Mistral acquires NXAI spin-off Emmi AI / API Calls

This podcast is presented by NXAI, your partner for time series. foundation models and physical AI. Hello everybody! And welcome to a new episode of our Industrial AI Podcast.

My name is Roviba. I'm recording in the rain... and i send my greetings to Munich too. Peter Sieber good morning Robert.

on the road again you busy bee On-the-road? Yeah absolutely I am sitting here..I think Fifty kilometers from Cologne, so it's a good place to record. I'm charging my car and now i have time To discuss the latest and greatest when It comes to industrial AI with you.

Okay let's do that. why don't You start? I Have some big big news but before Do you remember what I did two-and-a-half years ago pointing at, but maybe before I make just a stupid weird mistake you tell me. I wrote an email to guy called Frank Hoeter?

I was thinking of Frank. yeah exactly! Yeah he was two and half years... He was professor in University of Freiburg And i wrote him an e-mail and said hey Mr Hoeter..

I read your paper about this stuff call TAPPFN. Sounds very interesting for me. I'm not familiar with tabular data, but maybe it's interesting for all our listeners in the industrial space. Then we record an episode.

was Frank? then We invited frank and his team. do you remember to our event AI In The Forest? Yeah It wasn't a book.

greetings to the artwork guys. three things to verna. And there he got some feedback about his idea, its approach and got real use case feedback. Our listeners there were very impressed by the presentation but Frank...

And now he sold a company to SAP! So that's the deal right? Absolutely so. I must really underline our listeners get the latest and greatest shit when it comes to industrial AI first.

So really, because I have a second example. Maybe your comment first on that? Well yeah well as you say i do recall very good and in the meantime is what you didn't see In the mean time. they then established this company.

not all of them guys And one of his right hand guys who was now part of the three people that actually started a company, but there were couple other guys. There are some students as well and it's all very interesting! I believe if we talk about what they do, tabular data is their business. That is not like a new thing.

But typically the first thing most of us in an industrial space always look at when we are on the factory floor, will always look out time series data which for example Tyrex does and would look it later as well. I may be they overlapped. you know that better than I these days believe there's overlap but i think Frank and his team really focused on tabular danger and building foundation models when it comes to tabular data. Yeah, exactly.

and then again if we look in an industrial environment for example you know I talk about a little bit later on about test data. that's what WE in the industrial environment do. exactly same as well may be stronger even in the engineering phase at the beginning or When We Do Tests And We Have For Example All This Time Series Data. That's basically what Tableau data is XY columns, right?

And the data in it and that was for me. It wasn't at least relatively new as a topic. and then they did their company on them. exactly What did they do now?

They sold it to SAP. write two SAP rights. Yeah, SAP because SAP is a Tabular Company Right Yes. So it's a fit I think absolutely amazing Huge number.

we see one billion invest not the price for the company. That's okay. Yeah, exactly here I think We talked about it privately at some point and i think you suggest that yeah? And that's Exactly The way that frank wrote it as well right?

yeah exactly there is an investment over of one billion Over a certain time in into what the guys have been doing. So yeah, amazing congratulations! Congrats you guys. and as you say stay close to us come to our Alps or any other in-between year conferences that we do And you're going to learn everything about what is happening in the future.

Exactly, and now the second topic right? So The same approach. I got introduced to Johannes Brandstetter two years ago by Sepp Hoheuter. He told me there's a guy coming from Amsterdam You know from Microsoft coming back to JK Ulenz.

he will be a professor. here at JK Ulens We will build company called NXAI. then we did an interview with Johannes. Then we invited Johannes to the Alps and with this topic AI for simulation.

There he met The Simcon guys when it comes to injection molding simulation. last week there was a huge announcement of Simcon working together With Emmy, And This Week We Got The Announcement That Emmy It's A Spinoff Of NXAI Is Acquired By Mistral. So Huge Topic Right. Congratulations to Johannes and the team.

