Good afternoon. For those who are new, I'm Dr. Theron Sherman, and in today's briefing, we will be studying SCP-6101. There isn't any objectionable material in this document, so let's begin. Records and Information Security Administration Notice, the O5 Council, has approved for the SCP-6101 designation to be reserved for the exclusive use of the Department of Public Relations to aid in post-broken masquerade operations. Item Number SCP-6101 Classified Cosmic Top Secret Containment Class Esoteric Secondary Class Thaumiel Disruption Class Ecce Risk Class Danger Special Containment Procedures SCP-6101 is too powerful to contain. He is to be left in the care of his family until the next time the Foundation should call upon him for assistance. Description SCP-6101 is the most powerful SCP. His name is Ethan Prosper. He is 9 years old at time of writing. The full extent of SCP-6101's powers are unknown, but he has displayed capabilities such as flight, super strength, invisibility, and all the powers of the Marvel superheroes. He is anomalously brave and capable of doing anything he sets his mind to. SCP-6101 has two guns which he carries with him at all times. The guns, which he has named fear and loathing, shoot bullets of pure light and darkness respectively. His dog Heidi, sub-designated SCP-6101-1, is the second most powerful SCP. She is fiercely loyal to SCP-6101 and protects him from anomalous organizations who want to use his powers for themselves. Incident Log On May 18th, 2028, SCP Omega broke out of its cell in Site-301. Unable to re-establish containment of the anomaly, Site Director Roush Pashakavarty called upon SCP-6101 for assistance. SCP-6101 was then personally escorted to Site-301 by Mobile Task Force Psi-301, codename Genie in a Battle, from his room at St. Jude Children's Research Hospital. Using a combination of telekinetic abilities and verbal threats, SCP-6101 successfully drove SCP Omega back into its containment cell as witnesses applauded and cheered. He was awarded a Foundation Star for his efforts by Director Shakhavarty in a special ceremony shortly afterward. In addition to saving the lives of everyone at Site-301, SCP-6101 became a hero to countless other critically ill children like himself. After reports of his bravery on local news stations led to a surge of donations to the Make-A-Wish Foundation. Thank you for listening.  Please become a patron or visit our merch store at the link in our bio to support our work. Secure. Contain. Protect.


So we got a little busted this morning for sleeping, but I told them we showed up You know like I know right I told we showed up early in the morning and we're just resting trying to do some photography but um, so if you do come here just know that He said in all of the state parks you have to be in a designated camp spot So that basically means like we should have been parked down the street like a mile or up that way Also guys, I'm doing a giveaway for my subscribers But I want to be fair to everybody so you got to go over to Josh and Cody's channels a short description of the giveaway that I'm doing So rad okay, so me and Josh and Cody are on a road trip And we were thinking how to incentivize people to come over from their channels over to mine So if you guys can get me to 25,000 subscribers by August 1st 2017 I'll be giving away an iPhone 8 or 7 just tell me which one you want because I know some people I know we got to wait for it and if somebody wins and they want prefer a 7 that's totally okay But this is an iPhone 8 giveaway, so this is how you enter just comment on one of my road trip videos with these guys Starting a couple days ago.  That's it. Um, thank you for subscribing Welcome to my channel, and I just want to thank these guys for the generosity of promoting me on the next time Always All right Ready set go just so you guys know I mentioned there's no sleeping overnight. The sign doesn't say it I don't know the legality of getting a ticket, but we didn't get one. So I'm a little bit tired But you know whatever woke up to this view not hating life one Bit at all you can have your part in peers if that's your mode, but I get my half from smoke and so Oh, yeah, I get up with it down with it. Love it and can't quit it right on and the best that ever did it and got away with it But I get my half We just pulled over on the side of highway one we're gonna fly the drone well, you'll see What's your thoughts Josh you think I should get one of these things. Yeah, man. Everyone needs one of the creeps You're gonna have long boards. We're gonna just chill on bomb hills. Oh, man. That was so much fun. I'm totally hooked now. So Sick I actually felt like the rush out there. I don't know. It's just so cool Dude, thanks so much for filming us Because you see what that word says right there. I'm so excited I've never been so excited for a shower before Epic oh man, see I knew there's gonna be some sort of shower I was keeping my eyes peeled literally two minutes ago.  It looked like a sharp tooth Why there was shower in the drain? I don't know, but I now have a little band-aid so next time I stop I'm gonna get some super glue and patch that right up Sick So we are now over at Glass Beach in a Fort Bragg Just mind of my own business trying to update my drone and we got like a crew out here say what's up everybody These guys are parked behind me on PCH and Malibu the other day These guys are gem gemstone hunters and then we just met these guys a second ago Cool, what's your name? God bless. I'm Toby Toby and we got Nate Nate, and I'm sorry. I cut you off when you said your name Right on cool very friendly dudes up here. Just hanging out and actually One of Josh's viewers so when Josh gets back I'll introduce you for sure Boosted ride, he's also a little chilly welcome to Northern California where it is not hot and muggy in the summertime At least by the coast. We're just gonna go for a