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Shaping the Future through Artificial Intelligence and Simulation

Discover how visionary companies are leveraging the power of artificial intelligence (AI), machine learning (ML), deep learning (DL), and simulation to take a leap of certainty when solving complex engineering problems.

The Power of Augmented Simulation

Since the first computers, artificial intelligence (AI) has existed as a concept to describe programs that can solve actual problems and execute tasks without being explicitly programmed to do so. Machine learning is a means of realizing AI through making decisions, acting on them, and adapting over time based on the outcome of those decisions. Using artificial neural networks, which are algorithms that attempt to imitate how human brains make decisions, deep learning (DL) unlocks new insights, trains better algorithms, and accelerates engineering innovation.

Ansys uses AI/ML methods to automatically find simulation parameters to improve speed and accuracy simultaneously, and guide early product optimization efforts to help engineers quickly find the best design space based on thousands of parameters. Drive business intelligence and take a leap of certainty with Ansys.

The Benefits of Applying Artificial Intelligence and Simulation

AI/ML is rapidly being successfully adopted by an increasingly broad range of industries and users. We’d expect that AI/ML applications would be actively used in science and medicine, from streamlining drug discovery to robot-assisted surgery to automated medical records that can be instantaneously accessed by providers anywhere in the world. But it’s also helping consumer brands mine their social media to find out how customers feel about their products (sentiment analysis), giving investors a leg up on stock trade opportunities (financial algorithmic trading) and enabling e-commerce owners to personalize offerings to online shoppers (recommendation engines).

At Ansys, we can use AI/ML methods to automatically find the parameters of simulation to simultaneously improve speed and accuracy. We can use augmented simulation to speed up the simulation by factors of 100X by training neural networks via data-driven or physics-informed methods. Advanced simulation technology, enhanced with AI/ML, is underpinning the engineering design process.

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Revolutionizing 3D Surface-Contact Detection via Deep Learning

Behind the scenes, artificial intelligence technologies are reshaping the way new products are developed, verified, and brought to market. Discover the future of surface-contact modeling.

How AI and ML are Changing Simulation

Teaching AI “Brains” Using Digital Twins with Microsoft

Learn how Microsoft Project Bonsai is helping engineers create AI-powered automation without using data science by graphically connecting software modules that have already been programmed to perform certain AI functions.

Simulation-Based Product Innovation

From the earliest stages of design and analysis, simulation improves workflows and increases quality and accuracy. Read how, through the application of artificial intelligence and machine learning, Ansys customers are pushing those boundaries even further.

Ansys + Robert Bosch Engineering

Using Ansys technology, Bosch is creating digital models that take advantage of the capabilities of artificial intelligence (AI) and machine learning, and redefine electric vehicle design.

Ansys + Seagate Technology

Discover how AI/ML-powered simulation is empowering Seagate Technology engineers to achieve the highest possible accuracy in streamlined development workflows.

Accelerate Machine Learning with Simulation

Learn how Ansys Fluent can make effective use artificial intelligence (AI) to improve performance without compromising accuracy. Initial results show an 86X speedup.

Michael P. Brenner is the Michael F. Cronin Professor of Applied Mathematics & Applied Physics and a Professor of Physics at Harvard University. Brenner is also a Research Scientist at Google Research. He presents an overview of his work with Ansys and Google Research in “Machine Learning Convective Discretizations through User-Defined Functions in Fluent.”

How to accelerate product innovations and successfully scale with AI

Artificial Intelligence

Artificial Intelligence has the potential to shift the landscape of most industries. The automation potential of AI alone can rapidly accelerate the pace of design cycles and innovation.


In the last two decades, the industry has seen waves of disruption from high tech and automotive to the industrial and energy sector, all caused by a shift to digital internet platforms. The clear lesson from recent history has been those who move early to focus on building out their capabilities in transformative technologies tend to survive and thrive, and those who don't quite often see a different fate. Although introducing AI will come with its hurdles, those that start their innovation journey now will be able to lead their fields for decades to come.

