What Companies Has Nvidia Invested In? A Look at Key Sectors

Nvidia has grown beyond its origins as a graphics chip company, becoming a dominant force in artificial intelligence, data centers, and autonomous systems. To maintain its edge, the company strategically invests in startups and established firms that align with its long-term vision. These investments expand Nvidia’s influence and accelerate innovation in key industries.

Examining Nvidia’s investment strategy reveals the sectors it prioritizes for future growth.

AI Startups

Nvidia has aggressively backed artificial intelligence startups advancing machine learning, natural language processing, and generative AI. One of its most notable investments is Cohere, which develops large language models for enterprise applications. Unlike consumer-focused AI, Cohere’s models help businesses automate customer service, analyze documents, and manage internal knowledge.

Another major investment is Hugging Face, a platform central to AI model development and collaboration. By supporting Hugging Face, Nvidia ensures developers have access to optimized hardware and software tools for training and deploying models, reinforcing its GPUs as the preferred choice for AI workloads.

Nvidia has also invested in AI-driven drug discovery, backing Recursion Pharmaceuticals, which uses deep learning to analyze biological datasets and accelerate treatment identification. This highlights Nvidia’s interest in AI applications beyond traditional tech, particularly in industries where computational power can drive breakthroughs.

Autonomous Vehicle Ventures

Nvidia has positioned itself as a key player in self-driving technology by investing in companies specializing in advanced driver-assistance systems, sensor technology, and autonomous vehicle platforms. One of its most significant investments is TuSimple, which develops AI-powered perception systems for automating freight transportation. By integrating high-performance computing, TuSimple aims to improve the safety and efficiency of long-haul trucking.

The company has also invested in Waabi, a startup developing AI-driven simulation technology for training self-driving systems. Unlike traditional approaches reliant on real-world testing, Waabi’s models enable rapid iteration in virtual environments, reducing the time and cost of refining autonomous driving algorithms.

Beyond startups, Nvidia has partnered with automotive manufacturers like Mercedes-Benz to integrate AI-powered driving features into future models. By investing in both emerging companies and established automakers, Nvidia ensures its technology remains central to the evolving transportation industry.

Data Center Infrastructure

Nvidia’s investments in data center infrastructure reflect its ambition to dominate high-performance computing, cloud services, and enterprise AI workloads. As demand for accelerated computing grows, the company has backed firms that enhance efficiency, scalability, and energy optimization.

One such investment is CoreWeave, a specialized cloud provider offering GPU-accelerated computing for AI, visual effects, and scientific research. Supporting CoreWeave strengthens Nvidia’s foothold in the cloud GPU rental market, ensuring businesses can access high-powered computing without on-premises hardware.

To address data center bottlenecks, Nvidia has invested in networking and interconnect technologies, including Fungible, which develops data processing units. These offload networking, storage, and security tasks from traditional CPUs, reducing latency and improving system efficiency.

Storage solutions are another focus, as AI and analytics workloads generate massive datasets requiring fast access. Nvidia’s investment in WekaIO, a provider of high-performance cloud storage, ensures enterprises can scale seamlessly for machine learning and financial modeling without storage slowdowns.

Robotics and Automation

Nvidia’s investments in robotics and automation focus on AI-driven machines operating in complex environments across manufacturing, logistics, and healthcare. One such investment is Covariant, which develops deep-learning-powered warehouse automation. Unlike traditional programmed robots, Covariant’s systems continuously learn from their surroundings, improving their ability to handle unpredictable tasks like sorting and picking items of varying shapes and sizes.

In industrial robotics, Nvidia has backed Veo Robotics, which enhances workplace safety by integrating real-time AI perception systems. This allows robots to work alongside humans without physical barriers, increasing efficiency in manufacturing.

In healthcare, Nvidia has invested in Vicarious Surgical, which combines advanced computer vision with robotic manipulation to improve surgical outcomes while minimizing invasiveness.

Gaming and Visual Computing

Nvidia’s roots in graphics processing continue to shape its investment strategy, particularly in companies advancing gaming technology and real-time rendering. While it dominates the GPU market with its GeForce and RTX series, it also invests in firms enhancing gaming experiences through AI, cloud gaming, and content creation tools.

One notable investment is Inworld AI, which develops AI-powered non-playable characters that interact dynamically with players. Using machine learning, these NPCs generate unique dialogue and adapt to player behavior, making in-game interactions more immersive.

Beyond AI-driven gaming enhancements, Nvidia has backed companies focused on game development infrastructure. Its investment in Improbable, which specializes in large-scale multiplayer simulation technology, supports the creation of expansive virtual worlds with thousands of concurrent players. This aligns with Nvidia’s push for high-performance cloud gaming solutions.

Cloud-Focused Entities

As cloud computing reshapes enterprise IT and AI workloads, Nvidia has invested in companies enhancing cloud-based GPU acceleration and AI model deployment. By supporting firms specializing in cloud-native infrastructure, Nvidia ensures its technology remains integral to businesses shifting from traditional data centers to scalable, on-demand computing environments.

Lambda Labs, a cloud provider focused on AI training and inference, offers GPU-powered instances tailored for machine learning workloads. Nvidia’s backing of Lambda aligns with its broader strategy of making AI development more accessible through cloud-based solutions.

Another key investment is Run:ai, which optimizes GPU resource allocation in cloud environments. Its orchestration platform maximizes GPU utilization, reducing costs while improving efficiency in AI training and inference tasks.