Interpreting different types of information is a task humans are inherently good at with just a little guidance and, from there, conclusions can be drawn and connections made. Artificial intelligence by contrast requires much more training but is capable of analyzing information and building connections in wholly different ways than humans, allowing for a novel perspective on key data. In this episode, host Spencer Acain is joined by Dr. James Loach, head of research at Senseye Predictive Maintenance to explore the ways AI can analyze and interpret industrial data, the similarities between text generating LLMs and Senseye’s own time series foundation models. James also delves into what it took to make the time series foundation model a reality. In this episode you will learn: ·       The similarities between text and time series data (00:36) ·       Challenges of building a time series foundation model (05:50)

Artificial intelligence is rapidly becoming a core technology for both consumers and businesses but bringing AI into the design process or onto the shop floor presents a unique set of challenges. With a wide variety of tasks and data types, creating AI models to handle industrial tasks is far more difficult than creating simple chat interfaces, which is where foundation models come in. Host Spencer Acain is joined by Dr. James Loach, head of research at Senseye Predictive Maintenance to learn more about what foundation models are and how they can help address some of the challenges of bringing AI to industry. One example of this being Senseye’s own time series foundation model. In this episode you will learn: ·       What is a foundation model? (0:30) ·       Applications of a time series foundation model (6:00)

Over time what was once thought impossible slowly becomes possible. For all its flaws, the artificial intelligence of today would be more at home on the holodeck than the board room even 20 years ago, yet today AI is reshaping how people do their jobs in every sector.  For every great leap in technology, there are many smaller building blocks that pave the way and for AI in industry, digital transformation is one such building block, a key step in merging existing tools and data with the power of AI. In the final episode of this special miniseries, host Spencer Acain is joined by Todd Tuthill, Vice President for Aerospace and Defense and Marine Industry at Siemens, Dr. Justin Hodges, Senior AI/ML Technical Specialist at Siemens as well as Fatma Kocer-Poyraz, Vice President of Engineering Data Science at Altair to look both forward and backward at how far we’ve come with AI, simulation and digital transformation, and how far we still have to go. In this episode you will learn: ·       The importance of AI in the digital transformation of industry (0:50) ·       How science fiction becomes science fact (7:49)

Generative AI is proving to be a powerful force multiplier across many industries, allowing a single user to do more in less time and even highly complex tasks, like product design, are reaping generative AI-driven benefits. However, as powerful as these AI tools are, they must be carefully applied in conjunction with not in place of existing tools like simulation. Only together can AI and simulation achieve a better result than either could alone. In this special miniseries, host Spencer Acain is joined by Todd Tuthill, Vice President for Aerospace and Defense and Marine Industry at Siemens, Dr. Justin Hodges, Senior AI/ML Technical Specialist at Siemens as well as Fatma Kocer-Poyraz, Vice President of Engineering Data Science at Altair to examine it takes to develop generative AI fit for industry and how best to combine the two fields. In this episode you will learn: ·       Where generative AI fits in industry (0:43) ·       What is an industrial foundation model? (9:27) ·       Balancing AI-generated and simulated results (17:49)

Simulation has been a cornerstone of the design process for many years but despite how advanced modern simulation tools have become, there are always ways to continue advancing. Artificial intelligence and machine learning represent one such path to improvement, working in tandem with existing simulation techniques to accelerate design space exploration and beyond. In this special miniseries, host Spencer Acain is joined by Todd Tuthill, Vice President for Aerospace and Defense and Marine Industry at Siemens, Dr. Justin Hodges, Senior AI/ML Technical Specialist at Siemens as well as Fatma Kocer-Poyraz, Vice President of Engineering Data Science at Altair to explore the ways AI/ML will complement traditional simulation and enhance design space exploration going forward. In this episode you will learn: ·       What are the synergies between AI and simulation? (3:12) ·       The power ML surrogates for design space exploration (7:17) ·       Value of AI and simulation (11:35) ·       Understanding synthetic data (14:36)

Merging AI with operational technology (OT) is no simple task, between concerns about robustness and reliability as well as data privacy, there are many challenges to overcome. With that said, the potential benefits make the endeavor worth the effort. Rather than bringing AI into every aspect of manufacturing right away, the key for long-term success will be adopting it gradually through small tasks with immediate benefit that also support broader, long-term goals. In this episode, host Spencer Acain is joined by Ralf Wagner, Senior Vice President of data-driven manufacturing at Siemens, to look at the steps it will take to bring AI into the manufacturing and operations world, the key insights he and his team have gained along the way and finally, what the future will hold for AI in industry. In the episode you will learn: ·       Challenges of bringing AI into operations (00:57) ·       The future of AI in manufacturing (7:36)

