AI Spectrum

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)