Guest: Nico Kelling, Head of Buisness Center of Excellence for Artificial Intelligence, Infineon 
Moderator:  Thomas Reinhardt, Director Corporate Campaigns ＆ Customer Communication, Infineon
Date of publication: 15 June 2023

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“So think about simple voice assistants, we all have smart speakers around us, think about music streaming, voice translation, already AI-supported news – now this is something that everybody is talking about, since ChatGPT has been published; latest since then it is clear that everybody is taking advantage of this technology already.”

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Moderator:

Hi everyone. Welcome to a new episode of the #MakeIoTwork podcast. My name is Thomas Reinhardt, I am your host, and I am excited to have this great opportunity sharing this podcast with all of you. 

Artificial intelligence is once again a hot topic, especially since the launch of latest versions of applications like ChatGPT and midjourney. It is one of the hottest and most trending technologies of digitalization. But, where can AI be applied, especially in the business environment? That is what I'm going to talk about today with my guest Nico Kelling. Nico is heading Infineon’s Center of Excellence for Artificial Intelligence and in this role focusing on connecting these kinds of technological innovations with our business. Great to have you here, Nico.

Guest:

The pleasure is mine. Thanks for inviting me.

Moderator: 

Artificial Intelligence has already found its place into our everyday lives – and mostly, it goes unnoticed in many variations and applications. To get us started, can you give us a few examples where we can find AI?

Guest:

From a matter-of-fact point of view, we already encounter forms of AI in our everyday lives - and often without even noticing or giving it much thought. It helps us with simple tasks, gives us tips and recommendations, and makes our lives easier and more convenient in many areas. So think about simple voice assistants, we all have smart speakers around us, think about music streaming, voice translation, already AI-supported news, and last but not least – now this is something that everybody is talking about – since ChatGPT has been published, latest since then it is clear that everybody is taking advantage of this technology already.

Moderator:

So, Artificial Intelligence is not only supposed to help and support in the private environment. There are also numerous use cases in the industrial environment, which promise huge efficiency gains. That's why the topic is playing a major role in all industry sectors. Not without reason, I suppose. What are the general advantages that are expected from applying AI in the industrial sector?

Guest:

Very true. The real value of AI is indeed in industrial areas and according to a McKinsey study, AI alone can increase global gross domestic product by 1.2 percentage points per year by 2030. And just to translate that into figures: This additional contribution to value creation could be as much as 13 trillion US dollars. AI systems in industry are the same technologies you use in daily life, but applied to industrial problems and of course to satisfy additional requirements. The same kind of AI that makes our phone conversations clearer can also pay attention to noise on the production floor, for instance. The benefits can really be immense. They range from increasing productivity to improving efficiency and enhancing quality, by really taking more informed decisions and the automation of certain processes. This naturally has a positive effect on sales, competitiveness and also on sustainability what is really a very major point.

Moderator:

Let’s take a closer look at the semiconductor industry as an example. What advantages can market participants expect here?

Guest:

Again referring to the McKinsey study and breaking this down specifically to the semiconductor industry, the projection is that within the midterm – a few years from now - there is a potential about almost 100 billion euros that could result from the use of AI. Of course, there are a wide variety of use cases, they go all across the entire processes that we have, mostly in manufacturing, which is the largest part of that.

Manufacturing is where we have the largest absolute invest but also can harvest a lot. Here, productivity can be increased by automating processes. The number one topic is here the equipment process monitoring. So, equipment can be used more efficiently, for example, by using predictive maintenance. But this is just one flavor of taking advantage of these signals for equipment health. Once we have this equipment health monitoring this gives us also a significant time advantage in the detecting deviations possibility to interact and prevent from perhaps samples being produced in the first place but also to act quickly.

An additional area of course - and that is equally important and significant in total effects – is the area of research and development. In our development processes we have quite a number of experiment-based and iterative approaches including simulations and testing. And if we use automation of data generation using AI to accelerate and match these simulations and predict simulation results we are able to produce vast amounts of reference data that can help to achieve optimization and completely different levels that have not been thinkable before. Also, the AI here really helps us to focus our attention and efforts on the areas that matter rather than wasting it in areas that are known bad. So the effect of AI in this field is really time-to-market, bringing products to market faster, taking better and more data-informed decisions for the product design and in the end ultimately better product-cost-performance that match to the market requirements.

