What agentic AI means for the design process

AI is not a one size fits all solution for approaching industrial problems, rather, it’s important to tailor different models to different applications to ensure the best results no matter the use case. Equally so, the chips that run these AI models should not be one size fits all either, with highly customized chips offering far better performance and efficiency when it comes to accelerating AI in everything from a datacenter to a smart camera. In this episode, host Spencer Acain is joined by Russell Klein, program director at Siemens EDA and a member of the Catapult HLS team, examines the needs of AI hardware through highly customized chip designs and how, through innovative applications, AI itself can increase the flexibility of the chip design process in novel ways. In this episode you will learn: ·         How AI is increasing the flexibility of the chip design process (1:26) ·         The importance of custom chips for AI use cases (11:57)

If the only constant is change, then AI represents the next big change for many tools and industries. High-level synthesis, one of the key tools in the semiconductor design process, is set to be one of the tools that receives a big upgrade from AI. Currently, HLS processes rely heavily on manual adjustments and hard-coded heuristics yet, with integrated intelligence, a new approach to chip design begins to emerge. In this episode, host Spencer Acain is joined by Russell Klein, program director at Siemens EDA and a member of the Catapult HLS team, explores the ways AI can bring even greater automation and intelligence to the chip design and manufacturing process. In this episode you will learn: ·       How AI enhances heuristics (0:30) ·       How AI will change the chip design process (2:41)

Chip design is one of the most complex and challenging tasks in the world, requiring specialized tools and knowledge far beyond what is needed in other fields. High-level synthesis (HLS) is a key tool to help address complexity and achieve efficient, optimized designs which are key in both modern smart products and cutting-edge AI. HLS and AI have strong synergies in improving ease of use, speed and efficiency. In this episode, host Spencer Acain is joined by Russell Klein, program director at Siemens EDA and a member of the Catapult HLS team to examine what HLS is and how it intersects with AI. Russ explains how AI benefits from HLS-designed chips and, in turn, how AI can help make a complex tool like Catapult more powerful. In this episode you will learn: ·         What is high-level synthesis? (0:30) ·         Improving efficiency with AI and HLS (2:38) ·         The potential of AI-assisted chip design (5:35)

New technology can offer a lot of promise for improving on long-standing techniques or developing innovative approaches to different challenges but, when it comes to adopting these new technologies into complex industries, there are always challenges to overcome. With advancements as complex as artificial intelligence and agentic AI, unlocking their full potential across the design and manufacturing process will take time, yet in so doing, achieve new heights of what is possible. In this episode, host Spencer Acain is joined Shirish More, AI Program Product Manager at Siemens and Michael Taesch, Senior Director of Product Management for NX Manufacturing to look at what it takes to deploy AI in industry, the challenges both technical and personal that must be overcome and why making the effort will be important in the years to come. In this episode you will learn: ·       What it takes to bring generative AI to industry (0:51) ·       The impact of AI industry going forward (7:31)

As it continues to develop, artificial intelligence is starting to be applied across many different sectors of industry with equally many different new technologies used to support that. Agentic AI represents one of the latest ways AI can be applied to more complex tasks including complex design and manufacturing processes that existing AI isn’t well suited for. In this episode, host Spencer Acain is joined Shirish More, AI Program Product Manager at Siemens and Michael Taesch, Senior Director of Product Management for NX Manufacturing explore the future of agentic and generative AI in design and manufacturing applications, what that will mean for the design process, and the role of AI as an assistant going forward. In this episode you will learn: ·       The future role of AI in design and manufacturing (0:58) ·       What is agentic AI? (7:51) ·       The transition from AI to coworker (12:23)

Bringing AI into industry isn’t something that can happen all at once, rather, something that will happen gradually by applying AI to individual areas where it can have the most impact. With that said, as these foundations continue to grow, more complex, overarching AI applications will begin to find their way into industry as well, offering greater flexibility and possibility then traditional systems can. In this episode, host Spencer Acain is joined by Dr. James Loach, head of research at Senseye Predictive Maintenance to look at the applications of LLMs and other, similar AI technologies to the vast store of information available across a digital enterprise, and what that means for the future of design and manufacturing. In this episode you will learn: ·       What comes after the time series foundation model? (0:35) ·       Expanding AI to enterprise data (3:26) ·       The broader role of AI in industry (9:50)

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)