 and welcome to Leitaz's live. My name is Federico and I'm delighted to be joining you from our studio here in Geneva at the World Economic Forum. We'll hear from leaders of the Global Lighthouse Network about opportunities of deploying at scale advanced and emerging technologies such as generative AI to reshape the future of manufacturing. For those of you joining for the first time, the Global Lighthouse Network is a World Economic Forum initiative founded in 2018. It is the leading global community of factories and value chains who are transforming their operations through the adoption of technologies of the fourth industrial revolution. As we speak, the network comprises of 132 lighthouses who are recognized for their leadership in using advanced technologies to drive growth, improve resilience, and deliver environmental sustainability. They represent a truly global community whose learnings and insights are lighting the way for manufacturers across all industries. To better understand the drivers of their success, we have interviewed some of these global manufacturing leaders. So without further ado, let me give the floor to our speakers to learn more about their strategies, their best-in-class applications, and their insights. First, let's hear from Enno de Boer, senior partner and global head of operations technology at McKinsey, as well as a long-lasting champion of the Global Lighthouse Network. Enno will help us set the stage sharing how key business priorities are shifting and how lighthouses leverage technologies to react. The past decade has seen more global disruptions than ever before. Hand in hand with these disruption comes economic impact affecting both, the big and the small companies. At the same time, we are part of the fourth industrial revolution, a transformative digital era in which members of the Global Lighthouse Network, our lighthouses are showcasing the potential of tech-enabled operations. In this environment, the traditional focus on service, quality and cost have become table stakes. There are three new objectives that have been added, resiliency, workforce and sustainability. In fact, in a recent survey, 77% of the respondents said labor productivity, sustainability or resilience is their top priority over the next 12 months. What sets lighthouses apart in these challenging times is that they know how to react. I'll dive in. First resiliency. Supply chain shocks have become increasingly frequent and intense over the past decade with serious ripple effects. Today, manufacturers can expect a disruption lasting one month or longer every 3.7 years, requiring them to make resiliency a top priority. This new environment means organizations need to rethink their operating model and build new capabilities to address these challenges. And lighthouses are doing this just with advanced technology such as real-time supply chain visibility, automated multi-tier assessments of materialists or predictive modeling of natural disasters. This has served them very, very well. Their capability to shift capacity, quickly introduce new products and proactively manage their supply chain, help lighthouse companies to experience about one third of the revenue shock of their non-lighthouse peers. One third. Second sustainability. Did you know that manufacturing consumes 54% of energy worldwide and contributes to roughly 20% of the global CO2 footprint? Lighthouses are showing us that with technology you don't have to choose between people, profit and the planet. With use cases such as real-time process controls, green digital twins and advanced energy management systems, lighthouses have not only reduced waste and carbon by more than 30% but also improved productivity by the same amount. This is remarkable. Third workforce. Talent clearly has become increasingly hard to retain. In a recent survey, 43% of the manufacturing operations respondents said that they are somehow likely to leave their job in the next three to six months. 43% in the next three to six months. All of this means that building the muscle to upskill workers for new opportunities and the challenge of digital transformations is important. Yet few companies know how to do it. Lighthouses can lead the way here again. Technologies they have implemented such as VR-assisted operator training, chatbot-based assessments and intelligent work instructions are all part of developing an adequately skilled but also engaged and productive workforce. Some have seen reductions of nearly 90% in both onboarding times and operator errors. Insightful overview and three clear imperatives. Resilience, workforce and sustainability. Today we are excited to talk about what has set lighthouses apart in their digital transformation journeys. We will first hear from Johnson & Johnson about their tech-enabled resilience engine. Then from Henkel on how to involve employees to maximize the transformation potential. And finally from Schneider Electric on leveraging AI to manage resource consumption. Later on we will ask other lighthouses leaders about their strategies for scaling the impact of the fourth industrial revolution and explore with them how breakthrough technologies can accelerate this journey. We asked Remo Colaruso, vice president of technical operations at Johnson & Johnson and Kevin Whitehead, vice president of supply chain, standards, risk and compliance to tell us more about their story on resilience and agility. For over a decade at Johnson & Johnson our supply chains have worked to prevent potential interruptions through robust business continuity