Artificial intelligence and data go hand in hand together, whether that’s as data used to train AI models or as AI models used to analyze and retrieve data. In the industrial world, there’s a fine balance between leveraging data to fine-tune shop floor AI systems meaning data intelligence is an equally valuable asset as well. Similarly, AI itself can provide a form of data intelligence through the lens of an Industrial Copilot capable of aggregating vast quantities of data into easy to access and understand formats. Bringing these elements together will be vital in realizing the future of data-driven manufacturing. In this episode, host Spencer Acain is joined once more by Ralf Wagner, Senior Vice President of data-driven manufacturing at Siemens as he examines the applications of pretrained AI solutions compared to fine-tuning them for specific deployments. Additionally, he looks at the ways the Industrial Copilot can be applied to the data-driven manufacturing process. In the episode you will learn: ·         Out-of-the-box vs. fine-tuned models (0:42) ·         Applications of the Industrial Copilot (5:02)

AI will drive the future of data-driven manufacturing with tools like Siemens Insights Hub already adopting AI in key areas today. For the manufacturing industry, leveraging data and taking advantage of AI means leveraging out of the box solutions and robust, easy to use models that don’t require teams of data scientists. Leveraging data-driven manufacturing will be vital for companies to traditionally siloed domains and unlock broad-ranging optimizations. In this episode, host Spencer Acain is joined once again by Ralf Wagner, Senior Vice President of data-driven manufacturing at Siemens, to explore core applications of AI within Siemens Insights Hub, with everything ranging from out of the box solutions to powerful customizations for expert users. Beyond that, Ralf examines the importance of data-driven manufacturing going forward, and why AI will play a key role in that. In the episode you will learn: ·         What are the 4 applications of AI in Insights Hub? (00:28) ·         Importance of data-driven manufacturing (11:50)

Data is playing an increasingly important role in the manufacturing process but leveraging it to its fullest potential and intelligently applying it to optimize production process and systems can present many challenges. AI provides a path to leveraging production and IIoT data to support continuous optimization and achieve insights faster than traditional methods allow. In this episode, host Spencer Acain is joined by Ralf Wagner, Senior Vice President of data driven manufacturing at Siemens, to discuss the importance of tools like Siemens Insights Hub for smart manufacturing. Additionally, he will examine the key role AI is playing in these types of tools and why it will be crucial in achieving the next step in smart manufacturing. In the episode you will learn: ·         What is Insights Hub? (2:11) ·         Major AI applications in Insights Hub (10:11)

Artificial intelligence is already finding a place across many different areas of the design and manufacturing process but its benefits aren’t limited to supporting individual, siloed, applications. As both AI technology and the digitalization of the complete product design process continue to develop, AI will become a key tool that spans across the entire breadth of industry, reshaping the entire process from end to end.   In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, as they look to the future of what AI will offer the product design and manufacturing process. They highlight key AI trends and they impact they are already having at every stage of the design process, while also examining the impact those trends will have in the future. In this episode you will learn: ·         The impact of AI across the breadth of product design (1:25) ·         The future of AI in industry (7:18)

Artificial intelligence is having a major impact on the way products are designed and manufactured. Applying AI to the manufacturing industry can help bring a new layer of speed and adaptability to an industry that has traditionally been slow to adopt new trends. AI offers the ability to understand, package, and transport information between systems and users in a more efficient and intuitive way than ever before, enabling new approaches and innovations across the breadth of a factories operations. In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, to examine the ways AI is being applied to the manufacturing process. They cover topics focused on applying AI/ML to critical data within factories, encompassing both usage and analysis. In this episode you will learn: ·        Applications of AI in manufacturing (1:17) ·        How AI is accelerating operations (5:01) ·        Packaging data with ML models (7:46)

Advanced software methods, like simulation and the digital twin, are at the core of modern product design, enabling new designs to be tested and validated quickly and efficiently based on real-world data without the need for expensive prototypes. Now, thanks to the latest advances in AI, these key technologies can be taken a step further, allowing for even greater efficiency and new ways of tackling complex problems. In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, to explore the applications of AI in simulation and design, including applying AI to unify different elements of the digital twin and deepening the connection between the virtual and physical worlds. In this episode you will learn: ·        The benefits of moving to smaller models (0:37) ·        How reduced order models help bring together digital twins (3:16) ·        AI enables DevOps for hardware (7:46)

With the continuing digitalization of industry, the product design and manufacturing process is becoming more connected from end to end. Taking advantage of that connection and digitalization, artificial intelligence is starting to take a bigger and bigger role across every stage of the design and manufacturing process. Bringing AI into the design process helps organizations achieve both long- and short-term goals while simultaneously accelerating traditionally slow processes, help enable new, innovative approaches to historic problems. In this episode host Spencer Acain is joined by guests Boris Scharinger, Senior Innovation Manager and Technology Strategist for Siemens Digital Industries, and Dr. Justin Hodges, Senior AI/ML Technical Specialist in Product Management for Siemens Digital Industries Software, to discuss the applications of AI in the early stages of the design process. They discuss key topics such as the application of AI as a decision support system, as well as ways AI is helping address important concerns such as sustainability. In this episode you will learn: ·        What are the applications of AI in the early stages of product design? (4:06) ·        How AI is helping address sustainability concerns (6:27) ·        How AI enables faster decision making (9:15)