little cruise Try to update the drone trying to fix that with a hopefully firmware update My laptop is kind of broken Sounds like the fan sounds like a Coffee maker percolating not good, right? I Know it's very nerve-wracking. So that's a yet another thing to fix Anyways, go for a little ride Makes the glass a little bit cleaner clear because up here. It's a bit more opaque The water makes it just amazing and sunset I got to say is by far the best time to come down here. So if you guys do stop by If you can stop by at sunset highly highly recommend it From being down here before I can tell you guys that this place used to be a dump They used to throw cars down here stoves And obviously lots of like I'm assuming glass bottles and all kinds of glass glassware Way back in the day and it was a an ongoing inferno For for many years. They just burned non-stop. I guess that's what they did way back in the day was burn their trash Something kind of unheard of but also something that third world countries still do Yeah, totally do it here. Yeah, they don't not anymore Anyways, so check it out. It's a super cool place. It's fun. Look at this. Oh, that's not glass. That's like a Sea monster, but um don't take the glass because if everybody takes the glass there will be no more for everyone to enjoy I found the most epic parking spot for anybody who wants to park here. There are a ton of cars This is kind of what it looks like in the daytime ocean view Pretty awesome. So we're gonna wake up to an incredible incredible view tomorrow morning. So You said you can't really see but there are a ton of cars Parked right here For all the new viewers. This is called boondocking. It's basically Parking without a campsite kind of thing. So You guys are in for a treat either. Yeah, you guys are in for a treat tomorrow. What's over here the ocean? Yeah We could have thank God we didn't Anyways, you want to play around with some night photography? Yeah, all right. We're gonna do that. Well, thanks for watching and I will see you tomorrow


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 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.  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.


Well, it's a wonderful day to be here today with so many people from the QPS, but our partner agencies as well as the community Darkness to Daylight is really shining the light on DV to remember the victims To educate the public to change the way that we think about DV to actually make it a safer place For our women for our children and for our families. That's what Darkness to Daylight is all about As a broader community it affects all of us and we all have a responsibility to it So coming together with other sectors of the community other departments other people committing to making a difference But I tell you for me is very very cathartic We can improve in this space we can prevent the escalation of this part of Our society seeing everybody coming together like that with those candles reinforces to me that we can make a difference I know from your presence here this morning that you have heard her voice and That you are committed to changing attitudes and social norms All of us together Can create a society of equality and respect where these rights are realised and where violence against women children and family members is unthinkable


This is stock number 10673. We are here at Summit Automotive in Fond du Lac, Wisconsin. You're new and use Dodge and Dodge Durango headquarters. Today we are checking out this extremely clean, extremely good-looking 2018 Dodge Durango RT. This vehicle has the 5.7 liter V8 Hemi motor, which pumps out 360 horsepower. It has been fully safe and inspected by our service shop. It has a fresh oil and filter change. All the fluids have been checked and topped off. The Durango has been fully inspected and is 100% ready to go. Diamond black pearl coat, or DB black as Dodge calls it, is the color. We shoot all of our videos in 1080p, 60 frames per second, so if you have HD capabilities on your computer, tablet, or smartphone device, turn them on right now because it is definitely your best way to check out the vehicle quality and condition-wise before seeing it in person. If you'd like to check out all the photos in the upper right-hand party screen, there's a link right to our website. It comes with the Granite Crystal painted 20-inch rims and it has Bridgestone Ecopia tires on here. These are two 6550R20 tires and they have probably about, I'd say, 60 to 70% of the tread left on them. I didn't see any dents or dings on that front fender. You do get the projected lamp headlamps, the LED running lights, and the LED fog lamps, front bumper parking sensors, and that front bumper is in excellent shape. No dents, dings, or cracks on that. It comes with the sport hood. Didn't see any dents or dings on there. Passenger side fender is in excellent condition as well. And the passenger side rim, no scuffs or scrapes on that very nice condition. As you go down this side of the derangle, you can see just how clean the body is, how reflective and mirror-like that paint is. We take these HD videos so if you are far away, or even if you're close by, and just cannot make the trip down, but you're still interested in purchasing the vehicle, you can see the vehicle, hear the vehicle, and have confidence in what you're looking at before you even get here. So that when you do get here, there's no surprises. And that is why we offer the Summit Auto Fastpass option in the upper right-hand part of your screen, link right to our website where you can apply for financing. Get pre-approved, see a payment quote, and even appraise the trade if you have one. So when you get here, all you got to do is drive the vehicle, love it. Back tires have just as much tread as the front tires, and this back rim no scuffs or scrapes. Four-wheel disc brakes on all the derangos. And as we come around to the back of the vehicle, you can see the rear bumper is in excellent shape. No dense dings or cracks on that. You do get the dual rear exhaust with the chrome tips. The rear gate and LED racetrack tail lamps are in excellent condition as well.  