NVIDIA Leads the European Digital Revolution from Paris

NVIDIA Leads the European Digital Revolution from Paris

The Power of Tokens in the New Era of Artificial Intelligence

Tokens as Engines of Transformation

NVIDIA’s presentation at GTC Paris opened with a powerful metaphor: tokens as the new fundamental units of knowledge and artificial intelligence. Far from being just fragments of language, these tokens—words, images, data, and code—represent the machine’s ability to perceive, analyze, reason, and transform the world.

Jensen Huang, founder and CEO of NVIDIA, described these tokens as elements capable of “probing the depths of the Earth, detecting disease before it manifests, and guiding future explorers.” Their impact goes far beyond computing, becoming tools with broad scientific, medical, and social applications.

Tokens. Source: Nvidia

Unlike the bits and bytes of the traditional digital era, tokens symbolize meaning, context, and purpose, enabling machines to move from processing data to understanding the world. This evolution is the foundation of a new era of AI that relies on intelligent interpretation and autonomous action.

Real-World Applications in Medicine, Physics, and Exploration

The functionality of tokens extends to diverse domains such as precision medicine, where they can anticipate diseases before symptoms arise; planetary exploration, where they guide scientific missions through image analysis; and computational physics, where they help uncover new laws and natural patterns.

With this conceptual foundation, NVIDIA states that every field of knowledge can be transformed by the proper use of these blocks of intelligence. From hospitals to observatories, and from material science labs to data centers, token-based AI is redefining what’s possible.

These units also allow developers to generate more adaptive solutions, train models with advanced generative capabilities, and establish real-time links between data, decisions, and results. Ultimately, tokens represent a new frontier not only for technology, but also for humanity.

Grace Blackwell and the New Supercomputing Architecture

A Masterpiece of Engineering

On the Parisian stage, NVIDIA unveiled its latest milestone in supercomputing: the Grace Blackwell system (GB200). This architecture represents a monumental leap in power, efficiency, and scalability. With more than 1.2 million components, 200 billion transistors, and weighing nearly 2 tons, the GB200 is not just a technological marvel but also a bold statement of intent.

The system, built with a $40 billion R&D investment, is designed to think, reason, and plan. Unlike previous generations, Grace Blackwell doesn’t just execute instructions—it talks to itself, making it a truly thinking machine, optimized for inference tasks, simulation, and training of advanced models.

Scalability with NVLink and MVLink

One of the key achievements of this new architecture is its scaling capability. Thanks to technologies like NVLink and MVLink, 144 Blackwell chips have been interconnected without bottlenecks, reaching an astounding 130 TB/s of bandwidth—more than the world’s peak internet traffic.

These advancements enable the creation of GPU networks that operate as a single logical unit, maintaining synchronization and extreme performance. The result is an environment where each component contributes to a distributed, coordinated, ultra-fast intelligence.

The combination of compute power, interconnectivity, and energy efficiency positions Grace Blackwell as the technological foundation for token factories, large-scale simulations, and agentic AI systems.

Massive Simulation for the Real World

The paradigm shift proposed by NVIDIA goes beyond hardware. With GB200, simulation becomes a core component of the innovation cycle. It’s no longer just about rendering graphics, but about simulating the real world with photonic and physical precision.

Each system can run simulations of industrial, physical, and biological processes before building anything in the real world. This capability is the essence of digital twins: virtual representations that allow experimentation, optimization, and validation without real-world risks or costs.

From nuclear fusion to automated supply chains, Grace Blackwell enables real-time design, training, and deployment of the future.

From CUDA to CUDAQ: The Leap to Quantum Computing

Google and NVIDIA Achieve the First Logical Qubit

One of the most groundbreaking announcements at GTC Paris was the joint achievement by NVIDIA and Google: the creation of the world’s first functional logical qubit, revealed in 2023. This milestone marks the dawn of a new era in quantum computing, where errors can be corrected, and true scalability becomes possible.

This breakthrough accelerated the development of CUDAQ, a suite of libraries that extends the power of CUDA into the quantum realm. CUDAQ enables the execution of hybrid quantum-classical algorithms, integrating QPU (Quantum Processing Units) with high-performance GPU systems.

Thanks to this technology, researchers can simulate qubits and design complex quantum algorithms even before fully operational quantum computers become available. It is a bridge between today’s computing and a quantum-powered future.

NVIDIA CUDA-Q. Source: Nvidia

Europe as the Epicenter of Quantum Computing

NVIDIA emphasized Europe’s strategic role in the quantum shift. With a rich scientific heritage, established supercomputing infrastructure, and a thriving collaborative ecosystem, the continent is well-positioned to lead this transformation.

Supercomputing centers, research institutions, and emerging startups are adopting NVIDIA’s quantum platform to tackle previously unsolvable problems—from material optimization and molecular simulation to advanced financial algorithms.

This strategy is fueling a new wave of scientific and economic growth, driven by technologies that were once only theoretical.

QPU + GPU: The Hybrid Future Is Already Here

NVIDIA’s hybrid approach brings together the best of both worlds: GPUs handle control, error correction, preprocessing, and postprocessing, while QPUs perform the core quantum operations.

This architecture is now available to developers through Grace Blackwell, enabling applications to be tested and executed even before quantum hardware is widely deployed. Once quantum computers arrive, the code will already be ready to run.

The result is a futuristic computing platform that democratizes quantum power, accelerates research, and opens the door to unimaginable innovation.