plans and a strong risk management framework in quality, compliance, safety and reliability across our operations. We regularly benchmark and involve our processes to ensure ongoing continuity of supply for the patients and customers we serve. As we have moved from an approach of reactive risk management to one that drives proactive resilience we have been able to identify, mitigate and address multidimensional risk with increased agility and responsiveness. This proactive resilience methodology was developed and deployed to complement internal product-related risk categories with real-time external product-agnostic risk information like geolocation, weather, resource availability, social impacts, geopolitical complexities and more. Our proactive resilience capabilities centered around a resilience engine that leverages data science and analytics to look at a multitude of risks all at once. When combined with network and product-specific data it enables improved velocity and quality of trade-off decisions at node, product and network levels. These outcomes are enabled and enhanced by our operational capabilities which include digital control towers that provide real-time visibility across our end-to-end value chain, harnessing intelligent automation to maximize the capacity and productivity of our plants and implementing adaptive digital process controls to conduct in-line and real-time quality control. In our pivot towards proactive resilience we developed a platform to enable a multi-dimensional approach to building resilience supply chains. The new platform leverages a digital twin of each product supply chain and this has enabled us to move from what was predominantly manual and functionally led assessments to an integrated end-to-end approach creating visibility of all potential vulnerabilities. It was designed to be modular so we can build in extra functionality and sophistication enabling us to identify additional vulnerabilities and issues sooner and then react faster. Today we can more quickly quantify the potential impact and the best options for mitigation. In a way we've democratized decision-making along the value chain and this has led to cultural changes, greater engagement and richer dialogue on how best to move forward. As we built, advanced and evolved these new capabilities that are helping us uphold commitments to patients and customers to bridge connections from the Global Lighthouse Network and partnered across this ecosystem of industries, suppliers and customers to increase flexibility of our networks. It's no longer about just responding to risk. With the rapid pace of evolution it's about building the capabilities today that will help us proactively get ahead of and even transcend future risks. Let's change lens now and focus on workforce. We recently surveyed the Lighthouse Network and we found out that worker shortages and skills gaps are top of mind for 80% of our companies. To address this, over 90% have taken a holistic strategy to workforce enablement developing use cases across attraction, engagement, connectivity, skills development and augmentation. Let's hear from Dirk Holbach, corporate senior vice president of Global Supply Chain at Henkel joined by Marcel Welt, digital engineer and their experience on using technology to enable and empower Henkel's workforce. At Henkel we have transformed our supply chain in various phases. Currently we are leveraging the fourth industrial revolution with smart factory concepts, artificial intelligence and augmented reality. Our consumer brands factory is an excellent example. In this state-of-the-art factory we have implemented our so-called digital backbone more than 10 years ago. The factory is one of the first three most sustainable production sites in the World Economic Forum Lighthouse Network. Our fourth IR journey started here and now around 30 productions and these 10 distribution centers are in the meantime connected worldwide. The digital backbone records millions of data points every day and converts them in real-time using artificial intelligence and translates them into concrete actions via dashboards and graphs. Thereby our workforce can identify the most efficient and sustainable processes for our productions in real-time and soon in every consumer brands factory worldwide. This ecosystem is important an important lever for our sustainability ambitions and is helping us to improve our overall energy efficiency. I'm as digital engineer working here in the Consumer Brands Production Plant in Düsseldorf to ensure that we take these employees with us on our digitization journey. A lot of production workers have been working for Hankel for quite some time. They have their fixed work routines, they are doing what they're doing every day and that maybe for the past 30 years. We know that change doesn't happen overnight. We also introduced iPads on our production lines. There we use ourselves developed and created apps like the Connected Worker Apps. With these apps we are reducing the paper in the production and enabling people to feel digitization at the production line and really to enrich our data with more metadata from the production workers. So during the rollout of the Connected Worker Apps we went to production and introduced them actively to our operators. We received feedback from them in order to then redevelop and reiterate on the design of the app so that the end product of the app is actually very usable for the production workers and that they receive it well. For example, in one of the apps the defect handling