Lots of room in the back storage area. These seats do fold down for extra storage. They go down really nice and flat. To get them up, you just go like so. Then you do get a subwoofer back here, part of the Beats audio, and then there are jack tools in there and more storage area underneath.  As you go down this side of the vehicle, just as clean as the passenger side, no dense or dings on that rear quarter. And for full disclosure, this back rim no scuffs or scrapes on that. Down the rest of this side of the vehicle, very, very clean. You do get the enter-and-go system, just have to have the key on you and it will automatically unlock. You do get heated mirrors and built-in directional signals.  You get the red stitching, the RT stitched into the backrest. There are no rips, tears, or scuffs on those seats. Driver side lumbar with power driver seat, factory floor mats, auto headlamps, power tilt, and telescopic steering wheel. You got those Beats audio speakers right there, memory driver seat, power windows, power locks, and power mirrors. And as we hop inside the vehicle here, I will turn the lights off so we can get a better look at the instrument cluster here. You get the seven-inch LCD display, digital speedometer, has a compass, time. You can change those to read whatever you'd like and you can see that this vehicle only has 11,724 miles. You get the heated leather wrapped steering wheel, cruise controls on the right, Bluetooth and information center controls on the left, and you do get the paddle shifters there for sport mode. This one has the AM FM and Sirius XM radio capabilities on the UConnect 4C radio. You can do Android Auto and Apple CarPlay capabilities on here to project to the screen, and this one comes with the factory navigation as well. You can see you got AM FM and Sirius. You can do your climate controls here with the dual climate control. You can also do your heated seats and cooled seats and heated steering wheel buttons there, and you can check out the backup cam. Those are dynamic grid lines, meaning that they are going to turn as you turn that steering wheel, so you can kind of see where you're headed in the future, and then that center line lines right up if you would have a receiver hitch on this vehicle, or put one on here to be right in line with that. Then you do have the factory navigation, other controls, and then your projection manager is where you would do your Android Auto and Apple CarPlay.  Down here you get two USBs and an aux jack, the eight speed automatic transmission. You also get the entering-go system with the remote start and power lift gate. Passengers side format and seat are in excellent condition. I don't think this vehicle's ever been smoked in. You do get the power sunroof up here, and you have home link buttons for your garage door security systems and lighting systems. You also get map lights up there, SOS and assist buttons in the rear view mirror, and finally for your four-wheel drive system you do get four-wheel drive auto and a low-range as well as a neutral feature for flat towing. We'll take a quick look at the back seats and then we'll check out under the hood. Also point out that it does have that cool carbon fiber dash and door trim throughout the interior here. Back seats are just as clean as the front seats, no rips or tears back. Here you do get the latch child safety system, the second-row bench seating. These seats on the outboard side, so the passenger and driver side, are heated. You have factory floor mats back here as well as your heated seat buttons, two USBs, and then a 115 volt 150 watt plug-in. These seats fold down and up like so. To get to that third row we do have the floor mat back there for that, and the third row seats are in excellent shape. Looks like they've never been sat in, and just in really nice condition. You also get rear air controls up there. Child safety locks on the back doors, the bottom of the doors all look really good, which they should for an 18, and then it does have the capitalist fuel fill back here, which is a nice feature. Never get gas on your hands again. And we'll take a quick look under the hood. I would personally like to thank you for checking out the video today, and I think from this HD video you should have been able to tell just how clean this Durango is all the way around, inside and out. Under the hood we have the 5.7 liter V8 Hemi motor. Engine bay is very, very clean, runs very smooth. This Jeep has been fully safe and inspected by our service shop, has a fresh oil and filter change. All the fluids have been checked and topped off. You can see it does have the true cobble hood, 360 horsepower, and this one's all ready to go. I would highly recommend this vehicle from a quality and condition standpoint. And to see more pictures of this Durango or one of our other 450 new and used cars, trucks, SUVs, minivans, Wranglers, half tons, three-quarter tons, one tons, Durangos, you name it, we got it. Go to our website www.summitauto.com. Full pictures and descriptions of every single vehicle from two locations, all at summitauto.com. And if you'd like to check out more HD videos, you can go to youtube.com slash summitauto. Remember to like, subscribe, and share on this video and all the videos that you see there. In fact, in a second you will see a link to subscribe to our YouTube channel on your left. A link to more Durango videos like this one on your right, if you have not been to our website, on the bottom link to this vehicle on our website. Click those, check us out, and we're super excited to help you with this extremely clean 2018 Dodge Durango RT in DB Black Metallic. Thanks again.