Join this webinar, hosted by IDC and Ansys, and in collaboration with Infineon and Monolith. Hear how AI impacts product innovation and discover the type of success users of AI already have achieved. Take away key learnings from organizations leading in the field of AI, and learn how to smoothly introduce and scale for AI innovation in organizations.

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By accelerating simulation with artificial intelligence, machine learning and deep learning, engineers are empowered to work with large, complex design more quickly – without sacrificing accuracy for speed.


Ansys Enables Faster, More Reliable Chip Design for Juniper Networks

Ansys helps Juniper achieve highly predictively accurate power integrity signoff in significantly less time with a massively parallelizable design methodology that achieves greater switching coverage and improved reliability.

Car demonstration

Deep Learning Is Poised to end the Trade-off Between Speed and Fidelity

The Ansys research and development team is exploring the potential use of deep learning to solve high-dimensional problems in simulation space much like the problems in computer vision space.

How AI and ML are Changing Simulation

How AI and ML are Changing Simulation

At Ansys, we can speed up simulation by factors of 100X by training neural networks via data-driven or physics-informed methods. We believe that AI/ML will help us narrow the gap between the ideal world and what happens in real life, making simulation productivity, ease of use, and accuracy a little less of a trade-off.

3D Artificial Intelligence Compression

AI and ML: The Brave New World of Simulation

The capabilities of AI and ML are quietly changing the field of engineering simulation. Read how this advanced technology makes the job of product development teams more complex and challenging than ever.

Ansys Expertise

Featured Events

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Safe System Design and Autonomous Vehicle Software Development

How can autonomous development teams working on L3+ systems ensure that they are safer than a human driver while affordable for the business model? For a sustainable business model solution, an intensive trade-off between performance and safety is required in AD system development. Learn how Ansys solutions address critical technical challenges in safe system design and AV Software development.

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Hybrid Digital Twins: Bringing Together the Best of AI and Physics

In this webinar, our panel of experts will discuss how to bring together the best of AI and physics to create hybrid digital twins. Hybrid digital twins implement advanced techniques including physics simulations and virtual sensors. The panelists will also look inside the AI/physics work already underway thanks to the liaison between the AIoT User Group and the Digital Twin Consortium.

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5G Design Innovation Through Simulation

This presentation showcases the past, present and future of mobile networking, and how the convergence of 5G, edge computing and artificial intelligence machine learning will change the industry landscape.

Featured Resources

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Improving Autonomous Vehicle Radar Performance with Simulation

As the world draws near to the reality of fully autonomous automobiles and transport vehicles, there is a great deal of focus on the development of artificial intelligence (AI), machine learning and rapid automated decision-making. While the AI and decision-making systems must plan the vehicle trajectory and response to the environment, the sensors must feed the control systems executing those algorithms with accurate data on the current and developing state of the vehicle’s surroundings.

How Machine Learning Helps Getting Additive Manufactured Parts to Market Faster

For additive manufacturing (AM) to become adopted as a mainstream industrial production technique there remains a challenge: speed + reliability. How can you rapidly optimize process parameters for additive manufactured parts, thus reducing time-to-market?

IDC & Ansys Webinar Post‐Event Executive Summary

Artificial Intelligence has the potential to shift the landscape of most industries. The automation potential of AI alone can rapidly accelerate the pace of design cycles and innovation. Although introducing AI will come with its hurdles, those that start their innovation journey now will be able to lead their fields for decades to come. Download this summary to learn more.


Increasing Additive Manufacturing Build Success With Machine Learning

A new level of insight into additive manufacturing (AM) data enables engineers to control the AM process and optimize material and part performance. Results can be achieved with a greatly reduced number of experimental test cycles.

Optimize High-Speed Serial Links for Crosstalk

NVIDIA turned to Ansys Totem for power grid weakness analysis, point-to-point checks, and a variety of early-stage static and dynamic IR and EM analyses that can highlight design weakness.

Simulate, Compete, Repeat

Racing teams are turning to data analytics, digital twins and artificial intelligence tools on race day to gain an advantage. They can now take real-time data coming from a car and create actionable data on the spot.