I'm very, very happy And a little bit proud To be part of this journey A bit. So again If you want to get The first shit When it comes to industrial AI Listen to the Industrial AI podcast. We were really... Johannes was Very famous in the whole research area.

Everybody knew him But i think In an industrial sector Nobody Was so much familiar with Him. I mean, Frank he was at some point in time. He was part of Google while Johannes was in the Microsoft space and he wasn't in the weather forecasting space right? Exactly!

The big Aurora model. And do recall that as long as i've been following him... he was still every now an then reporting what people had left.. I mean he co-founded that team ,i believe And I think that's what SAP has been talking about all the time as well.

The capabilities of, uh...the models you know looking into the future. so weather air fluid. it's all about physics simulation i guess That is i guess the overlap and As You Say maybe if he came from From Weather moving Into more the industrial use Of Physics i Guess right?

He found it. So if we do the comparison then to Frank with his team, three people that's exactly what they did Three of them as well or not? I guess no. It was Seb Johannes and Albert.

They had the idea to find an xai Then they run nxai than they recognize how We need to spin off emmy then they spin off me. amy raised fifty million euros a think last year And now they got acquired by mistral. Amazing Yeah, amazing story. So well then tell me which is going to be the next one?

I don't know! Let's see do you want to bet on some companies? You're not allowed. If you're not going to be right, we are gonna have legal problems here.

Absolutely! But... You need to listen to the podcast if you want to get the hottest shit when it comes to industrialization really? Exactly Yeah exactly.

So what else do you have? We just wanna talk about things now and then..you know ..You'll listen And we will see whats gonna happen.

Let's see. I think today also from my side The news topics is about money deals but also the role of humans. so a big thing very similar i think is to what I see, that OpenAI they launched their deployment company and Tropic. there's something similar right for AI native enterprise services company.

And i must say this sounds almost like similar. not completely think. the two ones we talked about are these sound more technology buy? in this case They're not technology buys.

And that's maybe, I thought is very similar to what we learned AWS doing. You know? What they have their industrial fund and it all sounds about in this case not only building the AI, large language models are thinking of you if were going be talking about a lot of language models. In the end i don't think we always talk about assistance or whatever.

doesn't matter. build into technology that not only. okay we provide you services companies out there in the world with their technology. now they say, build companies, maybe we buy them?

That's what I assume. We're going to buy. companies were gonna buy the humans that are very capable of using the AI and we then as companies are gonna provide these services to market which i think is a very interesting development. okay it sounds little bit like they are building some AI integrators for their technology or am i'm wrong exactly?

I don't know what that means, as always for you dear listeners who depending on what you are thinking of doing, maybe today. You're exactly that in an industrial environment? Maybe you are the Industrial Integrator who has put a AI layer on top or re-invented your company and then you put AI at the bottom with all the rest of it than you are today! Exactly what OpenAI, Enantropic, AWS...

And I'm sure many others will follow want to do as well. That means that you are in the same business, so now have new competition soon or maybe get a phone call from them. one of these Exactly! Maybe somebody is getting their phone called?

What else do we got Peter? The second is price differentiation. I thought very interesting...I'm not into details about models You're much closer.

Confirm this or not. I see as an example clothes sonnet becoming nine times more expensive gpd five four eighteen times More expensive. and so whoever the person is, i don't have it here. looking at this says like The cost spread is Like sixty acts.

So what we See Is? I think the word is bifurcating so splitting into two extremes. right One hand is the commodity models. Again, I hear because i'm not using all these models that it's not to think that I do but here about deep-seek and quen.

some of them maybe you almost get for free These days on the other end may be called a frontier models becoming premium infrastructure. now In the past I've asked, we have talked about what model are we going to be using? We as humans. We as consumers each of us consumers i'm completely convinced.

you know we're gonna have our personal assistant and why not...I don't think consumer is calling it AI but doesn't matter. Personal assistance The same as business assistants. That's what they are going to be for me until I change my view and then compare it a lot, too.

buying your car. is that the right thing? Maybe you can say buy something else by a chair or but maybe did the value of what It Is Going To Be Is A Car? Or Maybe It Could Be.

