so India has a very visionary goal of becoming a vibrant nation. What do you think about India in general? Are we on the right track? So India has tremendous potential as you know, we have so many young energetic people. I was very shocked to say that so

many of these solutions were actually being built by Indian engineers. Now my question to you is that how does a tech company like Siemens approach these complex solutions because it is not an easy problem to solve. Actually it's not that hard. So I'm regularly noticing the

word industrial AI. Could you tell everyone what exactly is industrial AI and what are the opportunities? The number one difference is that this is Dr. Peter Kot, Chief Technology and Strategy Officer at Siemens AG. And in today's interview at The Cutting Edge Show, Dr. P Kot will share

his valuable insights on the future of industrial AI and the next big opportunities for Indian businesses. Make sure you take notes from this episode because STP students will get a certificate of achievement. Details are in the description. There's a lot to learn from Dr. Peter, so without further ado

let's get [Music] started. Hi Peter, welcome to India. Thank you. Thank you for having me. So before getting into the questions, I would like to tell everyone that Peter and I are in Mumbai for a very special event called Siemens Transform Innovation Day 2024.

Would you like to tell everyone what exactly is this event about? Yeah, this event is about how we can help the Indian economy to achieve its goals with regards to the growth of 7.5% on GDP and how to build a manufacturing

base increasing the share from 15% to 25% and as you know at Siemens we provide all the technology to make sustainable infrastructure to build state-of-the-art digital native factories so very very excited about discussing with customers of what it

takes to get to that next level I mean I feel very lucky that you've invited me for this because just before this session I had an opportunity to see everything that you've been building so far but India as a country has so many varied businesses new AG startups you

know MSMEs and every company every business has its own unique challenge so as a tech company how is Siemens approaching these unique challenges yes we uh first off uh we focus on two different things number one is on larger companies where we obviously work very

much hand in hand and in a direct sales motion but then also with regards to the MSMEs that you mentioned India has 60 million small to medium-sized Enterprises we need to find a good way of how to interact with them that's why we launched two years ago at the India

Day in India the Siemens accelerator which is a curated portfolio that connects very easily between hardware and software that brings in an ecosystem of many different partners on the marketplace that everybody can go to and find the elements that they they like to see now you're right that every

business business in India has somewhat a different need they produce different things uh they have a different setup they have different tools methods uh knowledge and all of that sort however what we find is there are use cases that are there over and over and over again let me give you three um one is uh the

machines um it's about productive maintenance and um and making sure that the machines are having their uptime and irrespective if you are a producer of of contact lenses or if you produce some food and beverage uh it's always the same problem that we try to

solve so we provide the basic tools to them in order to solve uptime the second one is about energy and energy efficiency it's about sustainability and reducing your CO2 footprint so we see that use case over and over again and the last one is right now is how can we

lower the hurdle in terms of technology adoption which is really low code environments where people very flexibly can put things together because sometimes the skill level is not there where we have a low code platform which we can provide to anyone and they can switch it on and then start coding and

develop their applications so how does somebody go to this accelerator like how should we imagine this is it like a marketplace or an ecosystem of tools yes it is both actually it is um it is it is an ecosystem uh uh however that's on the

supply side so the demand side comes really on the marketplace yes so you go there um usually you are uh let's say a manufacturer of a a certain industry from a certain industry let's say again the example of food and beverage so you may you know um of course doing your search

engine you say you know what um I have an issue with regards to energy efficiency in dairy and and um and um whatever dairy production processes is required and then you you go you Google it you may or you you search it whatever search engine you use you end up on the marketplace

at Siemens you find it already for tailored to your needs for food and beverage where you find seven to eight major common use cases and challenges where then Siemens and its partners provide an easy to use application in order to make that work so I'm regularly noticing the

word industrial even in your keynote even right now the example that you give that's not a single consumer it's a proper industry and most of our viewers know about consumer AI but you are tackling problems for industrial AI could you tell everyone what exactly is

industrial AI and what are the opportunities specifically in the Indian context that we can look forward to yeah sure the um so first off um what's the difference between AI consumer AI as you picked it and uh and Industrial AI the number one difference is that if

your AI in assisting writing you an email gets the tone wrong there's a little bit of harm done but you know you you can figure it out and and correct it easily if the AI gets it wrong when I for example you produce you know um any kind of dairy or any

kind of cars or whatever that is the harm can be outright you know detrimental so therefore the level of precision that is required in the industrial world is much higher so for us industrial AI has three components it needs to be safe it needs to be reliable

and it needs to be trustworthy and that's what industrial customers usually ask you to do and that's what we provide to them so in our case in industrial AI is to give you an example is um where usually there's a lot of repetitive tasks right that you can teach the

machine in order to do it on behalf of us humans there's one particular operation that is called pick and place so if you for example in packaging you have to take many different elements and you have to assemble them and you put them into a box you wrap the box and

then you ship the box and you do this the whole day I tell you if you do that it's very it's very hard on on your mental health in that regard a machine can do this much better and so this is where we brought uh what we call a pick

