AI Spectrum

AI Spectrum

By Siemens Digital Industry SoftwareScienceTechnology
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AI Spectrum episodes

  • The importance of flexibility in AI chip desgin

    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)

    19 min
  • Developing an AI enhanced chip design process

    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)

    11 min
  • Understanding AI-assisted Chip Design

    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)

    16 min
  • Driving the adoption of generative AI in industry

    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)

    12 min
  • What agentic AI means for the design process

    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)

    17 min
  • Building an AI foundation for a smarter digital enterprise

    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)

    14 min
  • Understanding information with AI

    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)

    13 min
  • Building a time series foundation model

    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)

    14 min
  • Understanding the intersection of AI and simulation – Part 3

    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)

    13 min
  • Understanding the intersection of AI and simulation – Part 2

    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)

    24 min

About AI Spectrum

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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…