Welcome to another edition of RCE. I am your host Brock Palin. You can find our website at www.rce-cast.com. You can subscribe find the RSS feed and submit requests for other shows. I have with me my co-host Jeff Squire from Cisco and the open MPI project. Good morning Brock. Good morning Jeff. And today we have with us two people who work with the HDF5 file and not exactly sure exactly what it does and what you'd call a file a file format or what but I have with me Mike Fulk Hi and Quincy Quincy, I think Brock was being a little too polite there. He wasn't entirely sure how to pronounce your last name Quincy Could you could you say that for us? Sure Quincy cozy all Okay, thanks a lot guys for taking some time with us So quickly where you guys located? We're located in Champaign, Illinois We're at the Research Park That's part of the University of Illinois So are you guys affiliated with NCSA down there also or not? Not Officially anymore. We still do work with them. We have a contract with them We started out as a group at NCSA and we were there for 18 years and then we spun off as a non-profit company whose mission is to sustain and support HDF technologies Okay, before we go further though. Can you guys give us a quick rundown on what is HDF? Yeah So HDF is actually several things We talk about the HDF suite of technologies and by that we mean file format and then software Library that allows one to access data in the format and then various Tools some of which we developed and then those Others There are actually two HDFs The original HDF was developed in 19 first first 1987 and Implemented at NCSA with a variety of really visualization tools and It was always open source and it kind of caught on and Went through several generations Until the fourth generation, which we now call HDF for By that time it was widely used All over the world, but in particular the NASA Earth observing system was using it And that was sort of our bread and butter project Then by that time that was a what ten years we'd been in existence almost We realized that there were a lot of things we could do better The Accelerated Strategic Computing Initiative project came along which was out of the DOE weapons labs and they came to us looking for a Standard format that was scalable and could handle you know the kinds of data that they were dealing with and We said well, you know, we're ready to start over so we Invented HDF 5 which was really Part of the ideas we had from the original HDF But also a number of ideas that came out of the labs and other users and lessons learned and so forth so HDF 5 was developed over a couple years originally released in 1998 and I think we really think of that as the flagship HDF at this point HDF 4 is still very widely used By those projects that adopted it in the 90s And in particular the NASA Earth observing system, so it's still there But the real growth is with HDF 5 and we really think that it's the product that everybody ought to be using For those who haven't used HDF before What exactly is HDF stand for? Oh hierarchical data format So does it actually is it a freeform format or is it a it's like this is the way the files laid out? It's a very freeform format the original idea was We didn't know what kinds of data people would be wanting to exchange and share the real motivation at The NCSA, which is the National Center for Supercomputing Applications Was that we had a variety of different computing platforms That scientists were using and they wanted to be able to move their data seamlessly from one platform to another In an architecture independent way So they might have some data that was on a big Indian Machines some other data on a cray some other data on a you know a PC a Mac and so forth and so we developed this format that Describes how the data is is laid out And then we developed a software that can convert from one architecture to another So it's really designed to be an architecture independent format At the same time we were developing it for scientists. So scalability The ability to deal with complexity The ability to run efficiently on a lot of different platforms Those were all very important principles that we were trying to address So that's That's where that came from the hierarchical aspect of it Came from the idea that we wanted to be able to Store a variety of objects and to be organized able to organize them In ways that were meaningful to an application So the original idea was that it would be a hierarchy in fact HDF and HDF file is not Necessarily a strict hierarchy. It can be any graph structure, but we did have this idea that You'll have what we call a group Which would be like a node in a graph Links which would be like the branches in the graphs and then objects which could be nodes or What we call data sets and that's where the actual data go So you can think of an HDF file as a container That has a user defined internal structure for organizing objects The data sets themselves Support a rich variety of data sets a data types. I'm sorry A data set itself is essentially an array One-dimensional two-dimensional, you know End-dimensional array And you can pretty much store anything inside a data set you wanted to So for example, if you wanted to encapsulate a PDF file in HDF you could store that as a byte stream Associate attributes with it that explains that it's a PDF file so forth if you wanted to store a Finite element mesh You could store that say as a big Regular grid or an array so the idea was that You wanted to have a really rich set of data types and then the ability to just describe Those data types and describe the the sort of aggregate or array that Stored those data types Okay, so let me let me let me ask some clarifying questions here So it sounds like you've you know as part of the suite of Tools and and products that you've got there At least part of it isn't is an API that you would you know Compile link into your application and and call functions that store and retrieve data out of out of HDF files What is that inaccurate characterization? Yeah, sure definitely API's when the core API is written in C We've got languages and bindings built on top of that and then tools that layer up on top of that as well Okay, and so and at least part of the target audience here is the scientist or engineer who doesn't really want to screw around with the You know the bits and bytes and how this stuff is stored But they want to be able to write data from a spark for example And then read it on an x86 machine where the Indians are different So the files are kind of self-describing in themselves that when I write an integer value seven There's enough data, you know stored behind the scenes that when I you know If I write that on a spark and and read that on an x86 machine I'll actually get a value seven on that x86 machine even though the internal data Representation between these two machines is different. Is that also accurate? Yes, that's definitely true We we designed the format and the interfaces so that people could exchange their data and have easily translated binary