Published on: March 25, 2025 / update from: March 25, 2025 - Author: Konrad Wolfenstein
NVIDIAS GR00T N1: Strategy for full control of the robotics value chain-Image: Xpert.digital
Strategy for the future: Nvidia's plans for a dominant robotics ecosystem
Exponential growth: How Nvidia benefits from the robotics transformation
With the recent idea of the Foundation model GR00T N1 on the GTC 2025, Nvidia has taken a strategic step to strengthen its position in the robotic sector and to control the entire value chain in the long term. Similar to the successful Cuda strategy in the GPU area, Nvidia creates an ecosystem that is openly but closely linked to its own hardware. The company uses its technological lead and a wide portfolio of products to achieve a market -dominant position. Nvidia's advance takes place at a crucial time when the global robotics market grows exponentially and is expected to achieve a volume of $ 96 billion by 2029.
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The innovation behind Gr00T N1
GR00T N1 is the world's first open, fully adjustable foundation model for humanoid robots. Nvidia presented it at the GTC conference on March 18, 2025 and made it available immediately. It is the first of an entire family of models that will train Nvidia and release worldwide for robotics developers.
Dual-system architecture for human-like cognition
The technological basis of Gr00T N1 is a two -stage system architecture that is modeled on human cognition:
- “System 1” acts as a quick -thinking action model that imitates human reflexes and intuitive reactions. It implements the plans developed by “System 2” into precise, continuous robot movements.
- “System 2” is a slow thinking model for conscious, methodological decision -making. Based on a vision-length model, it analyzes the surroundings and develops plans for robot actions.
This architecture enables the robots to perceive their surroundings, understand instructions and perform complex tasks. In a typical task such as fetching a box from the shelf, system 2 analyzes the scene, understands the request and plans a number of steps, while System 1 takes over the actual execution - it coordinates the walk to the shelf and controls the box for grasping the box.
Generalistic skills and broad applicability
GR00T N1 was developed to cope with general tasks that are essential for humanoid robots. It can easily switch between different activities:
- Grip and move objects with one or both arms
- Handover of objects from one arm to another
- Execution of multi -stage tasks that require long -term context
- Combination of different basic skills for complex tasks
These skills are suitable for numerous areas of application such as material handling, packaging and inspection. In his GTC keynote, CEO Jensen Huang demonstrated a humanoid robot from the manufacturer 1x, which autonomously cleaned up cleaning up in the household-the result of AI training cooperation between 1x and Nvidia.
Nvidia's holistic strategy for the robotics value chain
Nvidia's approach with GR00T N1 follows the successful pattern of the Cuda platform. The company controls the entire value chain from hardware to software and positions GR00T as a potential standard for robot AI.
Controlled “openness” as a strategic advantage
Compared to similar projects such as Google Deepminds Robotic Transformer, to which the complete platform integration is missing, or Tesla's closed Optimus project relies on a more open ecosystem. Similar to Cuda, the company makes central components available to the public, but keeps control of critical elements such as hardware optimization.
This strategy aims to create a sustainable market for Nvidia's chips. Each GR00T-based robot needs powerful Nvidia hardware for both training and operation. At the same time, valuable usage data flow back into the ecosystem.
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Attention: “more open” ecosystem still remains a lock-in business model
The “Lock-in business model” or “Vendor Lock-In” is a strategy in which companies are binding to their products and services by creating an apparently open but actually closed ecosystem.
Nvidia's approach with the GR00T N1 Foundation model follows this pattern. The company creates an ecosystem that appears open but is closely linked to its own hardware. This is similar to the Cuda strategy in the GPU area and aims to control the entire value chain in the robotic sector.
This strategy actually harbors the risk of extensive dependency:
- Technological binding: Users are bound to Nvidia's technology stack, which makes it difficult to switch to competing products.
- Ecosystem trap: The more products and services within the ecosystem are used, the more difficult it is to leave it.
- Investment dependency: Companies that invest in NVIDIAS technology can be forced to stay in the ecosystem due to high change costs.
- Market dominance: By controlling the value chain, Nvidia can achieve a dominant position, which could restrict the competition.
This type of business model is widespread in the technology industry. Companies such as Apple, Amazon and Google have successfully used similar strategies to keep customers in their ecosystems.
While such ecosystems often offer advantages such as seamless integration and improved user experience, it is important to take into account the long -term effects and potential dependencies that you can create.