app you can go ahead take pictures on the line of defects and then add some data about the actual defect. This defect will then go out to the day shift team so that it can properly prepare for maintenance. This success was only possible because we put our workforce at the center of the transformation journey. I am deeply convinced that technology only works and delivers benefits when we manage to take everybody along. Technologies can be bought but our employees at the end make the true difference. There is no transformation without engaging and involving our people. The requirements for our workforce change faster than ever. Therefore we are investing into capabilities into our teams so that everyone is not only involved but can actively shape and take part in our digital transformation. An important message here technology only works when you bring the whole organization on the journey. Let's consider now our next key priority sustainability. Lighthouses are using technology to find and enable new synergies between sustainability and productivity. This proving the notion that reducing impact on the environment only comes at a cost. Schneider Electric has been a leader on exactly this deploying digital use cases to drive sustainability across their production network. We'll now hear more from Murad Tamoud, Chief Supply Chain Officer joined by Virginie Rigodeau Sustainable Transformation Project Leader from Schneider Electric. In my conversation with supply chain leaders I often hear that one of the biggest challenge they face is how to get out of what the World Economic Forum calls pilot purgatory. That is how to scale projects that improve sustainability at the site level across the organization. There are two steps we have taken at Schneider Electric to make this challenge. Firstly, sustainability is a core pillar of our supply chain strategy and central to our mission. We have made public commitments to improve sustainability across our own operation as well as throughout our entire value chain. By clearly defining our goals and making them transparent we provide the clarity to our organization when it comes to sustainability. Secondly, we have set ourselves up to empower our local teams to drive innovation supported and connected to the global network. Our local teams act as owners in their plans and are encouraged and given the opportunity to test ideas to improve sustainability outcomes. We know how people make the difference for our organization. They are connected to a variety of platforms, to each other and to our global teams to share what they did and what they learned so that we can scale quickly across the organization. Let's take a look at one example of a local project that has now been implemented in some of our other sites in our factory in Le Vaud Roy, France. The biggest consumption is compressed air. It accounts for 20% of the total energy used in the plant. And on our line there is DECA contactor. We use a lot of compressed air and we wanted to better manage the energy consumption on the line without impacting the manufacturing performance as well as empower collaborator to manage their own energy efficiency on the line. To do this, we have worked on this area as an example on TESIS DECA production with our operators with Pascal Pica that is set around this line to implement a global energy monitoring architecture including IOT sensors and data measurement through analytics like this one and we go deeper with artificial intelligence analyzing the influence of each part of the machine once we reduce the air pressure we identify the bottleneck and bring the other part of the machine to the same cycle time. It results in the set of a reference model to the machine Intelligent Artificial Sense Alert and all the action done will be registered by the system on delivery prescription. You can see that this is a close relationship between Pascal between our operators and the artificial intelligence development team that make possible to build this model. In parallel, we have connected our production planning to our PLCs in order to generate an automatic cut of energy on most of our machines taking care of the critical ones. So we have our production planning and we can follow if we have the shift during all the day or not and at each end of shift there is a countdown that will start. Let's have a look to this countdown so this countdown starts and the operator has the possibility to interrupt or not this countdown according if we have a team working after or not. The combination of those two actions brings minus 15% of air savings with an estimation of minus 3.5% of electricity consumption on this area and a return on investment about two years and two months. So globally, it enhance the global achievement on energy efficiency at Lovatres site that is amounting to 29% at the end of 2022. This is a scalable solution so we have implemented it across other factories driving greater impact and globally, we have achieved 7 million euros savings on energy consumption scaling this project alone that 3% improved energy efficiency. It's inspiring to hear about all these technology use cases to improve resilience, workforce and sustainability. There are more than 600 solutions like these in the Lighthouse Network most of them showcasing double digit improvements on metrics like energy efficiency product quality or manufacturing cost. Although to achieve the full benefits of the transformation these use cases must be deployed at scale. This includes scaling across production networks, supply chains and