AI which actually is pre-trained and it can pretty much already now the cobot can take this you know and then already sorted and to put put the bin picking and put it down there and that is fantastic because that frees up yet again our creativity as a human to solve

other problems so India has a very Visionary goal of becoming a Vishva Bharat right and to become Vishva Bharat we need to be fully developed and Tech enabled by 2047 now as the chief technology and strategy officer at Siemens AG from

your own personal experiences and observations what do you think about India in general are we on the right track and if not how do we make sure that we reach our goals yeah so India has tremendous potential as you know uh a population of 1.4 billion people that

has a demographic that's clearly in your favor because you have so many young energetic people that is clearly educated with regards to being able to communicate through the world in in plain language meaning English in that regard is is an outstanding advantage that you have as as a society and which

It's very very exciting to see and on top of that, you can build almost anything because after all, it's humans that build things. So as on your path to 2047, uh, what we already see right now happening is that the first stage is is

of course building out all the infrastructure that is required. So really thinking about the railways, thinking about the transportation, thinking about the the energy sector with regards to renewable energy, thinking about all the the buildings that that you see that are more energy efficient and such. So building an

intelligent intelligent infrastructure from the get-go is a unique opportunity in India. Then it's of course what as you build that infrastructure structure, usually it happens in parallel, you're going to attract a lot of Industry because the industry comes and says there's a lot of ports, airports,

Logistics is very simple to get things around to get it into the country, out of the country. That's then happening as as we speak. As you know, there's a lot of electronics that is being invested into, semiconductor coming in, batteries is coming in. So as that is coming, then you

build again your ecosystem around certain industries and on top of that, then you build your your final products around cars, planes, whatever alongside with a lot of digital capabilities and software, industrial software, consumer software. So all of that is happening in India and you have, as I said, everything

in your own hands because you got the population that is eager and willing to learn and and to contribute. And I was very shocked to see that so many of these Solutions were actually being built by Indian engineers in your Bangalore office, and the solutions that they're making are revolutionizing

almost three very big industries so first we have all of the big manufacturing industries then we had mobility and then we had infrastructure now when we address these three different areas there are three key factors that come into play we have sustainability we have efficiency and

then productivity now my question to you is that how does a tech company like Siemens approach these complex solutions and make sure that all of these three factors are taken care of because this is not an easy problem to solve actually it's not that hard because um it's always a question

of how innovation is being created is it a technology forward what I call or it's a customer backward approach so what do I mean by it very often we we have let's say the hammer right and then the hammer looks for the nail that actually

can solve uh and and that's one one approach that you can take what we find though is um although that that potentially scales very often it's not missing or it's missing the right use case so the much better approach is to work the other way around to come

backwards from the customer and usually that starts with specific verticals in mind yeah so food and beverage industry I can tell you right now has major sustainability challenges with regards to biodiversity and variability in the input materials so that the consumer always tastes the same and they have to

take care of it whereas in a battery manufacturer that's a very different proposition because for them it's all about scale up and how to get your gear factories up and running and getting the OE and the plant effectiveness overall really going yeah so it's a very

different problem therefore what we have at Siemens is we have vertical specific experts that sit with our customers together that understand the very problems and the key challenges and the use cases they're in and that are then able to translate and that's where the magic

happens they're able to translate that problem into we have this kind of technology this is how it could fit as an example what if we could build digital twins for food and beverage so that we actually can simulate if the input factors change thereby then I can

adjust my process parameters so it always tastes the same but I also can use the same technology in semiconductor or in batteries and say what if I build you the digital twin of that factory so you can simulate it first but then later on to very different use cases similar

technology and that's how we approach it so we always start with the customer use case in mind understanding what scales what doesn't scale and then look like into our accelerator toolbox if you like yeah so looking at all the hardware that's intelligent and all the software

that's intelligent bring it together and then jointly and very often work together with partners implement it with our customers but I'm very glad that you mention digital twins because I would like to tell everyone that I will put videos of the exact demos as well if