And Then Today Its Very Similar. There'S A Premium Card As An Entry Level Car. You just said you are loading your electric gear, battery gas prices. So there's so many ways of looking and deciding what is your available budget?

Now I think while all different types of cars do the job of moving from A to B And that has all these differentiations my guess maybe with regards to LLMs i say personal or business assistant choosing what is going to be best for each of us personally or business, it's Does it do the task at hand? So if the consumer just wants to know, you know how the weather is going To be next week in I don't know Southern Europe because he or she's considering a private trip there. You know.

Just telling her where that's gonna Be and then go on their underwear like that. That's kind of wonderful. Going back to your harness. for example right If you're going to have a very complex engineering and in the background, You'll have the smartest LML business assistant.

And it's gonna be really expensive. It is gonna cost you a couple of hundred dollars within maybe one day. Maybe that's perfectly okay, right? So I think the comparison there are so somewhere and it's you know maybe want to rather pay two days an expensive consultant That does a job Rather than a lower rate for five days.

That is not so that what i see happening in that market now You are very close to at least the technology there. Is that is a something you see happening as well? How do you see the differentiation for our listeners in this moment, I see on the market it's like software guys only using Claude right. so entropicus must have and they're always reaching their token limits credit cards burning.

Yeah, we see that and there will be price discussions. And more common to use an entropic or to chat GPT for the consumers. And I think we will see two different, we need We would see specialized models when it comes to quen are highly individual trained models When he comes to Quen open source topics and know that BMW is using a lot of deep-seek stuff? So let's see what else do you have Peter?

i'm A bit in your hurry! Sure. Yeah, yeah I jump a jump two or three just one or two small pieces? Oh yeah i mean talking about Claude court in ninety eight percent of Claude Court is not AI.

five hundred twelve thousand lines after an hour and was perfectly happy with that because what they talk About Is They Talk About A Deterministic Harness. So they say, ninety eight percent of these five hundred twelve line a thousand lines. They looked at is deterministic and only two percent one point six percent equal AI. Now, that's a weird.

That's an amazing two to ninety eight percent. I would have thought maybe eighty-eighty but I'm perfectly happy with it if its only the two percent. The smart thing is changing world today and i am so happy with this specifically in the industrial environment. you are putting pressure on me here that we put it in this deterministic harness, because that's exactly what we need.

So I'm perfectly happy with that. perfect interesting. and your last news testator. you said something was test data?

You have oh yeah but i'm not going to do that Because they need more time for that! And then were gonna be talking to Boris. Boris Scheringer has his book coming out, right? Oh wow!

You and I are going to be talking to Boris. And it's his industrial AI from pilot-to-profit that we're gonna talk to Boris... and learn what is inside of him in the book. We will have a dinner with Boris this week i think Right?

Exactly The time when this comes up we'll let our dinner actually already With him. Yeah hopefully he got assigned copy there Exactly. Some pressure on Boris, Peter let's move to the main part testator next time because I'm in a hurry. perfectly fine.

In The Main Part Davey is waiting and maybe you remember we had discussion about AI APIs right? I think two episodes And Davey sent comment of your LinkedIn post. then we have small discussion. Do not discuss it here on LinkedIn.

Come to the podcast and tell us what I missed, And we did it! It's a very interesting episode from an industrial user perspective when it comes to AI APIs Very interesting. Thanks a lot. Greetings to Belgium.

It was pleasure Looking forward to listening. Thank you Robert. Have great time in Cologne. See ya soon Take care Bye bye.