all corporate functions. Most of our Lighthouses are currently already successfully focusing on these challenges. Let's now hear from these scaling champions including CATL, Foxconn Industrial Internet, Cosh Holding and Siemens on their strategies to scaling digital solutions and their perspectives on future manufacturing technologies. I believe challenges is always there. Scaling has its own difficulties. The intricate nature of discrete manufacturing involving process like metal working and assembly demanding solo automation besides that capturing subjective touring related knowledge for success proof challenging. Let's look at ourselves Siemens 175 years old we're very big but we're also very decentralized. We have more than 120 factories and there's many different types of factories. Some are being built right now others have been around for decades and especially these ones, the latter ones the brownfield sites have very specific challenges when it comes to scaling technologies. The software which has been developed for those factories is often very specific for those factories. Very specific needs, very specific environments. They have never been designed to be in an open manufacturing ecosystems. Second one each of those factories tend to be microcosm. They have their own patterns, their own culture if you want and they're very skeptical to really sort of apply technology from another factory and see if it would work even at all. And the third one common across most engineers the not invented years syndrome. Now the main challenge we have is to transform all these individual factories which are isolated microcosm into an open manufacturing ecosystem. Scaling is hard even for our 70 Lighthouse organizations. Only 11% have deployed 4IR technologies across their full production network. The top three challenges that our Lighthouse network community experiences are fragmented data landscapes, legacy IT infrastructure and a lack of in-house talent. But advantages for companies that do effectively scale are clear. In our experience transformations that start with scale in mind show two to three times the ROI of single-side approaches. That's a lot of value at stake. To find out why we can look to 14 companies that have made real headway on scaling challenge. These companies have scaled to three or more Lighthouse sites. Eight of them have scaled to five or more. These, I would call them advanced scalers possess a unique ability to design 4IR solutions with scale in mind. They master three transformations simultaneously. The business, the technology and the organization transformation. What sets front runners apart is how they design each transformation in a way that reinforces the others. That and the fact that they found the right pace. Pace is critical and can be like swimming against the current. If you go too fast you leave too many people behind. If you go too slow and change fatigue that sets in, typical after two to three years it's very problematic. Scaling itself is very important because at CATO we have hundreds of production lines and they all have similar characteristics. When we discover one opportunity for example in energy consumption if we see an opportunity to improve the energy consumption we quickly adapt to the rest of the production line in our cooperation. That simple innovation can produce a very large effect. Each of the production lines has its own unique requirements. That requires us to customize even though the idea methodology is the same but actual implementation, actual scaling requires customization. In scaling up the use cases we have focused on the ones with substantial impact on operational efficiency and overall performance. Compatible data availability is of course another precondition. The use cases should also serve to our strategic goals of institutional resilience, agility and sustainable growth. As prominent examples I can say that related to mobile robotics and AI-based energy management and quality check systems were quickly scaled up. Another successful use case was creating digital twins of our production lines and machines. This one alone enabled a 10% reduction in cycle time, over 30% decreasing defect products and 15% saving in energy consumption. Ultimately business transformations are about identifying, prioritizing and capturing pockets of value. Organizations that prioritize and scale use cases according to business value will clearly outperform peers. The right approach needs to be tailored. Across the hundreds of examples we have seen, three stand out. The IT-led approach is best when speed of adoption is critical and sites have strong change leaders. As we have heard, CATL is one of the examples of this. With hundreds of production lines, they can identify new use cases in one area and then rapidly roll it out across all the lines and factories creating productivity improvements of up to 75% in some cases. The COE-led approach is best if networks have slightly differentiated sites. There are very good examples for that. Their COE in Hamburg developed a blockchain-based software to exchange CO2 data with suppliers and gain visibility over 90% of their carbon footprint. This way, they were able to concentrate resources and talent in one area and share best practices and learnings across other sites. The IT-led and COE-led approach have worked for companies with many factories such as Siemens and CATL. But for more consolidated manufacturers such as Tata Steel, a built and replicated approach has been successful. This is best when time isn't a critical