PLM systems are at the heart of modern, digitally integrated manufacturing and design companies, helping to support the digitalization of industry and the advancement of next-generation manufacturing. However, with as complex as these systems are and with the vast quantities of data available within them, leveraging a PLM system to its fullest potential isn’t always a simple task. In this episode, host Spencer Acain is joined by Charles Aldave, Product Marketing Manager for Teamcenter, to discuss the ways AI is impacting PLM systems, both as a means for directly interfacing with users and as a way to silently speed things up behind the scenes. In this episode you will learn: ·         What is Teamcenter? (0:43) ·         Creating hallucination free generative AI (2:37) ·         How Teamcenter seamlessly integrates AI (6:00)

Microchips are getting smaller, denser and more complex with each passing year not only incurring increased costs, but greater manufacturing challenges as well. To help drive the continued advancement of semiconductor technology, the design and testing of these new chips must be ready to accommodate AI and ML from the ground up. In this podcast, host Spencer Acain is joined by Ron Press, Senior Director of Technology Enablement at Siemens Digital Industries, looks to the future of AI and ML in the chip design and verification process. Ron explores the needs for cutting edge technology in a field as complex as IC production, as well as the challenges of adopting that same technology into a multi-billion-dollar industry. In this episode you will learn: ·         What is analytical AI? (0:37) ·         Challenges of bringing AI into IC design and test (4:48) ·         The need for cutting edge technology in leading processes (6:36)

Microchips are an integral part of modern society, controlling devices big and small, simple and complex. Designing these chips isn’t a simple process by any means but equally so, fabricating and verifying completed parts is not only incredibly complex, but a vital step in the manufacturing process. Cutting edge microchips are so expensive to manufacture that improving yields by even 1% can represent multi-million dollar improvements in revenue. In this podcast, host Spencer Acain is joined by Ron Press, Senior Director of Technology Enablement at Siemens Digital Industries to explore the ways he and his team are applying AI and ML in Tessent, a key tool in the chip verification and design process. Additionally, Ron explains the importance of testing and why the process takes so well to AI/ML. In this episode you will learn: ·         What is Tessent? (1:04) ·         Applications of AI/ML in Tessent (5:58) ·         What makes IC verification a good fit for machine learning? (8:56)

AI is a constantly changing field, sometimes with a staggering pace of innovation so when considering the development and deployment of AI solutions it’s important to also understand where the technology will go in the future. Adapting to the challenges of today while preparing for the advancements of tomorrow must be key considerations when developing any AI technology, especially broad-reaching ones like the Industrial Copilot. In this episode, join host Spencer Acain and guests Michi Lebacher and Alessia Bortolotti as they examine the challenges of bringing an ambitions project like the Industrial Copilot to life, how that project will evolve in the future, and where AI is leading the industry as a whole. In this episode you will learn: The future of the Industrial Copilot (0:31) What it takes to bring AI to industry (5:20)

The Industrial Copilot is already beginning to prove its value across industries but ensuring such a powerful AI tool is industrial grade and ready to deploy not in months or years but in days, isn’t without its challenges. Addressing these challenges requires a smarter approach to data and training, as well as extensive cooperation both between new and existing software tools and with partners seeking to deploy these AI solutions. In this episode, host Spencer Acain is joined by Michi Lebacher and Alessia Bortolotti to examine the approaches to data and deployments, trade-offs and customer benefits of the Industrial Copilot. In this episode you will learn: How the Industrial Copilot integrates across the Siemens ecosystem (0:28) Training AI across different disciplines (9:20) RAG vs. fine tuning for industrial grade AI (13:55)

Chatbots and digital assistants aren’t anything new, but their abilities and perceived intelligence were often extremely limited, giving them no place in the complex world of industrial design and manufacturing. Now, thanks to advances in industrial grade generative AI, that’s all beginning to change. The Industrial Copilot is the first step in that change, offering human-like assistance and intelligence to users at every level of the industrial value chain. In this episode, host Spencer Acain is joined by Michi Lebacher and Alessia Bortolotti to discuss the applications of AI in the Industrial Copilot, a generative AI-based tool that assists users across a broad range of tasks and with intuitive natural language abilities. In this episode you will learn: What is the Industrial Copilot? (2:48) What are the key areas the Industrial Copilot is applying AI? (6:08

Implementing AI into a complex and often mission-critical application is rarely an easy task even though it is often highly worthwhile. Even as AI experts work to bring AI into the applications where it can provide the greatest benefits, their efforts also have a democratizing effect on both the tools its being added to and the AI models themselves. This ensures that everyone will have full access to the tools they need to capitalize on their own domain knowledge without needing to become an expert in the tool itself. Join host Spencer Acain in a conversation with Subba Rao, Director of Manufacturing Industries Cloud for Mendix, a part of Siemens Xcelerator as he discusses the challenges, benefits and future of AI within Mendix and the industry at large. In the episodes you will learn: ·         Challenges of bringing AI to Mendix (0:00) ·         Mendix democratizes industrial AI (4:16) ·         What the future holds (8:08)