formats like that Exchange well between the different platforms Okay, and I would imagine that since these files are self-described that kind of leads into all the other tools in your suite So you can say oh well, you know I can tell that what's coming up here is 27 integers and I can perhaps visualize that in an interesting way Is that kind of what your your tools do too? Yeah, I think so We have at least a tool a good tool for browsing and Some visualization aspects of HDF five although we tend to leave that out to some of the third-party tools like MATLAB and IDL But the general goal is to have At least the the low-level structure is self-describing enough that people can browse into them and go Oh look, it's an array of 27 integers, but What does that mean to them? Maybe one of the the more difficult things occasionally they have to come up with a data model that says Oh that data set is supposed to be interpreted like this Right, right, okay All right And so and and and you're also hitting on another what I would assume is a key point too that this stuff the actual file formats are Well documented so that third parties can write tools you mentioned, you know MATLAB right there too So, you know, they could just read the file and actually act on it within their MATLAB scripts That's the goal It's not always the case that they're well-described So that's one of the things that we work a lot on With our users is to make sure that for example within a group They all agree on how they're going to organize their data in HDF five So yeah, that is a challenge right the syntax is self-describing But the semantics are challenging and need a good Community data model to really make them meaningful to that community I see what you're saying So even even if you have a file that's nicely self-described if if I'm expecting to read in 27 integers But there's actually three doubles there then we've got a problem, right? Yeah, definitely Okay Another random question that occurred to me while I was listening to your descriptions there So we heard similar things from the Hadoop guys that they say we're very good at unstructured data You know, we put stuff in files and and it can be retrieved any old way later How are you comparable to Hadoop or is that an entirely different thing or am I talking apples and oranges or their similarities here or what? there's probably some similarities, but I have a And I haven't done an enormous amount of background on Hadoop, but It seems to me like Hadoop is a little more from the database Model of things we've got these tables and records in them and it may be a little more unstructured than that It's kind of bags with key value pairs But we we have a lot more Arrayness to the the datum in our data sets. It's it's a particular Structure that is more science and engineering oriented than Hadoop's kind of Random we can put anything in here thing Does that make any sense? Yeah, yeah, no, I I did some But before the show I did some screwing around with HDF 5 and it was quite neat There was a little command that came with the core product called h5 ls and h5 dump And it really is just like there's the root group slash and then you can have group stick Mike was describing them as like nodes on a graph and stuff But for me being a sys admin it looked very much like the Unix file system I had a group that I could put data sets in that looked like files and the group looked like a folder And but it was all internal and they included extra information like were they doubles How many dimensions they were so if I wrote a three-dimensional array it remained a three-dimensional array with very little work And it was very easy to write. I was quite happy with how easy it was Yep, you've discovered the the secret handshake That's we tell people we don't lead off with this is a file system But functionally inside it's a file system It even had from Unix there. Yeah Interesting. What was the motivation for that kind of design? Well, it was it was well known. It was a nice hierarchical design It mapped well to some of the products and projects that we were working on and it Just there was a lot of experience and and and knowledge to draw from in the file system design community and it and we could Specialize it enough into the science and engineering zone that it seemed to work pretty well Okay, in terms of what you were supporting you said the core language is written in C But you had bindings for others. I noticed the core package had Fortran and a C++ Set up Is there anything else out there? There was something I ran across called PY tables It do you support some of these other languages? Do you support cobalt? That's dangerous. Yes, no, but we have an eight of wrapper that we know about well, there you go We have Java bindings that we produce in-house and some prototype Dot-net rappers for things that are very experimental right now. We do support the Java stuff, but not the dot-nets There's Python one of the rappers that's out there is the PY tables one and another one that's called H5 PY and There's Ruby bindings Pearl bindings lots of people have come along and said gosh, that's cool Let's go write a binding for it because the HDF group guys haven't done it yet But we support basically our C C++ Fortran and Java for now So question about your bindings there Are they kind of a one-to-one mapping to your C bindings or do you try and have them take advantage of language features? Or you know, how do you how do you manage that stuff? Yes We try to make them as native as possible So But the ones that are third-party, we don't have any controller. You know you give what you get For our cases the C++ is somewhat or object oriented It's pretty reasonable in class oriented. The Fortran is very fortran-y Java has good Object model behind it as well. So we try to be very native to the the particular language and not Not just right rappers sometimes we end up having that and our dot-net Rappers are just that they're just plain old rappers and they don't have any object model to them But the best thing to do is generally to write the object model and that the native programmers and feel at home in that Interface Yeah, and I should add that there's been a lot of interest from the community on high-level language Access to HDF So the h5 pi is an example of that and We actually have a little wiki that we set up to discuss How we might create certain CAP eyes that would bind better with the sort of high-level view of HDF And that's a direction. We're trying to move into Because we feel that if we can make it really look natural to a pearl or ruby or Python programmer It'll make HDF accessible to a much wider Audience or group of potential users Okay, and you keep referring to to community here is is HDF open source Yes, it is What what license you guys use? BSD type of license okay, and So is this truly a you know an open source collaborative kind of development or are you guys? You know 90% of the development accepting patches. How do you guys work work the project and work with the community? This has been a challenging place for