Agentic Artificial Intelligence and Digital Twins

From Perception to Autonomous Reasoning

Since its breakthrough in 2012 with the famed AlexNet model, artificial intelligence has gone through several waves: first perceptive AI, capable of recognizing faces, objects, and voices; then generative AI, which creates images, text, or sound. Now, according to NVIDIA, we are entering the age of agentic AI.

This new generation of models can reason, plan, make decisions, and carry out tasks step by step. It no longer just answers a question—it breaks down complex problems into subtasks, selects tools, and collaborates with other agents to achieve a goal.

Agentic AI. Source: Nvidia

Agentic AI relies on advanced language models and accelerated infrastructures like Grace Blackwell, capable of processing millions of tokens per second. These capabilities are paving the way for specialized digital assistants, such as financial planners, concept designers, or operations managers.

Robots Trained in Virtual Worlds

A key element of this advanced AI is the training environment. NVIDIA has developed Omniverse, a platform where robots and agents can learn in realistic simulations governed by the laws of physics.

In these environments, models learn to move, manipulate objects, walk on complex surfaces, and make sensor-based decisions. A prime example is Grek, a humanoid robot trained virtually to walk, adapt to terrain, and even dance—all in response to human instructions.

Thanks to such simulations, agents can be trained with thousands of scenarios before entering the real world, reducing costs, minimizing risks, and accelerating deployment in factories, hospitals, and homes.

Omniverse as a Training Platform

The physical and visual fidelity of Omniverse allows the creation of hyper-realistic digital twins of real environments: factories, warehouses, operating rooms, and cities. These digital twins replicate not only appearance, but also the physical properties of objects—such as weight, friction, temperature, and resistance.

Companies like BMW, Toyota, and Mercedes-Benz are already using Omniverse to design, test, and optimize their facilities in real-time, without halting production or making costly changes.

These digital twins are the foundation of the new industrial revolution, where the design and operation of complex systems are virtually modeled before physical implementation.

Token Factories and AI Infrastructure in Europe

Data Centers as Intelligence Factories

One of the most impactful concepts presented by NVIDIA at GTC Paris was that of AI Factories—intelligent token factories. Unlike traditional data centers that simply execute software, these new facilities are designed to continuously and scalably generate intelligence.

Each token produced by these factories represents a unit of knowledge, a piece of reasoning, or an inference made by an AI. This approach turns digital infrastructure into an economic production platform, prompting many countries to consider it as part of their strategic industry.

As Jensen Huang stated, “AI factories will be the critical infrastructure of the 21st century”, comparable to power grids or transportation networks. For this reason, NVIDIA is working with governments and corporations to help build them on a global scale.

New Gigafactories and the European Ecosystem

Europe is positioning itself as a leading hub in this revolution. More than 20 new AI factories and several gigafactories have already been announced across the continent, with the goal of multiplying computing capacity tenfold in just two years.

This expansion is backed by telecom companies, cloud providers, supercomputing centers, and European tech firms, all investing in sovereign infrastructure. The objective is to guarantee technological autonomy and digital independence for the region.

In addition, AI technology centers are being established in seven European countries to strengthen innovation ecosystems, support startups, and foster scientific collaboration.

Key Collaborations: Mistral, Perplexity, and Schneider

Among the most strategic partnerships announced are three standout names:

• Mistral, a European startup working with NVIDIA to build a native European AI cloud, based on open models adapted to regional languages.
• Perplexity, a reasoning-based search engine that will connect regional AI models to deliver answers in users’ local language and cultural context.
• Schneider Electric, which is building fully virtualized AI factories using digital twins for complete digital optimization and energy efficiency.

These collaborations reflect NVIDIA’s commitment to building local ecosystems with global impact, combining European talent, cutting-edge technology, and long-term strategy.

The Industrial and Human Impact of the AI Revolution

AI in Manufacturing, Automotive, and Healthcare

Artificial intelligence is no longer a promise of the future—it is a transformative force already shaping key industries such as advanced manufacturing, autonomous vehicles, and healthcare.

Companies like Siemens are partnering with NVIDIA to merge traditional industrial capabilities with AI technologies, creating smart factories and autonomous systems. In the automotive sector, platforms like NVIDIA Drive enable manufacturers to develop self-driving vehicles with high safety standards using realistic synthetic data generated in Omniverse.

In healthcare, tools like Parabricks and Moni accelerate genomic analysis and medical imaging with pinpoint precision. These solutions allow for faster and more accurate diagnoses, as well as more personalized treatments.

Human Robots Trained with Simulated Physics

One of the boldest ideas at GTC was the rise of human-like robots—physical systems capable of acting autonomously, adapting to their environment, and working alongside humans. Startups around the world are already developing such robots, trained in virtual worlds using high-fidelity physical simulations.

A compelling example is Grek, a humanoid robot trained to walk, adapt to complex surfaces, and even dance, all within a virtual environment. Thanks to simulations developed with Disney Research and DeepMind, these robots learn in the digital realm before interacting with the physical world.

Grew vs Jensen Huang. Source: Nvidia

This method reduces costs, improves safety, and accelerates deployment in industries facing labor shortages, such as logistics, manufacturing, healthcare, and even entertainment.

Europe’s Role in the New Industrial Revolution

Europe is emerging not just as a user, but as a leader of the Fourth Industrial Revolution. With a strong foundation in scientific talent, key partnerships, and technological ambition, the continent is building its own AI infrastructure aligned with its values and needs.

Investments in industrial AI, token factories, quantum computing, and digital twins are creating a new economic fabric. This transformation is not only technological but also social, educational, and cultural, redefining how we work, research, build, and interact.

As Jensen Huang stated in Paris, “Artificial intelligence is now part of national infrastructure,” and Europe is fully committed to leading that future.

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