My guest today is Davy de Meijer From Belgium. Davy Welcome To The Podcast. Thank you, Robert. Introduce yourself briefly to the listeners.

what are your doing in a moment? Yeah okay so I've been working and industrial automation space for about twenty years. So i started as an Automation Engineer And I worked with Octamium for twenty years. You may be also known because they're one of the biggest system integrators.

And, uh... The last twelve years with our team I spent in China. so i was based in Shanghai and had a local team over Chinese automation engineers some software engineers. We supported multinationals setting up green fields mostly greenfields in china.

So pharmaceuticals food and find chemicals. So traditional process industry? Yeah, yeah. And I came back to Belgium and also left Octamium two years ago to set up my own company which is called Accelere.

so the name of the company's Accelier and it targets to accelerate engineering. more specific accelerates industrial processes automation engineering. That interesting. we will talk later a bit about your company or approach.

but First of all, you'll listen to our latest episode and didn't want to let my criticizing of API stand. We exchanged messages on LinkedIn And then we decided Let's record an episode on the whole topic Maybe for all the listeners. maybe I do a little recap? I was at Hanover Mesa with many companies that spoke too.

The topic always came up. so now customers can And we have an API and the customers can do now, do AI. For me that wasn't enough for me! I don't see any business value in this only to write an API...

and then it was your take. what you think? You said APIs is a good approach for the first step or am i wrong?! Yeah, so I said my eyebrows were raised a little bit and in the end.

Actually there's two ways of looking at APIs. one is actually The API going towards the models And then the other one is the APIs Going toward industrial applications That we want to apply the AI too. So it was not entirely clear. Of course, I only was also half listening to the podcast but it wasn't entirely clear what you were talking about.

so my point is that i see there's an API and then guys are telling me now we have here a API for language model one two three four five and you can do AI with them. this was not enough from me. Do We Have A Creativity Lack In The Industrial Sector When It Comes To APIs To The Model? Okay, so for the APIs to the model I think The API's to the models are starting to represent intelligence.

So ii think you can compare it a bit like your taking electricity or an industrial plant. You need compressed air. It is becoming basic utility in essence. So you need to somewhere get this intelligence, either.

You take it from one of the main providers for man tropic from open AI or are you considered to run at yourself? Either still on a private cloud or maybe even locally with one off the open models that you need these access to the models but there's not business model for the companies. I am wrong because This will be common API At The End. Yeah so Of course if If you want To Play That Game You Need To Invest billions.

And it's not just a couple of billions, we're talking about hundreds off billions. So if you look at the investments over and tropic and an open AI You see that Chinese companies are trying to keep up. No I don't mean to build in own entropic or something But i think The Companies need To Think About. Can I Add A Value Edit Service?

Even more, is there a business model for me not only to provide an API? What's your opinion on that. Yeah okay but then maybe first we need talk about the other kind of APIs and they're all different kinds of APIs as the APIs towards the industrial applications. so what do you see now?

if look at the world outside of industry We see that the biggest part of AI being applied it going toward coding engineering. And it's relatively easy to do this because in the world outside of the industrial space everything is relatively open. So we have access to code, We have access data and for applications... we have Open APIs.

Today its very difficult to imagine applications in the software space that don't have an API thats commonly available. Now if you look at the Industrial Space It actually very very difficult get access to codes To Data and to the APIs. So that was also part of raising my eyebrows quite a bit, because in the industrial space we already have trouble applying main models... because they almost don't have grip on anything!

We need to take step back. as if you look at the software world over time software has been being built on top of software, and you know the saying people say okay software is eating the world but we still don't see this in industry. Software is still not eating industry! And that's even before we start talking about AI.

so it's very difficult to automate things in industry. if you look at industrial engineering had industrial engineering workflows they are very manual. We say we're automation engineers, automate the factories. We aim to make them autonomous but if you look at our own workflows or engineering work flows they are almost not automated and very difficult to automate.