us. We've been It's a funny specialized product, right? So we'd like to have more community involvement, but at the same time I think over the course of our 12 years or so on HDF 5 we've accepted a total of three patches from users So we have lots of people using it, but not many people really want to walk in there and get involved in 250,000 lines of library source code So we were definitely out there, but people have to kind of pick up the ball. So right now we do 99% of the development We seek funding through contracts and grants and other mechanisms and then basically Take those in the directions that the customers from the grants and contracts want or we have some internal Funding that we try to apply in directions. We think are best for the total HDF 5 community You guys do support contracts as well Yes, we do. Yeah, in fact, that's a lot of where our bread and butter comes from So we had the visit visualization on here under show a while ago and They supported many different file formats and so in my exploration in just one week of using HDF 5 The free formness something That was actually really really nice, but like in visit. They'll say okay. We support flash We've had on this show and we support All these other different formats And it turns out those files are all using directly HDF 5 files But like you said, they're they're internally the actual data model for that project could be completely different Yeah, that's one of the things that Sometimes our support contracts work in that direction as we say oh this community really wants to use HDF 5 for storing their data But they they need to come up with standards for how they're gonna Structure their groups and data sets or what attributes they're gonna apply in them and then it comes out as like well, that's a say flash HDF 5 file and then whatever visualization tool has to be Kind of cognizant of that data model in order to do something meaningful with the data that it supplies Yeah, and one other thing in my quick little you know one week of screwing around with it The IO I could do from HDF 5 was actually a higher performing than the stuff. I could write low-level So I was I was quite happy with that. Yeah, it's a special time machine technology. Yes Lots of wonders of middleware, right? I mean that's that's exactly the goal for being able to encapsulate, you know Specific types of expertise into stuff that you the developer don't have to worry about I mean that's kind of it's kind of the goal I mean, I'm an MPI guy and we do that kind of stuff for networking and sounds like these guys do that stuff for file storage that absolutely is you've hit on I think what are Really one of our strongest selling points is and I think your point is right. It's it's because it's middleware We try to do things that other folks would have to do on their own We do it for them. So Yeah, that's right An example of this is right now. We're Just starting a project in the bioinformatics area and this is a community that in the last two or three years has seen an increase in the Amount and complexity of data particularly the amount of Several orders of magnitude and their existing file formats and technologies for managing that data is just breaking down under the weight HDF already has The ability to deal with a lot of the problems that they would Themselves have to create solutions for so in this project. We're Looking for ways to adapt HDF to handle that specific kind of data and it's actually going very quickly and very well So it's a good example of that Well, cool. Let me let me ask something along my natural bias, you know, we've already mentioned. I'm an MPI guy here So how does HDF 5 do you guys interact with MPI at all to use the parallel IO streams? Or how does that stuff work? Right we do and we've been We've been using MPI almost before it was Certain that MPI would survive That was one of the baseline questions was should we try this crazy MPI thing, I don't know if it's going to stick around But yeah, we do have support for collective and independent IO within HDF 5 for doing large data rights to the datasets and we do a lot of Coordination with some of the Department of Energy labs and other large national labs in order to try to get our performance and All the other aspects ease of use Really optimized for the for their users Okay, no, what does that mean? So are you plugged into the back of MPI file read and write or do you actually use MPI? Technology yourself so that you can paralyze what HDF does so are you in the front end or the back end? I guess is kind of what I'm asking. We definitely need to be on the front end We want to leverage MPI to the the maximum Extent we can we don't actually write any networking code. We don't do any parallel file system IO directly intentionally occasionally when there's a badly performant MPI implementation on some particular HPC platform we have to get in there and then start tweaking with MPI info and other sort of little Hints to the file system in order to get things working better But by and large we try to say use MPI make MPI faster and better and we'll take advantage of that Well as you guys have on your website This got me going really really quick and it goes everywhere from the very basic open a file Um, do most people learn that way or is there a full manual? Is that all available or you guys give training or? We do give We do give training. I would say most people start out by working with the tutorial Welcome any feedback that we can get on them Usually That's the way you have tries a few things out. They're looking for a solution of some sort and then When they really get into the Mitty gritty of the problem then it may Be a good time for them to contact us and then we can come out and do a specific training Consulting as Quincy was talking about earlier We really like to work with people who are Haven't yet decided how they're going to use HDF, you know specifically So we help them kind of come up with a data model Very often for example last week Quincy and a couple of others were out at a Navy project where they have How many several different groups doing four different groups and they're all doing different kinds of things But their data needs to be integrated Some are doing simulations or some are actually doing measurements and others doing and other things others are connecting probably HDF data with some database somewhere and By Working with sort of us as people who know HDF and Trying to pull out of them what their use cases are what their needs are What their performance issues are? We kind of are able as a team to come up with the best kind of HDF solution to whatever their problem is So that's that's kind of way it works I would guess that we have no way of really measuring this But I guess that 90% of the HDF users we never hear from Have no idea what they're doing But that's open source We have exactly the same problem in the open MPI project. I get asked this a lot. How many people are using open MPI? It's really hard to say I can tell you how many downloads there have been that's that's about