AI Spectrum

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 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:

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 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)

Going forward, AI will be an important part of many

industrial processes, from data analytics to development to manufacturing, there

are many places where AI could step in to boost productivity. However, it is

equally important to make sure that AI is suitable for the roles it takes –

that of an assistant, not a replacement for human expertise.

Join host Spencer Acain along with Subba Rao, Director of

Manufacturing Industries Cloud for Mendix, a part of Siemens Xcelerator as he examines

the application of AI within Mendix, their limitations, and why they chose the

AI integration path they did.

In the episodes you will learn:

·        

AI augmented vs. AI assisted (0:48)

·        

Applications of AI in industry (8:02)

When it comes to developing industrial software and

workflows it’s not just expert domain knowledge that is a limiting factor, but

also the ability to transfer that expertise into the required software and

programming languages. Low- and no-code solutions combat this by helping anyone

with an idea translate it, with little to no coding knowledge, into a

full-fledged application and generative AI is at the heart of this process.

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 ways Mendix leverages AI in low-code application development

and how it is supporting the integration of AI withing industrial apps.

In the episodes you will learn:

·        

What is Mendix? (1:19)

·        

Key applications of AI within Mendix (4:27)

·        

How AI helps build AI apps (7:11)

When designing a product, there are countless parameters

that must be considered and balanced to arrive at a final, optimal result. In a

traditional design cycle, this is a highly manual process that seeks to reduce

the number of variables as much as possible to simplify the process. Now thanks

to advances in AI, it’s possible to not only handle a greater number of

variables but extract additional information from each one – allowing for

further design refinement.

In this episode, host Spencer Acain is joined once again by

Dr. Gabriel Amine-Eddine, Technical Product Manager for the HEEDS Design

Exploration Team, to examine the ways AI can be used to aid in design space

exploration and what that will mean for the future.

In this episode you will learn:

·        

Using AI to handle high dimensionality models

(1:09)

·        

Reuse of AI models (9:37)

·        

How AI will change the design process (12:24)

Bringing AI into the fold isn’t always easy. Sometimes, even

knowing when and where it makes sense to apply it can prove challenging and

once potential applications are identified, building trust in the model is also

a critical factor. These are common challenges faced by AI applications in

every industry and while the solutions each one reaches will be unique, they

all share some commonalities.

In this episode, host Spencer Acain is joined once again by

Dr. Gabriel Amine-Eddine, Technical Product Manager for the HEEDS Design

Exploration Team, to continue discussing the creation of HEEDS AI Boost and how

such a complex tool can find its place in industry.

In this episode you will learn:

·        

What prompted the creation of HEEDS AI Simulation

Predictor? (0:43)

·        

How uncertainty-aware AI can build trust (6:24)