And The main reason that is like this Is because we have no interface service To do so. So That's one of my main concerns. If I start talking about applying AI industry We don't even have basics yet. Okay Your opinion is that going this API, it's a good way to go.

To have only two provide an API doesn't matter. if you haven value added service and you can sell the APIs? That what do think they can really sell APIs? okay I think in many cases You don't even need the API.

so every look at The basic thing that running the factories. What is making sure we can automate factories? that PLC DCS systems. first of all they need to have their code accessible.

They need to move towards a more modern development workflow and multiple companies are starting to do this. so Siemens, Backoff, BNR, Codesys I believe as well is also working on something. So these teams realize that the future is there. For accessing codes you don't need an API You just need to be able to let your agent work directly on the codes.

Then for everything else, yes. You need APIs. and then if you ask what is the business model? That's also a thing that's now in discussion in the software world how do your charge for this?

classically people would say okay we charged four per user but were talking about subscription model. We're still in the industry world where most companies are trying to switch from perpetual to a subscription model. But we're already a step further in the software world where people say that agents start doing so much work. How do you measure that?

so? You will need to figure out something. That's more closer to the value of being delivered, So it is going be less seed based subscriptions and more value-based usage deliverables. And that would probably be different for every type Of company because depending on what you offer It'll be different.

What about this creativity lack in industry? Do you see or only my opinion? Yes, I think industry is a bit close ecosystem. Not looking enough outside of the bubble.

it has also been for very long time not so popular. change a bit. It's becoming a bit cooler again to join industry? Yeah, I feel it is a bubble.

people think industry needs do everything in different way while actually maybe its ten or twenty percent that we need to be doing this specific way but for the rest of eighty percent thats left We should look more at whats happening and the software industry. then main AI applications what people are doing there. so yeah i also think thats an issue. Imagine you own an automation company like Backoff or Rockwell, whatever.

What would you offer to your customers when it comes to AI? First of all I think these companies their business model will change a lot because... You probably heard also about software-defined automation. Yeah, we had an episode with the guys.

Yes but software defined automation is also a concept and it's actually starting to work on two levels And that's too income streams for the automation companies. one Is The Hardware. so the hardware is becoming commoditized So That Will Have A Big Impact On The Business Model. I think many of the bigger companies also say, look.

The hardware will become less important but you need to get through this transition. and then the second thing is also the software...the basic software layer is also going through a commoditization step which is normal. so in the software world we see that over time as certain layers becomes mature, that it becomes more a commodity and then companies they switch to higher levels of value.

So if you look at Microsoft and Amazon uh... You see? They always keep climbing the stack The stack. so the automation companies also need to start doing that And I don't have the perfect answer.

Of course i'm working on my own product but think we need to shift towards higher level values. Again. its not easy Because I also understand what position they are in. Some of them doing really cool things, but it's still early.

But you will have no choice then to switch because You can delay the commodization for some time at a certain moment and move. And i think everybody is looking Automation AI killer application or am I wrong? and nobody found it yet. You mean in the automation engineering?

Yeah, so what's happening in a software world? who is building the killer apps? you see it all open. It's all Open Agents.

you have codecs but also an open code. that pretty good. So... What does this similar thing in the software world.

You see, Siemens has made a demonstration with one of these open agents on their new Sematic AX platform And it works well. I know many people who just use regular plot codes on, on back over or CMOS. It's a little bit of struggle because again this code is not always directly accessible but basically at works. so i think the killer app will Not Just be On The Pure Coding Because That Has Already Been Solved!

I Think The Killer App Will Be More Level Level Higher. So I Think Companies Need To Look More Into Orchestration and and how to manage all of that. Also, a coding agent by itself is difficult to control. if you can with pure coding agents go from pure vibe-coding to a very sort of agentic coding.

So if you don't pay attention, it's going to be too much vibe coding. so we will need go into the situation where anything that is adjusted with agents goes through proper version control and reviews or unit testing something we are also lacking in industrial automation. I think opportunity is more in this direction especially coupled by specific things. I mean by that sphere.