Also, in the digital go to market- area there is a lot of potential with AI. Thanks to a better understanding of customers and a better assessment of market developments, we know at an early stage what the customer needs next. This allows us to proactively send suitable offers complementing our customers system design - a significant service for our customers.

Moderator:

I assume that as Infineon we are also keen to leverage all these potentials, right?

Guest:

Absolutely. We have come a long way already. We just concluded our 2-days Annual Corporate AI Days where many of our AI experts showed their AI projects and exchanged experiences. Indeed, there have been more than 100 expert contributions to this conference sharing about the progress that has been made in all these various areas, applications, but also on how to ensure robustness and reliability.

As operators of our own smart factories, we are already implementing this today and will continue to work on that. A lot will happen. This not only serves us, but is also beneficial for our customers. So they receive better quality and higher dependability.

If we look at the R&D and in product applications, customers will also benefit from a minimized development effort when using our products. We can for instance provide AI-supported development tools. This way we can make customers more successful by reducing their time-to-market.

Another field is, when we combine AI with smart sensor technology. AI has a lot of potential to bring benefit to an application level. Think about dealing with enhancing signal quality to the application. Also, an AI allows to extract information that are not immediately represented in the signal itself. Think about certain gas content that can be extracted from the information. Or we can even customize sensors to the certain customer need e.g. in automation systems and vehicles.

Moderator:

Okay, so we as Infineon can see numerous benefits from the application of AI in our own processes, both for ourselves and for our customers. But are there also AI applications or products that we develop ourselves or in whose development we are at least significantly involved with our solutions?

Guest:

Well, that’s for sure. We classify three different types of solutions here.

Firstly: Products can be enhanced by using AI. They happen to include some sort of AI, like the example of improved sensors for special solutions.

Secondly: We enable our customers by providing an environment to easily taking advantage of the technology.

And thirdly, we can also design new services that happen to be based on AI. So, we can offer our customers a comprehensive range of services because we stay in touch with the product. This enables us to provide predictive lifetime services for example.

Moderator:

Recently, Infineon has announced the acquisition of Imagimob. How does this fit with the examples just gave?

Guest:

I think that is a perfect match to our strategy. We want to make our customers successful on their journey and allow them to differentiate in their specific markets. At the end our customers experience our products through the ecosystem that we provide. That is their view on our products. And therefor it is of upmost importance to have a good ecosystem, a good tool-chain that allows them to get simplified access to development processes to get products implemented quickly. That is exactly the role of the Imagimob tool-chain that we have acquired and that have become part of the Infineon universe here. So they have a very strong background and knowledge in productizing AI based algorithms in real applications and they have converted this knowledge and experience in a tool-chain that really enables what I talked about: Developing robust solutions, targeting production use of our customers.

Moderator:

Despite all the euphoria, is there anything we should watch out for? If one reads about the topic in the media, it quickly becomes clear that there are not only a lot of advantages, but also prejudices. How do you see that?

Guest:

I think you are referring to the responsible use of AI and the possible trustworthiness of AI systems. And for sure this is a public debate latest since the start of ChatGBT. But also this is a fundamental requirement for us in business terms to scale AI application.

AI should always support humans and expand their capabilities instead of limiting them. AI should not replace and observe humans but should serve us and help us to take better decisions. For example, in customer service, employees are supported in routine tasks in the back office by software robots that copy customer data or send customer information automatically. This relieves the workload on advisors and gives them more time for more complex inquiries in personal customer meetings or to focus on the task itself.

After all, humans with their experience and empathy are still important. They will not be replaced. We need them. Responsible use of AI is of utmost importance to us and the benefit for humans should be at the forefront of all our developments. We have already agreed on key principles for the responsible use of AI. The transparency of use, and save and bias-free use of these technologies is of utmost priority. If we all agree on this, then we can use the great potential that AI still offers for us individually, for us as a company in business context and last but not least for the society overall.

Moderator:

Thank you very much, Nico, for these exciting insights. This brings us to the end of this episode.
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