The core components of the Nvidia robotics ecosystem
NVIDIA has developed a comprehensive portfolio of technologies that together form a closed ecosystem:
1. Hardware: powerful chips for training and operation of GR00T-based robots; Jetson Thor especially for humanoid robots
2. Software: The GR00T N1 Foundation model with its dual system architecture forms the core
3. Development tools:
- Isaac Gr00T Blueprint for synthetic data generation
- Newton, an open source physics engine, developed with Google Deepmind and Disney Research
- Omnive platform for simulations and digital twins
4. Data ecosystem: Massive data generation for training and data backflow of robots in use
Market effects and economic importance
The robotics industry is facing unprecedented growth. The market volume was around $ 46 billion in 2024 and is expected to grow to around $ 96 billion by 2029, which corresponds to an annual growth of +16%.
Transformative effect on the robotic sector
Nvidia CEO Jensen Huang describes the introduction of GR00T N1 as the beginning of the “age of generalist robotics”. This assessment is supported by industrial partners. Bernt Børnich, CEO of 1x Technologies, emphasizes: "The future of humanoids lies in adaptability and learning. With minimal post-training session, we have fully implemented on Neo Gamma."
Jonathan Hurst, co -founder of Agility Robotics, sees a “turning point in history where human -oriented robots like Digit will change the world of work forever”. These statements underline the transformation potential that the leading companies in the industry see in Gr00T N1.
Strategic partnerships as a key to success
NVIDIA has built up a wide network of partnerships with leading robotics manufacturers:
- Humanoid specialist: 1x technologies, agility robotics, boston dynamics, neura robotics
- Industrial robot manufacturers: Universal Robots, Franka Robotics
- Logistics-focused partner: As part of the “Mega” project, Nvidia is working on solutions for warehouse automation
These partnerships strengthen Nvidia's influence on the entire value chain and create an ecosystem in which Nvidia technology becomes standard.
Regulatory challenges and competitive concerns
Nvidia's growing dominance in the AI and Robotic sector has attracted the attention of regulatory authorities worldwide.
Antitrust investigations in the USA and China
The U.S. Ministry of Justice has initiated a antitrust investigation against Nvidia. The authorities are concerned that NVIDIA could make it difficult to switch to competition and that customers who only use Nvidia technology may receive better conditions.
In China, Nvidia is also under competition law examination and could be fined up to a billion US dollars. Despite these regulatory challenges, the company continues its expansion course in China, especially in the area of autonomous vehicles.
Market concentration and competition concerns
With a share of about 80% in the global AI chip market, Nvidia's market power is considerable. The strategy of gaining control of the robotics value chain through GR00T N1 and the associated ecosystem could cause similar competitive concerns.
Nvidia's current strategy with GR00T N1 could be seen as an attempt to establish a similar dominance in the robotic sector, as is already the case in the area of AI chips. The regulatory reactions to this expansion will be crucial for the future development of the market.
Future prospects and market development
The development of humanoid robots accelerates rapidly. By 2026, the first humanoid robots in private households could help with tasks such as laundry, vacuuming and dishwashing. By 2040 there could be up to 10 billion of such robots in all economic sectors worldwide.
Competition landscape and innovation dynamics
The competitive landscape in humanoid robotics includes established technology companies and specialized startups:
- USA: Tesla (Optimus), Boston Dynamics (Atlas), Figure AI (Figure 02), Agility Robotics (Digit)
- China: Unitree (H1, G1), Ubtech Robotics (Walker S), Agibot (Yuanzheng A2)
- Europe: Neura Robotics from Germany as an important innovator
In this competitive environment, Nvidia is not positioned as a direct competitor of the robot manufacturers, but as a provider of the basic technologies on which the next generation of robots will build up.
GR00T N1 as a bridge for industry development
By providing a pre-trained, customizable foundation model, Nvidia lowers the entry barrier for new actors and accelerates the development of humanid robots. This democratization of the technology could lead to an explosion of new applications and use cases.
At the same time, NVIDIA secures a strategic advantage and long-term income from the growth of the sector with its hardware infrastructure due to the close integration of GR00T N1.
Nvidia on the way to the market dominance
Nvidia's strategy with GR00T N1 is an ambitious advance to control the entire robotics value chain. By combining an open but hardware -bound model with a comprehensive ecosystem of development tools and partnerships, the company positions itself as a central player in the next phase of robotics development.
This strategy follows the successful Cuda pattern, in which Nvidia has achieved a sustainable competitive advantage through the control of critical technology components. The success of this strategy in the robotic sector will depend on several factors: the technical superiority of GR00T N1, the development of the overall market for humanoid robots and, last but not least, the regulatory reaction to Nvidia's growing market power.
The next few years will show whether NVIDIA with GR00T N1 can actually control the entire value chain of robotics, or whether regulatory interventions and competitive dynamics will promote a more balanced market development.
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