factor or when plans are each very large and distinct. In Tata Steel's case, they deployed advanced analytics tools on one plant at a time. First in the Netherlands, they then replicated to two more plants in India. All three are now lighthouses. Today, nearly 80% of Tata's total steel production comes from these three sites. Scaling a use case across diverse locations and challenges. Digital maturity levels, IT backbones, and of course skills of employees are not the same in different factories. So, in order to ensure the coherence of the process, for example, Archelik established central and local transformation offices. The central office shapes the defining pillars of transformation strategies while local offices use case applications. We also have a tailored platform for best practice sharing among different factories. This platform enabled Archelik to implement more than 60 scale-up projects which were all inspired by lighthouse factory use cases. Active employee engagement is also pivotal in transformation governance. Previously, we mainly rely on experience process and tooling engineering experience to ensure precision level and the quality, which actually limits our ability to extend to new regions and to quickly establish new factories to meet quality standards. Besides that, we privatize flexible automation to adapt to the rapidly changing demands of the consumer electronics industry. We have successfully extended automation to improve processing, material routing, tooling handling and packaging enabling us to respond more efficiently to market fluctuations. Our strategy involved in two key steps. First, we focus on horizontal integration using software to streamline PLC programming and data collection across diverse hardware. Second, we move from exploring an LP to harnessing generative AI which offer a more effective route to digitize compressed knowledge. We are now able to ramp up at the multiple sites at the same time which means we can be more efficient than before with digitalization. Technology transformations are about ensuring you have platforms and infrastructure in place to deploy new use cases and capture business value. Lighthouses often cite the design of the technology stack and the robustness of the technology ecosystem as a two critical enablers to their success. We have seen this again and again with the lighthouses go slow to scale fast. Make sure your data is clean, accessible and secure and make sure there is a business informed standard across your sites. You don't need every piece of data but you should have every piece of data you need. When we like to use data then priority number one is going to be security and quality so ensuring the quality and security of collected data actually are very crucial. So particularly when using external AI resources so we build data center and establish Vaskan's private cloud to move all local storage to the cloud allowing us to efficiently access data across the sites globally while maintaining security. Also we put a lot of different security scheme in the network in addition to the data center itself so which actually will protect the integrity of our data we collect especially for the overall operation. So the security scheme between data center and also between factories become crucial so we pay a lot of attention to maintain the security and safety for the data center as well. We need to bring everybody on board. Siemens' unique situation mandates that we use the software and hardware we sell to industrial customers in our own factories. Silicon Valley where I came from we talked about eating our own dog food I'm how French and I prefer to tell my team drink your own champagne and that's what we do. Our factories act as customers zero for our technology. They provide insights into our product experience. With our Siemens Accelerator approach we make sure that all of our products are compatible and not only with each other but with partners and the entire manufacturing ecosystems. Using what we sell really helps to drive innovation and foster a customer centric approach. Collaboration with external partners is very significant. As transformation requires a compatible ecosystem you cannot leave any stakeholder behind. We offer our state of art capacities to our partners. Archelic works with technology providers, start-ups, academia, SMEs and it's all suppliers at Atelier 4.0 which is an advanced manufacturing and robotics lab. Synchronization with suppliers is especially important. That's why both for Totosan and Archelic actively encourage and support the digital transformation of their suppliers. But don't think that our partnerships are only focused on manufacturing technologies or logistics. It's beyond that. For example, Archelic has collaborated with a stakeholder to develop a digital occupational health and safety platform which reduced safety warnings by 80%. Underpinning both business and technology transformations organization transformations are about step changes in operating model culture and capabilities. Full leadership alignment and commitment are necessary so that leaders can flexibly manage priorities and accelerate resource allocation or decision making. To do this Lighthouses commonly deploy strong transformation offices, robust learning programs and many universities as well as strategic reward mechanisms. Technology is only as effective as a people and the organization behind it. Siemens is a huge company with more than 120 factories in the world. Many of them were developed in different small organizations. Even