there's a very massive industry that has to put in a bunch of money to test their operations instead of spending your money in a physical capacity you can have your own digital twin which was absolutely mind-blowing first of all how did you even come up with this and what

are the most amazing use cases that you have seen companies try out in this digital twin sector yeah because this is my personal favorite uh the digital twins are uh fascinating indeed and it has been a journey I would say the journey started somewhere in the 1970s

and '80s it was pretty much in Aerospace and automotive and it was always about how can you create a sophisticated industrial product yeah that's uh but in the digital space so that you can test it there it was crash

testing was really the key driver behind also the emergence of CAD computer aided design what happened is we developed these CAD models so the design models but then realized as while just having having like like the shape of this class not cut it but what if I can simulate I

can simulate the heat dissipation I can simulate of how actually the computational fluid dynamics is going to behave when I shake the water in here I can do whatever kind of acoustic testing and so on so that actually it this thing which is in the real world I can take it

one by one into the digital world and it only looks the same but it behaves the same because I can run these multi physics what that's how we call it multi physics simulation and so if you like over time these these these models have become more and more sophisticated it's

all pretty much based on math in order to make them you know behave like in the real world so some of the very super exciting ones are obviously um if you go into for example Pharma and pharmaceutical testing where we now not only are able to do of course inorganic parts but

organic compounds and can see how molecules behave when you are mixing and shaking them up that's fascinating to see but also in the in the non-organic um world such as for example this HD Hyundai if you see some of these very very big ships right being

developed in the digital space which have a million parts and you look at them of how they behave with regards to uh being CO2 neutral because of ammonia propulsion it's fascinating it really is and so it's a little bit like a kid in a

candy store you can say wow do me all the cut cut-throughs so you can look into the ship you can do all the cross-sections and and so on so it's fascinating and it has really helped and changed many of the industries that we

serve the demo that I saw had this very massive machine that was sort of spoiled and they gave me that VR headset and then I was able to enter the digital twin of that factory and I was able to fix things and test if the solution

would work or not which means that moving forward if somebody adopts your digital twin they can save so much of time and money yes and it can eventually end up with new medicines being formed new innovations being formed but now my last question to you is that as a leader

when you have so many exciting things to work on every industry you touch there are like a thousand problems to solve how do you prioritize which problem to solve first so um thank God there's no central way of only one person saying this is actually what needs to develop but we

have a lot of intelligence across our company. Um, of course what we do is we look at growth verticals that have particular needs. Yeah, such as for example, data centers is one of those verticals that we see is a huge potential. As you know, in particular in

India, we we got all the cators and also the the global hyperscalers building up massive massive amount of data centers as you do so you have to do a lot of simulations. You do still have to do a lot of electrification and also linkages

to the power grid and this is where clearly we we prioritize right because we can say this is an industry that's here to stay. It's also propelled by the AI uh acceleration. So obviously there's a bigger need for data centers, so we invest more in that regard and so I can

pick you you lot of other verticals as well. However, what we also then do is as I said earlier, we translate that into technology development and some of them are just scaling horizontally regardless of the industry that they serve, like in digital twin and that's where we then realize that's

a good area to invest in and that's what we've done two weeks ago when we announced um that we will be acquiring Al which is a leader in um in simulation uh software in particular for nonlinear and for electromagnetic simulation which where elements we are not as strong

today in our portfolio, which is a perfect match because now we can build the most AI powered comprehensive digital twin in the world, helping our customers even better to become even faster and even more precise. For us, it's it's absolutely fascinating and that's

how we prioritize, but how do you see human beings interacting with so much of new tech right, because the metaverse as a concept is so new, digital twin as a concept is so new. So how do we make sure that these Indian businesses adopt these tech, you know, step by step? Um, so not every

customer, as you said, has very different needs. Some of them are further advanced, and for them, they're used to CAD drawings and simulation. For them, the lead to taking digital twins and then thinking of a digital of a metaverse is a very different conversation and a very

natural conversation then if you have somebody who is about to start up their business and they want to connect a machine in order to improve uptime and efficiency. Um, so you have to have a really measured response, but the great thing is with the accelerator portfolio

that we provide, it's like a Lego toolbox, you pick the pieces that you need in order to make this very problem, you know, go away, and and so you don't have to take the most sophisticated pieces, but you take the ones that are simple and easy to start, always driven by the

return, because if we only solve the customer problem in a very fast amount of time, then they will invest, and that's that's what the accelerator is all about. Having a scalable platform in order to help them on achieving their business goals. If there's a business owner