it What's the largest store of data you're aware of like what's the What's the most number of terabytes, you know, somebody has data sitting around in HDF format probably the Earth observing system they've got online about for petabytes They've collected more than that, but they don't keep it all online There may be larger ones well the earthquake people do Terabyte simulations at a time, don't they? Yeah, so the largest single object we know about is Southern California earthquake Center Has a terabyte size Simulations that they do so they'll have one image. That's a terabyte in size And that's actually a very good example. I think of the flexibility and power of HDF In in terms of bringing solutions to say an existing problem they have They I don't know came to us maybe three or four years ago and they had these images that consisted of so your one image consisted of 900 separate files Okay, so Conceptually it was just one great big Actually, there's a three-dimensional image And if the scientist ever wanted to say access some part of that image They'd have to figure out. Okay, which file contains the data that I'm interested in What is the data type of that data? so how can I go in and Pull out exactly the data that I wanted from the various files Put it back together Convert it to the endian-ness of my machine And then maybe do something with it With HDF We were able to Overlay HDF one of the things we didn't mention earlier is that an HDF file is not necessarily a single file a data set within an HDF file could actually have Pieces that are in a lot of different other files so we would create a data set that sits on top of these 900 files and Looks to the application through HDF Just like a big array and they could say okay I want this subset from this array and I wanted in you know 32-bit float And HDF would do all the work for it So it's that kind of thing where HDF its scalability and it's sort of ability to Provide a view that's meaningful to an application is is really valuable Let me ask I also want to mention since we're talking about big things The electron microscopy community is Working with us now and it's actually probably broadening to biomedical imaging generally But they're looking towards images that are going to be 1.6 terabytes in the next year or two So that's where size really matters cool Let me ask you a little bit of a technical question here You were talking about how the different back ends, you know, it's it's transparent to the user They're just doing you know HDF reads and writes and so on. How do you? How do you actually write on the back end? You just use the normal POSIX read and write system calls or is there more more magic underneath? I mean do you have special kernel drivers, or are you just using basically? Whatever the the file system is beneath you Well in other times we try to reside over a Portable layer underneath us so most of the time it's actually a POSIX file system underneath us Occasionally it's MPI or something else But we really try to abstract out the hardware to the extent we can we leverage it But we try not to depend on it for everything so There's a lot of extensions. So there's some new POSIX IO extensions I'd really like to take advantage of and if more people would Standardize those and use them then we could actually start using them in HDF 5 But a lot of our speed is either through MPI or some aggressive caching and other special technology inside the library So when you were saying the file sizes were like 1.6 terabytes. There's actually no Like that's far from the limit that HDF will actually support right? Oh, yeah, we can go we support it basically well the file format is currently Written to use 64-bit offsets and everything and But the file format is actually it's got knobs in there we can tweak it out to Remember what the exact upper limit? I think it was 8 to the 256th power Whatever that is file size Without changing this file format significantly So exabytes now, you know exabytes of exabytes some day Okay, so size is size is not it should not be So what is the relationship between HDF 5 and net CDF? I know there were two separate things, but I see now that net CDF supports HDF 5 Do you kind of clarify those two projects? Yeah, the two projects started out approximately at the same time in the in the late 80s And net CDF actually Came originally from NASA something called CDF a common data format and net CDF was an attempt to make it platform independent and What that meant was a network? Common data format that's where the net came from And their approach was a little bit different from ours and we were really working You know in parallel universes in a sense They came directly from the atmospheric sciences community and they developed a format And the same idea that you know the format would be Something that the user wouldn't think about or worry about But rather they would work through a library in an API and then there would be tools and Their users which were it was really sponsored by the university consortium for atmospheric research Which is an NSF sponsored consortium Wanted to think About their data in the way that they generally thought about it which was that you have some sort of coordinate space and you define the The coordinate variables or the dimensions within that coordinate space for example, you might have latitude longitude and altitude And then all of your data Which they would call variables which would we would call just data sets or arrays Would be defined within that context So net CDF had a had a fairly well defined view of the data and the variables and the aggregates At the same time with HDF what we were doing was listening to scientists from all sorts of different places and They didn't want to be locked into a particular type of view some said well I just want to throw a thousand images into a file and make an animation and others might say well I want to make a you know a Angle mesh of some sort of visualization people or something like that. So we didn't define We didn't define coordinate spaces or anything like that within HDF But not too surprisingly the two formats Had a lot in common, you know, they dealt with they tried to deal with things that were fairly large They tried to deal with the ability to go in and subset take regions out of things store lots of images and and so forth and over the years We talked and at one point actually in the early 90s We talked about maybe merging our two formats But they were just so different that we really couldn't couldn't make that happen our users, you know We had different sets of users and then Towards the end of the 90s and the early 2000s our emphasis particularly with HDF 5 on Scalability and our ability to handle very large numbers of things and very large objects As well as we had built in the ability built in to compress Objects And we had some of the Filters and the kinds of things that Quincy has talked about The ability to to interface with MPI IO was actually a big thing We got back together and we talked about maybe the next generation of net CDF sticking