if it is one Siemens of course we have different organizations from mobility to smart infrastructure to digital industries and there was a kind of a silo environment. Our approach was when we started the digital journey that we need to bring these experts from the different factories together so that to create a community of experts where they feel free to speak and to exchange their ideas and their knowledge so that everyone can participate from their other solutions and scale faster in that way. In order to build up our capability we believe that we require talent. The talent who are knowledgeable about IT about DT, about AT and about OT at CATL when we bring engineers, higher graduates from college they come to CATL we provide a lot of training. So CATL up to now has created more than 22,000 different courses and this year alone we have over 960,000 workers went through different training courses so of course our size is 130,000 that means many people went to multiple courses. Related to the smart manufacturing digital transformation we have about 400 courses and we have more than 22,000 people trained with different IT ATDT technology. We established a brand new department called IMD Intelligent Manufacturing Development department and that department now has over 400 engineers. So it's a very comprehensive. This IMD department is specifically looking for opportunities to adapt for our technology to solve production problem or engineering problem or product design problems sometimes even they go beyond the CATL boundary to our supplier upstream or downstream supplier vendors to help bring smart manufacturing to our production. I always underline that at core of transformation we have our people that's why we promote agile transformation at coach establishing cross functional teams with minimal hierarchy. Because digital transformation requires rapid adaptation and action. We also implement special up-skilling and re-skilling programs with an ambitious program called FutureFit. Thousands of colleagues attended individual tailored digital skill trainings. Moreover with FutureFit we are defining completely new roles in the organizations which we believe best serve to our digitalized workforce. We had a kind of a mascot here and a symbol it was the flamingo. It sounds funny but the flamingo for us was so important because it shows when they these animals are standing together and then when they are going to another place for getting more food or for shelter they start together and they start together and wait for the last flamingo also to join. So the stronger one at first and the next one which are weaker or need support later but no one will left behind and it was a symbol for us we wanted to take all with us all 120 factories on this journey and they are still with us since 2016. Looking ahead Lighthouses see a really bright future they see a world where scaling 4IR technologies can do more than just unlock meaningful business value. They can mitigate environmental impact they can empower workers in all levels of the organization and they can build resilient supply chains. One additional thing these Lighthouses see on the horizon is applications of generative AI the next instrument in the digital toolbox for manufacturers. There's a good reason for that. Globally we expect generative AI to add 4 to 8 trillion to the global economy. Of that we expect half to 1 trillion in productivity improvements for manufacturing and supply chain related activities. We have identified 50 new use cases of how to apply generalized unique capabilities for insight extraction content generation and user interaction in supply chains. Many of these are already being piloted by manufacturers globally including by Lighthouse companies. I'll give two examples. Bosch has a use case to cluster and identify visual defects and Siemens is really interesting they for instance have been working with Microsoft to automate PLC code generation. Look, why do we use technology? It's to empower our people. They are and will remain an integral part of the factories. We use things like micro-learning or wearable technologies to make their working life a lot much easier. We want to also use tools like generative AI on the shop floor. For example, we integrate the Siemens Team Center software with the Microsoft Teams collaboration platforms. This enables services technicians to report quality problems in natural language via their smartphone or tablets. By deploying this type of generative AI we can help our people collaborate faster and much more efficiently. So FII, we envision a future landscape where digital plus ESG technology drives the scanning of forest industrial revolution technologies in the manufacturing sector. We will focus on creating smart factories with real-time monitoring predictive analytics and autonomous decision-making powered by advanced AI technologies. All enabled by cloud infrastructure. Additionally, we will leverage digital tools to mitigate our environmental impact starting with carbon emissions in our factories and eventually building a sustainable supply chain. This is a systematic engineering challenge that requires collaboration between companies and industries. And also, we are committed to exploring the path of sustainable development for the industry. Actually, to drive this landscape digitalization, automation robotics and AI fall in a merge together will be very important to drive the entire industrial 4.0 transformation. We prepare for wider adoption of generative AI and even general AI in the future. Our