AI Spectrum

Virtual testing of products has significantly been improved by the use of AI. We can now use models based on data from previous development cycles to create feasible designs faster. This translates to a shorter time to market and a lower cost of simulation because optimal cases are identified in advance.

In this episode, the second part of two, Spencer Acain interviews Justin Hodges, AI/ML specialist and Product Manager for Siemens Simcenter. He’ll help us understand how AI’s predictive capabilities help in simulation. He’ll also share with us how Siemens is approaching the field of AI/ML.

Tune in and learn more about how AI/ML is being applied in the world of product modeling and testing.

In this episode, you will learn:

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Simulation of digital models has completely transformed the product development process. However, it can be a time-consuming and expensive venture if the product being developed has many components. AI technology simplifies this process by creating thousands of models and test scenarios within a few hours.

In this episode, the first part of two, Spencer Acain interviews Justin Hodges, AI/ML specialist and Product Manager for Siemens Simcenter. He’ll help us understand how the different ways in which Simcenter is using AI technology. He’ll also share with us the benefits of using AI in simulation.

Tune in and learn more about how AI is transforming the world of product modeling and testing.

In this episode, you will learn:

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Companies look for every advantage over their competitors that can help them bring new products to the market faster and at a lower cost. One of the ways to increase the speed to market is by improving the design speed. That is why Siemens NX has developed a new Sketch Solver that makes design work easier, more accurate, and faster.

I’m your host, Spencer Acain, and today I’m joined by Scott Felber, Product Marketing Manager Siemens NX Design. And, Mike Yoder, who works with the Product Management group focused on the NX design tools. They’ll help us understand the new Sketch Solver and the impact it is having on the market.

In this episode, you’ll learn about how Siemens NX’s new Sketch Solver works and how it compares to the traditional Solver. You’ll also learn about the new features that have been introduced and how they impact design speed and accuracy. Additionally, you’ll learn about how the market is reacting to this new product.

What You’ll Learn in this Episode:

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Automation helps in accelerating repetitive but critical tasks that consume too much time. However, determining the tasks to automate requires deep knowledge of the actual steps, in chronological order, necessary to complete a process. Siemens NX is accelerating the design process by using knowledge gathered from past models to automate predictable tasks.

In this episode, the second part of two, Spencer Acain interviews Shirish More, Product Manager at Siemens Digital Industries Software, responsible for driving innovations inside Siemens NX. He’ll share with us how Siemens NX is using AI to accelerate the design process.

Tune in and learn more about how AI is transforming the world of mechanical engineering software.

In this episode, you will learn:

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• LinkedIn

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Imagine an engineering software that anticipates the commands you want to execute by studying your usage patterns. Such a feature would definitely decrease the design time as well as increase your overall user experience. That’s exactly what Siemens NX is doing thanks to its machine learning capabilities.

In this episode, the first part of two, Spencer Acain interviews Shirish More, Product Manager at Siemens Digital Industries Software, responsible for driving innovations inside Siemens NX. He’ll share with us how they are using AI to personalize NX users’ experience and improve productivity.

Tune in and learn more about how AI is transforming the world of mechanical engineering software.

In this episode, you will learn:

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• LinkedIn

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Creating an accurate AI model requires millions of images and data points to be fed into the computing system. This is a difficult task that can slow down the speed to market or lower the accuracy of the model that is created. Synthetic data helps in solving this problem by reducing the amount of real data that needs to be collected. That results in reduced time to market and increased model accuracy.

In today’s episode, I’m talking to Zachi Mann. He leads a new initiative that is focused on advanced robotics simulation capabilities at Siemens. He’ll help us understand AI model training for factory robots. He’ll also share with us how Siemens solutions such as CAD and NX help in model development.

In this episode, you’ll learn about the use of synthetic data in training AI-reliant factory robots. You’ll also learn about the challenges and the benefits that come with combining synthetic data with real data. Additionally, you’ll learn about Synth AI, a new synthetic data generating solution from Siemens.

In this episode, you will learn:

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Integration of AI into engineering solutions has changed how engineers approach product selection and development. One of the areas that have benefited the most from this integration is performance simulation. It has led to accurate decisions being made much faster as engineers use accurate insights that AI makes available to them.

In today’s episode, I am talking to Krishna Veeraraghavan - Project Manager at Siemens Digital Industries Software. We’ll discuss the role AI is playing in computational fluid dynamics (CFD), the benefits and the challenges in implementing AI into CFD simulations, as well as the different techniques that are deployed in CFD.

Tune in and learn more about the process of integrating AI into CFD, and the impact it’s having on the users.

In this episode, you will learn:

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• LinkedIn

Artificial intelligence has come a long way in the last few years and it is making a significant impact in many industries. However, there is still notable reluctance to hand over more operations to AI-based systems because they are still not seen as being robust enough to be fully relied upon.

In today’s episode, I am talking to Michael Berger, the head of Munich Reinsurance’s AI Insurance Unit, and Boris Scharinger, a senior innovation manager at Siemens Digital Industries. We’ll discuss AI performance risk insurance and the progress of industrial-grade AI.

Tune in and learn more about what’s happening in the field of AI, the challenges it’s facing, and what the future holds for it.

In this episode, you will learn:

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• LinkedIn

Computer vision is one of the fastest-growing AI fields. This has been fuelled by the progress made in data models training and its widespread adoption. Automation that results from this increases the quality of products and lowers the cost of production.

In today’s episode, I’m talking to Shahar Zuler, a data scientist and machine learning engineer at Siemens. We'll discuss object recognition in factories and the unique challenges being faced in its deployment. 

Tune in and learn more about computer vision in machine learning as well as the use of synthetic data in model training.

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In this episode, you will learn:

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• LinkedIn

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• LinkedIn

Artificial intelligence is becoming increasingly more common in the workplace. To really understand how it works and the benefits that it can bring about, talking to people with first-hand experience is key. To learn more about how AI technology is being used, we turn to our very own experts here at Siemens.  

In today’s episode, I’m talking to Roberto D'Ippolito, Senior Technical Product Manager of the HEEDS team at Siemens Digital Industries Software based in Belgium. We’ll discuss the range of possibilities within AI, where all that data comes from, and how to create value from it. AI has the potential to offer big advantages over the competition, and machine learning puts all of the information into focus. 

You’ll also learn where HEEDS fits into the simulation equation, the key benefits of using the technology, and the process of designing automated vehicles so that unpredictable situations are accounted for. We’ll wrap up by touching on a few misconceptions about AI, and where it might lead us in the future.  

In this episode, you will learn:

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