with a very similar data model that they had always used but having HDF 5 under the hood underneath And it's the same thing that that we were talking about earlier that I think Brock mentioned that that's the idea of middleware It does things for you so you don't have to do them themselves so That would mean that the new version of net CDF if it sat on top of HDF 5 It would still look to the users like net CDF But underneath they could say gee I'd like to compress my data or I'd like to use collective IO In this particular parallel system And so that's we got together wrote a proposal to national to NASA and They funded What we called a merge of net CDF and HDF 5. It's not really a merge But in the process The net CDF folks took advantage of some things that were outside of their data model For example the group structure the idea that you can create You know hierarchies and other kinds of graph structures now the way they use groups is somewhat limited And that's actually in my opinion one of the one of the real beauties of net CDF is they have a very clean simple Model so we were talking earlier about how a tool might open HDF and have no idea What was in there because things were just a jumble of stuff well from the net CDF point of view things have to adhere to that model fairly fairly strictly and So if your data Matches that model makes sense with that model the net CDF is is really the kind of interface that one should be using And from our perspective, it's just just another Data model that sits on top of HDF 5 So does that that's that explains sort of the the differences in the similarities? Yeah, no that that that definitely covers it that they're trying to do something That's very specific to their group and you were very generic. So they are now Using HDF 5 to provide all that lower level mm-hmm Let me ask a question in a slightly different direction here. What's your your favorites? Are you're the most unexpected or kind of the fun the most fun use you've seen of HDF 5? Maybe not even necessarily for scientific code or something, you know Just completely that you would not have have anticipated perhaps. Yeah Let's say I're talking about this earlier as saying, you know, that's a great question And I'm sure I'm gonna come up with better answers tomorrow and the next day because it's just a really neat thing to think about the first thing that came to the mind to mind for me was We we were hearing from this group in New Zealand. It's funny people. It's a funny weather name And we finally asked them what they were doing with HDF and said well, we're we're making this movie called based on Lord of the Rings and we're using HDF to Simulate fog in the in the movie No, we thought that was wow is that the hunt for golem movie? No, it was the very first one. I think it was at least they were sending us bug reports as they were working on the first Parts of things. Oh, it was the actual movie not not the the the fan created movie. No, no, very good Yeah, yeah So that's one of one of our favorites Quincy. Do you have some well? I mentioned this earlier when we were talking but some guy in Sweden I think it was had was sending us these other other end of questions like how can I make my files smaller and Make the software just a little bit lighter weight and we're trying to help them out and he says eventually He says well see I've got the cell phone application And I'm really trying to store some pictures and images that I'm recording off my cell phone in your using your software on the phone And well, that was a bit weird, too Did he end up doing it is that is that so is that Questions when you fix bugs eventually and he's like, okay, you know, by the way Wow, well open source. There you go. Yeah All right, as a as a developer myself I have to I have a standard question that I have to ask all other software projects. What version control Software do you guys use? We use we use subversion Which we transitioned off CVS Three years ago or so Because it was really very limiting and actually I wanted to pass along a thanks to you and the other parts of the opnm PI team because we just blatantly stole your release methodology document And I'm based there kind of reworking how we're gonna do our release methodology on some of the ideas you have there So there's some trade-off in the open source community as well But oh, that's great. I'm glad that you found it useful again Using using other people's projects for things that were completely unexpected. That's that's great. That's what this stuff is for Yeah Okay, guys, so we're gonna go ahead and wrap it up now Where is the best place for people to get information on HDF and where can they download it? You have like a website or a mailing list or how can they get a hold of you? Yeah HDF group dot org That's the website And then we have a Help desk with an email Address That's just help at HDF group dot org And then there's a forum HDF forum Quincy, how do we sign up? Well, I would go into the website and find the right user support link there and there's there's Thanks to get done to the mailing list as well as download stuff and get over to the wiki and what kinds of difference But that's easiest entry point Okay, and is the mailing list the best way to get Get involved with the project like if you did have like like a quick patch for like a found bug or something Just go through the mailing list. You want to be patch number four for you know, HDF five. Yes I want to say a little bit about that. I mean when we spun off from the university You know, we had no idea what I meant to start a company especially a nonprofit company and and so forth and but but one of our real You know strong Desires and it's really a part of our mission is to make our company strong enough and stable enough That we can have the extra resources to engage the wiser community in it in more effectively than we've been able to do You know, we've kind of had our heads down doing our job Just trying to survive but as as we become I think more fiscally sound We do want to try to encourage greater community involvement in things like well everything but Patches for example and and those sorts of things but those take a fair amount of resources just to manage particularly since Many of our users really need this product to be very robust and very heavily tested so if we do take a patch it has to be somebody who's willing to do a lot of testing and And adhere to a lot of requirements. I just want to throw that in. Yeah, there's a reason why we've only accepted three patches Understood. Yeah. Yeah, I'm sorry wasn't trying to be snide there I know no no wasn't taking difficulty of taking a patch from the wild You know works for me is is not always the best reason but sometimes you do get unexpected little, you know Gems in the rough. Oh Absolutely, that's great stuff Okay, well, thanks a lot guys for taking some time out with us If you have any questions, you know, just please let us know this will be ready soon Okay, great. Thank you very much. Yeah, thanks for having your time guys. Thank you. No problem. Bye