PODCAST

AI Spectrum

Siemens Digital Industry Software

AI Spectrum podcasts cover a wide range of artificial intelligence and machine learning topics. Listen to experts within Siemens and their customers talk about the impact of AI, success stories, and the future of AI. Gain insight into real world applications so that you can potentially apply AI within your world.



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Understanding the Role of AI and How to Use Data
02-06-2021
Understanding the Role of AI and How to Use Data
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:How we can utilize AI industrially and in general (1:48)The role of HEEDS (2:57)The key benefit of AI and machine learning technology (6:51)How the adaptive sampling strategy is being used (9:06)How machine learning meets the challenge of designing autonomous vehicles (11:02)The AV design process (14:13)Where all of the data is coming from (18:16)Challenging beliefs and misconceptions about AI (23:21)The future of AI in engineering (25:00)Connect with Roberto D'Ippolito:LinkedInConnect with Thomas Dewey:LinkedIn See acast.com/privacy for privacy and opt-out information.
Deploying AI’s Object Recognition in Factories
15-07-2021
Deploying AI’s Object Recognition in Factories
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.Some Questions I Ask:How do you see AI impacting the industrial industry? (3:06)What are the unique challenges of employing AI/ML in the industrial environment? (10:59)What are you doing at Siemens to help solve the industrial environment’s AI/ML challenges? (19:33)What do you do to validate the correctness of synthetic data? (23:15)Can you predict what you think will happen with machine learning in the next 10 years? (26:57)In this episode, you will learn:Different tasks of computer vision machine learning (11:30)How to train an object detection model (16:34)How synthetic images are used in ML model training (20:56)How to validate synthetic data (23:38)The benefits of partnerships between Siemens and their customers (25:08)Connect with Shahar Zuler: LinkedInConnect with Thomas Dewey: LinkedIn See acast.com/privacy for privacy and opt-out information.
The Use of Synthetic Data in AI model Training
11-05-2022
The Use of Synthetic Data in AI model Training
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:The meaning of synthetic data (03:03)The challenges that come with the use of synthetic data (04:19)The benefits of using synthetic data (08:05)Why the use of synthetic data has been on the rise (11:06)Other uses of synthetic data besides AI model training (17:25)Connect with Zachi Mann:LinkedInConnect with Spencer Acain:LinkedIn See acast.com/privacy for privacy and opt-out information.