Industrial vs Consumer AI: Exploring the Difference

But kind of in a broader sense, of course, everyone is talking AI right now.

It's not just us, it's not just Siemens, it's not just Rockwell or anything, but you also have the big guys like NVIDIA and AWS, Microsoft.

How is Siemens set apart from all these large AI-focused companies as well?

Oh, very, very important question because when we look at AI today, we see the fact that it's touching everybody all the way down from kids in elementary school to their grandparents and everybody in between.

And it's very important and critical to understand for our listeners here in terms of what is the difference in what we see with these technologies different types of AI offerings.

So let me start by saying this is the differences in terms of AI infrastructural services versus industrial domain AI and AI that is applicable to engineering and manufacturing.

So what do I mean by this? So when you look at the companies, like the ones that you mentioned, Spencer, you know, AWS, Microsoft, NVIDIA, focus a lot on what we call as infrastructural services.

Some may call them as foundational or platform services, but the key is whatever AI capabilities that these players and companies are providing are core for the broad set of industries to build their offerings And the services that they provide are agnostic of a particular industry.

So let's take, for example, NVIDIA.

Everybody knows the name NVIDIA in the AI world now.

They provide powerful GPUs and related accelerator services for graphics, right? AWS and Microsoft, they're providing services such as large language models or LLMs.

RAG or retrieval augmented generation, guardrails on how AI would perform, foundational pieces about how agents can be built, so on and so forth.

Now, these services can be used by any organization, any company, as a framework for building their specific specialized AI offerings.

And the other part that these great organizations do is they provide these services at scale, which is why they are also sometimes called as hyperscalers.

So in a nutshell, companies like AWS, Microsoft, NVIDIA, and their peers are providing infrastructural AI services at scale that can be used by several organizations, several companies, several businesses across any industry to build their specific AI capabilities.

Now, what is it that Siemens does and that is different? So at Siemens, we deliver industrial software.

That's a big part of our DNA and our bread and butter.

We provide these industrial software across multiple domains.

such as design engineering manufacturing processes simulation operations and so on so forth what our customers do is they use these softwares to build their products such as cars planes satellites phones machines factories consumer goods we have a very broad set of industries that we support where our customers come from.

And our software is very powerful that allows the users to do some very complex engineering and manufacturing and operations work.

Now, this is where we start bringing in AI for our customers and their users.

What we at Siemens are doing is that we are infusing AI in these industrial software systems that we offer across all the domains that I mentioned about engineering, manufacturing, operation simulations.

And what we are doing here is by infusing it, we make it highly efficient for our customers and their users.

Not only for them, but even our own software, we make it highly efficient by infusing AI and With this, our users are able to perform their tasks at breakneck speed than what they were before us infusing AI, and they're able to get this competitive advantage over there.

Now, the interesting part is the services or capabilities that Siemens provides versus what AWS, Microsoft, and NVIDIA and the hyperscalers provide Although they would seem and sound like different, they are actually connected.