For example, we don't do agile coding. We have more a waterfall approach kind of things. And that's the orchestration or whatever you want to call it, project management tying in into the entire ecosystem? That there's not going to come from outside industry is specific for us.

so I think There's gonna be a lot of opportunity. So making coach generation industrial great Is this way cogeneration industrial grade. Yeah, make it reliable deterministic approach and maybe call a deterministic. so this is the way to go for all four of your automation companies?

So deterministic code generation that's what my company is doing. And so there's an alternative two alternatives as complementary too to genetic coding. So determinist code generation means You use a template based approach. And even if you delete the code and regenerate, it's one hundred percent the same.

This is something that actually already has been done for multiple decades but often in smaller teams. But you can also see this deterministic approach when you ask agents to do something for you. imagine? Imagine you asked Claude To Do Some Data Analyzes!

You will See That Claude Is Not Gonna Do It Just In His Memory. He'S Gonna Write A Python Script Most Likely... and Then This Python Script will do all the analyzes. In your day-to-day work, what AI adoptions?

Do you see among customers What they are doing? It's very early and I see most customers that also starting to use their regular cloud code. coo pilot is very common because it's relatively easy for companies. They're on Microsoft, they can open the subscriptions and then individual people just try to figure things out.

but I see that actually in the industry space is much less than software world. Where do you see your business model going? Oh maybe you could describe a little bit about what are you guys doing. Yeah, so again it's focused on the process industry.

So food, pharma chemicals and then the engineering workflow in this kind of industries. we start from a PNID built by mechanical or process engineers And based upon the P&ID We will not do the coding. you'll first do a functional description like specification. There is standards automation.

That's ISO eighty eight, so the platform that we're building is allowing people to collaborate on this functional description. and So then based on that We do the deterministic code generation? Where I see The future going Is that the agents will be more towards the left Towards This Functional design specification Helping with Building that And Then humans Can review it Or They can also Make adjustments. But It's Much More Easy To Review a Specification.

Then, code. Code is very hard to review even if you're a software engineer but functional descriptions are easy-to-review and anybody can't review it. so process engineer or operations engineer or even smart operator everybody can work together. So that's where I think its going.

And i also think You have three things working together You will have agents, humans then you'll have tooling Deterministic tooling And so the opportunity is in this tooling to bring industry-specific workflows or calculations, things that need to be managed. If you look for example at a DCS system there's lots of specific things on it but currently DCS systems can only by humans. They're totally inaccessible by agents, so the future DCS needs to figure out how do you combine this world that the agents can also collaborate on?

That's coming back to the API. is where Do You see good AI APIs? adoptions Can just name some players in the market Where we can say all that makes sense what they are offering with their API What I can do what a customer can do industry or outside of industry both worlds inside Industry, so for the coding I think already mentioned them. So it's is a newer generation of IDEs built by Siemens or Sematic AX.

It's back off PLC++ which will be released later this year BNR who has always been like and codices And i believe Rockwell also working on something Other than that. you now start seeing some applications providing MCPs. It's going that direction, I'm not sure if it is an official MCP. So this is the SCADA system and the MES layer...

I don't see too much yet! There are now a fully new open source. The MES is quite popular with carbon. I didn't check the details, but they are quite popular.

It is not an API because of their open source. you can let your agents just take it and adjust it. And then outside of industry there's a lot people discussing about this. So for example i think this week was the owner of Box.

com so its content management. he also posting lots on X So all Twitter and on, I think also LinkedIn or people shared it about LinkedIn. And these companies still didn't figure out. they say what you said before?

They say we need to go through. instead of a seed based subscription We need to do more consumption base cons subscription. It's still very early. Companies are trying to figure that.

Okay, so everybody tries out some POCs here. So you don't see something that we really can say? Wow! That's impressive.