focus is on establishing a robust infrastructure to support their integration. While AI is still in development our emphasis on creating an accessible and adaptable software and hardware environment. We are also focused on data quality. Having high quality data is really important to be able to fully capture the problem-solving value of generative AI. AI rely on data, rely on model which also will give your process more consistency. And when you have this definitely is going to drive your process quality but also will drive your AI get more mature and AI keep growing as well. The real power is going to be autonomous intelligence like AI. So the AI got more popular and mature which is going to activate the robotics more in the production. So the new generation of AI will play very important role. So pretty much we will move from automation up to robotics production for next era. So which probably will be very important topics for all the manufacturing companies to adapt the latest AI technology as well as robotics to ensure your competitiveness and to ensure efficiency. Well looking into future we believe there's more opportunity we probably only touch the tip of iceberg we believe there's a tremendous opportunity all over the functions within CATL. Right now we are doing total transformation, digital transformation from every function from HR finance, purchasing internal service and of course engineering and research and marketing and after sales. So that's one thing we are doing systematically try to using more digital platform to automate our process. Second direction we are looking for how can we use in big data AI as a generative AI to enhance because the first effort, the digitalization only solve the automation problem the routine work humans routine work will be done with the help of computer to speed up. That solve the efficiency problem but now when we talk about smart solution we try to do better than our human being can do because human being we are limited we can only recall certain number of things we can only imagine several variable interactions. When the number variable interactions become hundreds of thousands we are limited. So the computer on the other hand can do much better recalling associating so we are trying to combine human beings intelligence with machine intelligence so we call augmented intelligence so in this regard we hope in the future CATO's design process will be much faster more efficient can do better than our human best designer can do. Also in the processing we hope we are driving for extreme manufacturing because without these kind of tools we are limited on the quality we can achieve in order to achieve a higher quality we must rely on these kind of smart tools methodologies to achieve that kind of level of quality. We know to train a lithium ion battery engineer from ecology graduate it takes several years before the person can independently perform a design task because it is so sophisticated involve multi physics, chemistry physics electrical engineer mechanical engineering, material science and so very complex it's very difficult for human engineer to really learn to master the skill of design. We are trying to using generative AI to help fresh engineer quickly learn those basic rules because you don't have to remember everything that generative AI can provide you the database the lookup table and even some simulations. So that's what we are trying to see can we help engineer ecology graduate after half year learning the tool can become an independent designer also maybe a designer who have a three years experience can design a product which is better than a 10 years engineer used to be able to achieve so that's something we are trying to do. These new generative AI use cases will have material impact not only can they accelerate key processes and reduce workload by 70% or more but they can also critically augment capabilities this will be especially critical for companies looking to accelerate their journeys from lighthouse factories to lighthouse networks being able to accelerate software development automate data structuring and personalize worker training and augment worker knowledge will be transformative to the organization's ability to scale quickly and effectively. Gen AI can have a nitro boost for technology adoption. The bad news is that to keep up you will have to move faster and go bigger from day one. The good news is that it's possible with a thoughtful approach to business, technology and organization transformation. I hope you enjoyed as much as I did the insights and learnings from the lighthouses we have seen today. And this is just a small fraction of the tens of thousands of manufacturers around the world. There is still a lot of work to do before all the factories realize the full benefits of the fourth industrial revolution. We hope these stories have inspired you to accelerate on your digital transformation journey. And now, it's time to bring the event to a close. Thank you again to all lighthouse leaders for sharing their stories and to our colleagues in Geneva and New York for the hard work that made all of this possible. If you are ready to share your success story on adopting leading-edge technology innovations or are interested to hear about the very unique learning opportunities that the Global Lighthouse Network provides, we invite you to reach out to us. The next application cycle to join the Lighthouse Network will close on January 26th. Visit our website to learn more. Thanks all for tuning in. Please stay engaged and see you soon.