Thank you, Sunil. Good morning everyone. I want to congratulate you on yesterday's T20 win against England. I was rooting for you. Our chairman in India told me to wear blue to support the India team. This gets into the keynote: we're talking about AI, digital twins, simulation, and the industrial metaverse. Now we're at industrial AI. I asked a large language model who would win the World Cup; it said India and New Zealand, with a 50% probability, then 60-40 on Sunday. I'll discuss industrial AI and how it changes the physical world: mobility, trains, factories, life sciences, semiconductor plants, intelligent infrastructure. India has a massive growth opportunity at 7% GDP growth. India will gain and contribute the most. I'll cover: the AI revolution in industry, why India has a unique position to benefit, and how much operations can improve. AI without data is nothing. There are 20 billion smart devices, generating up to a terabyte of data per hour in a factory, but 80% is unused. At Siemens, we combine real and digital worlds. Examples: Audi uses AI for spot welding quality, reducing testing and saving time and money. In water infrastructure, we cut losses by half using sensors. In buildings, we developed Comfort AI, reducing energy costs by a third. Industrial AI must be safe, secure, reliable, and trustworthy. Unlike consumer AI, it can't hallucinate. India is a major force in applying AI across industries. 80% of Indian enterprises already use AI. There's an adoption gap, but India's educated workforce will use AI the most. If GDP share of manufacturing goes from 15% to 25%, and we make it AI-native, India can leapfrog. Example: our Bangalore team developed an application for an oil and gas customer in a desert, using satellite images and weather data to predict sandstorms with 70% accuracy seven days ahead, saving 20% in costs. The Siemens Xcelerator platform makes technology available for industrial use cases. It's an open digital platform with hardware and software. We have nine partners in the exhibition. Siemens connects real and digital worlds. Every third machine in the world is controlled by a Siemens controller. We are the number one industrial software company with $11 billion in digital business, the 16th largest software company. Industrial AI needs domain data, not internet data. We have 300 petabytes of data but need more. We work with ecosystems and data alliances. We partner with Nvidia for GPU acceleration. Examples: digital reality viewer and digital twin composer for faster simulation. We need to scale from pilot to production, industry by industry. Welcome to the stage Vishal of Nvidia and Sanjit of Adverb Technologies.
Sunil set the stage. Manufacturing needs to be a significant proportion of GDP. The government is clear on that. Siemens and Nvidia can help you scale in software-defined, AI-native factories. Three things happening simultaneously: greenfield projects at scale where you can build a perfect virtual copy, reducing costs by 10-20%, increasing output by 20%, and capturing 90% of mistakes virtually. Second, PLI momentum of over $20 billion has generated 1.2 million jobs. Third, the AI flywheel through public-private partnership to build AI brains. When 16 million MSMEs get that AI brain, combined, India can become the architect for the industrial metaverse.
Wow. Okay. So 10 to 20% faster, more productive, 90% capturing failure rates earlier.
That's in virtual times. Now Sanjit, tell us about Adverb, what you've founded, created, and how those numbers reflect on using Siemens and Nvidia technology.
Adverb is a robotics company automating warehouses and factories. Started 10 years ago, now India's largest and one of the world's fastest-growing robotics companies. We build mobile robots, cobots, quadrupeds, and recently launched a humanoid. All for industrial and defense. Without Siemens and Nvidia technology, it's not possible. Since 2018, everything we design—mechanical, electrical, electronics—happens on Siemens platform. We use Teamcenter for product lifecycle management, Plant Simulation, and Tecnomatix to show customers solutions. We do 'what if' analysis in simulation, reducing real-world challenges. For Nvidia, we train models on their simulation platform for robot locomotion on different terrains, then transfer policies to reduce sim-to-real gap. Without these platforms, we can't build reliable products.
Great, thank you Sanjit. Fastest-growing robotics company. Now Vishal, you mentioned unlocking power for next-generation manufacturing. How do we do that in India? What are the challenges and how can we overcome them?
Siemens and Nvidia are building an industrial AI operating system. India can reimagine factories, optimize, control supply chains. Example: Reliance New Energy gigafactory is being built virtually without breaking ground, reducing design cycle time. We are building 12 new industrial cities; they need an AI-native operating system. Energy needs real-time virtual scenarios for renewable integration. In Pune, an AI lab does crash analysis for EV packs. It means AI moving from words to atoms, being grounded, connected, and scalable. That's India's advantage.
Fantastic, great examples. To conclude, Sanjit, you've built quadrupeds and mobile robots. Tell us where you see industries and which markets are important as you go from India to the world.
India is very important. We started to help Indian companies become more productive so they can scale globally. 40% of revenue comes from India and will continue in that range. We export robots to 25 countries with subsidiaries in US, Europe, Australia, Singapore. Dream to reach 100 countries in 10 years. We build robots for different applications. Reliance New Energy is a 20 GW solar factory; there are 11 similar customers. Electronics: 25% of Apple's mobile phones are manufactured in India, and companies like Tata Electronics and Foxconn are customers. Geopolitically, every country wants these industries. Our experience automating India at scale at competitive prices will serve global customers.
Thank you so much, Sanjit. Thank you so much, Vishal, for joining us on stage.
You can't go. We need to ask you a question too. How can it be only one-way traffic? We got Peter, we're fortunate he sees everything globally. What are one or two lessons you've seen across the world that India should be sensitive about?
What we've seen is many proof of concepts that don't scale. The key is to get to scale. You have to do it first customer backwards, industry by industry. Understand the key use cases per industry—electronics, battery manufacturing, automotive—and build applications that can scale, otherwise it's just another proof of concept.
That's so good. Go beyond proofs of concept to implementation. If our country became a shining star with less than 1% developers from total population, imagine each of you now is a developer. You can speak to the computer in your language, mix languages, the computer understands, program it, go from proof to production and make India really smart.
That's fantastic. Great summary. Very good. Thank you so much. Thank you.
Okay. Okay. We take a quick picture. I understand. Okay. Good.