That runs in the real world. Not immediately. What is on your agenda for next month when it comes to technology? Yeah...

I'm very much busy with my company. My Agenda is mainly supporting existing teams and onboarding new teams or trying to get more teams onboard. Also, my main thinking goes towards on the one hand how to make it easier. To adopt the new workflows and also how to prepare for AI in the future because you have to think anything that we built today if will be three years further.

competence. And I think most people still don't realize how, what actually they can do and the best way to figure it out is just give them. sometimes things so really go into the vibe coding or the Vibe engineering. So not on a real project.

but let them Do things see how far you can push them? It's becoming very crazy. The question is will these agents be able run for longer time by themselves, because now you do have to give them tasks. You have to review their tasks.

so how far are we from then being able to run for let's say almost a day and imagine what your product should look like? Then your products will be interfacing with agents. I see lots of people always saying yes but they cannot trust the agent. How do you structure your product that actually have full traceability, and then she had the checks.

And that's necessarily moments a human can come into to review and validate everything. so That one thing I'm working on a lot. if he asked me what i will do next month also saw it just got invited from. What is this?

The AI Association. did You see that one? no industrial network. So I see it's Accenture, Froenhofer, Siemens and Bosch.

Oh okay! I know the guys yeah... So I think that's also very interesting. months when it comes to APIs, AI coding agents.

What would you like to see from them? Okay well okay maybe three things. so first of all really make progress with this next generation of IDEs that are focused on decoupled the code So we can actually let the agent work directly in the codes. Second of all anything that cannot be managed by codes open up the eight APIs and some products have API's but they are not documented.

so document them. And then, third thing is we need to have a discussion about the standards because uh... We have big problem with the standards. Why do you have problems?

Can I explain that? why do we have a problem? So couple of key standard in automation. So we've got IEC six one-one three ones You're aware We have the ISA standards, ISA-Eighty-eight and ISA ninety five.

And now we have a very new interesting standard which is module type package Which will actually make it easier to connect skits and machines To higher level control systems. really interesting for pharmaceuticals chemicals. And so all these three standards, you are not allowed to share the documents and You're Not Allowed To Put These Documents Into AIs. So If You Go To The Website Of Isa For Example...

The First Thing You Will See Is A Pop-Up That Says if You Put The Standard into LLM They Will Sue You It's Literally On The Webside! This May Be Worked Before Because You Had To Have Humans Anyway To Improve The Standards. But Now We Come To World of Agentsic Engineering. If The Agents Do Not No, the standards.

They will not apply to standard. and then the engineers who have had to apply this standard if they have to choose between something that is known by the agent as something That's not know about agents? They will choose The things there are known By the agent. so IEC six one on three One Is a very big issue.

It already very fragmented And we still cannot teach the agents how To handle it. at the same time i really no. teams There Are just starting to switch two Things like python And of course you can say, well Python. Oh no deterministic and things like this.

but these are teams that really know what they're doing? They just said we need to move faster! Of course it's very small. But if automation companies want IEC six one-one three-one two survive...

they need to stand up as a look. This is still the future of automation then open up the standards and start thinking about this. So we will see new standards or We Will See A Standard Discussions. I prefer standard discussion, i prefer not to bring new standards.

like module type package is really nice standard. it's Not so complex! We could propose okay let us make a new standard but this doesn't help. and It Doesn'T Help To Go To A New Standard Because We Create Fragmentation.

The Best Thing Is That There'S A Discussion. People Understand And Say Okay This Documentation Needs To Be Open So We Can Apply It To Accelerate Engineering both with classical automation and with agentic engineering, but preferably on existing standards. We are living in interesting times and very interesting times. I really appreciated your feedback.

when it comes to the APIs via LinkedIn our discussion i keep my fingers crossed for you and your company. thanks a lot. all the best to belgium Okay! Thanks for having me.

You're welcome bye-bye.