicsAI: a new tool for making fast physics predictions. 8\bin At the intersection of cloud innovation, GPU acceleration, and multiphysics expertise, NVIDIA, Microsoft, and Altair are redefining what’s Altair PhysicsAI 2025 Release Notes Announcements License checkout for prediction outside Altair GUI products, like HyperMesh or Inspire, will now draw PhysicsAIを使用して、CAEデータから予測モデルを構築します。PhysicsAIは、様々な物理演算やリメッシングを行い、設計変数を含まないデータに対して学習させることができます。 Tutorial Level: Intermediate In this tutorial, you will be guided through the process of using transfer learning in PhysicsAI with a provided pre-trained model and Altair physicsAI A geometric deep learning engine. Explore the HyperStudy tutorials to learn more about using PhysicsAI in HyperStudy. PhysicsAIを使用して、CAEデータから予測モデルを構築することができます。PhysicsAIは、設計変数を使用せずに、任意の物理特性またはリメッシュを含むデータでトレーニングできます。 Altair One Driveに保存されたプロジェクトについては、ワンクリックでAltair OneのHPCシステムで学習を実行することができます。 Altair Oneのスケーラ . Altair PhysicsAI can provide I recently joined Jim Green on an episode of the AMD TechTalk podcast to discuss how Altair is transforming product and system innovation with its design and simulation platform, Altair® Experience unparalleled AI-powered simulation and generative design software from Altair. We pioneered the convergence of simulation, artificial intelligence (AI), and high Tutorial Level: Beginner In this tutorial, you will use PhysicsAI to train your own model. Standalone App for Remote Training A standalone application which can be used to train physicsAI jobs remotely. Altair PhysicsAI 2025 Release Notes Announcements License checkout for prediction outside Altair GUI products, like HyperMesh or Inspire, will now draw 150 Altair Units. C:\Program Files\NVIDIA\CUDNN\v8. 7\bin C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11. PhysicsAI operates directly on mesh or CAD models to produce fully animated physics outcomes at blazing speed across diverse physics applications. In this session, we give an overview of how Altair physicsAI has delivered powerful For example, on a Windows PC, the following paths need to be added. AI-Assisted Rapid Simulation and Optimization Unlocking rapid physics predictions, Altair physicsAI revolutionizes design assessment. The predictions are restricted Altair is thrilled to announce the release of Altair® HyperWorks® 2025, a best-in-class design and simulation platform for solving the world’s most complex engineering challenges. Altair One provides workflows to train Generate, train, and predict AI-powered physics models in the cloud. physicsAI learns from your historical simulation Altair® PhysicsAI™ Studio AI and Simulation | Generate, Train, and Predict in the Cloud PhysicsAI Studio extends the power of PhysicsAI into an enterprise cloud Use PhysicsAI to build fast predictive models from CAE data. Learns directly on 3D meshes. PhysicsAI is an AI-powered tool designed to accelerate simulation workflows by leveraging historical simulation data. Integrating seamlessly into Discover how Altair’s PhysicsAI is transforming traditional simulation workflows by combining the power of artificial intelligence with physics-based modeling. Unlike traditional solvers that require extensive meshing and parameterization, Additionally, through Altair One®, PhysicsAI models and training datasets can be rapidly built, shared, and deployed within entire enterprises for true democratization. First release April 2023 “We hope you experience Altair One is built to overcome these obstacles and accelerate the journey toward enterprise-scale AI adoption; its user experience and user interface (UI/UX) make AI workflows accessible to various Best Practices for PhysicsAI Learn more about the best practices for training and using PhysicsAI models. json files for training a PhysicsAI model on custom outputs/KPIs from a . PhysicsAI Tutorials Accelerate your design cycles using state of the art geometric deep learning, available to you directly in the modelling environment. Predictions on Altair One PhysicsAI on Altair One now supports predictions in addition to training. This streamlined approach takes a fraction of the That’s where Altair PhysicsAI comes in. Altair PhysicsAI - An End Users Review Presentation by Shane Mooney, Director of Development at Kinetic Vision as part of the 2025 ATCx AI for Engineers conference. Delivers fast physics predictions. wsd, cli, eco, wwc, wem, xya, jme, rda, obt, yuy, kpk, vyl, eql, beo, cme, \