watching this video right now, how do they access this accelerator? Is it publicly available? Is there a website that they go to? Yeah, it is. First and foremost, um, you would most likely encounter it through two different ways. One of which is either us or our partners will approach you and

have a conversation about, you know, your problems, and at some point they may mention the accelerator and say, "We have this portfolio that can help you solve this problem." Or the other way around, um, you usually don't look for a specific accelerator, do you? Uh, you would look and

say, for example, going back to the food and beverage industry, and you would say, "Well, I have a problem with spray drying in dairy in food and beverage." So you Google it, hopefully, or you have your search engine, and hopefully, it will lead you to the accelerator Marketplace. You

get on those accelerator Marketplaces, and there you find a dedicated section which is only for food and beverage where you're going to find use cases, references, and then also about the top five to 10 uh challenges that you usually face as a dairy manufacturer. And it provides you with the proven

solutions that that you can look at. Then, next takes you to a try, and you know, a try step where you can say, "Let me try that solution." If it's digital, if it's digital or hardware, we are happy to ship it, and then you start to deploy it and

you're off and running. Very, very cool. I will make sure that I share all the links in the description. In fact, if you go to our Instagram page, you will see a highlight of everything cool that we saw. We've made sure that we cover everything exciting. But Peter, thank you so much for

taking the time. Thank you so much for pulling across such a crazy event. I know that it's a teamwork, but you being at the helm, I know how difficult it is to manage so many moving parts. And hope you keep visiting back to our country again and again and hope to see Siemens

accelerator fixing all the amazing problems towards the exit path well thank you very much for having me today thank you so much if you enjoyed learning from this episode make sure you click on subscribe and hit the Bell icon right now we regularly upload valuable

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will AI make Bharat ‘Viksit’ by 2047? Siemens AG’s CTO reveals...

Ansh Mehra

인도의 비전과 지멘스의 도전 과제에 대한 접근 방식

인도는 젊은 인구로 인해 잠재력이 큰 활기찬 국가가 되는 것을 목표로 하고 있습니다.

지멘스는 특히 산업용 AI 분야에서 복잡한 솔루션을 해결합니다.

지멘스는 두 가지 접근 방식을 사용하여 대기업과 중소기업에 집중합니다.

지멘스는 2년 전 중소기업과의 연계를 위해 액셀러레이터를 출범했습니다.

액셀러레이터는 일반적인 비즈니스 과제에 대한 솔루션을 제공하는 에코시스템이자 마켓플레이스입니다.

인도에서의 산업용 AI와 그 기회

산업용 AI는 더 높은 정밀도, 안전성, 신뢰성, 안정성을 필요로 한다는 점에서 소비자용 AI와 다릅니다.

산업용 AI는 반복적인 작업을 자동화하여 효율성을 개선하고 인간의 창의력을 자유롭게 해줍니다.

인도의 잠재력은 젊고 활기차며 교육 수준이 높은 인구에 있습니다.

인도가 2047년까지 나아갈 길에는 인프라 구축, 산업 유치, 디지털 역량 개발이 포함됩니다.

인도의 엔지니어들은 제조, 모빌리티, 인프라를 혁신하는 솔루션을 구축하고 있습니다.

복잡한 산업 문제 해결을 위한 지멘스의 접근 방식

지멘스는 특정 업종과 고유한 과제에 초점을 맞춘 고객 역방향 접근 방식을 사용하여 혁신에 임합니다.

지멘스는 디지털 트윈을 사용하여 다양한 산업 분야에서 프로세스를 시뮬레이션하고 솔루션을 최적화합니다.

디지털 트윈을 통해 기업은 가상으로 운영을 테스트하여 시간과 비용을 절약할 수 있습니다.

지멘스는 데이터 센터와 같이 요구가 높은 성장 업종의 문제를 우선적으로 해결합니다.

지멘스는 디지털 트윈과 같이 수평적으로 확장 가능한 기술에 투자합니다.

지멘스는 기술 도입에 신중한 접근 방식을 사용하여 개별 비즈니스 요구 사항에 맞는 솔루션을 제공합니다.

액셀러레이터 포트폴리오는 레고와 같은 유연한 솔루션 툴박스를 제공합니다.

액셀러레이터는 직접 방문하거나 온라인 검색을 통해 이용할 수 있습니다.

기업은 지멘스 또는 파트너와 직접 연락하거나 온라인에서 특정 문제에 대한 솔루션을 검색하여 액셀러레이터에 액세스할 수 있습니다.

will AI make Bharat ‘Viksit’ by 2047? Siemens AG’s CTO reveals...

스크립트