1. The ChatGPT Moment Has Arrived for Physical AI

In January 2026, at CES 2026—the world’s largest technology trade show held in Las Vegas—NVIDIA CEO Jensen Huang declared in his keynote address, “The ChatGPT moment for robotics is here,” officially signaling the start of the Physical AI era.

(Source: NVIDIA)

This statement is not a rhetorical expression, simply pointing to progress in robotics. It reflects a shift in AI itself—from generating text and images to becoming “intellectual in action” that understands the laws of physics, perceives the complex real world, and performs physical tasks through robotic bodies. If robots in the past were automated machines that followed preprogrammed activities, robots in the Physical AI era are autonomous agents that learn, reason, and adapt to unexpected situations.

Superb AI stands at the center of this major technological shift. Introduced at CES 2026 as one of NVIDIA’s key Physical AI partners, Superb AI provides the core Vision AI technologies that enable Physical AI to “see” the world properly and make the right judgments. Working within NVIDIA’s ecosystem alongside robot makers and enterprise software companies, Superb AI serves as a bridge that brings AI beyond the lab and into industrial sites and everyday life.

In this post, we take a deep dive into NVIDIA’s Physical AI strategy announced at CES 2026 and provide a comprehensive look at the essence of Physical AI as defined by Superb AI, its core technologies, and its ecosystem expansion strategy through global partnerships. We also examine real-world industrial applications to offer a concrete view of the future changes Physical AI will bring.

2. A Deep Dive Into the Physical AI Ecosystem: NVIDIA’s Blueprint and Key Components

2.1 The Structure of NVIDIA’s Physical AI Ecosystem

To foster the Physical AI ecosystem, NVIDIA operates its startup program, NVIDIA Inception. At CES 2026, Les Karpas, global head of Physical AI at NVIDIA Inception, unveiled the key partners expected to lead the Physical AI era. This ecosystem suggests that Physical AI cannot be realized by a single company alone—it is a system in which hardware, AI (the “Brain”), and solutions that bring AI into industry must come together as an integrated whole.

NVIDIA’s ecosystem map can be broadly divided into three core areas—hardware, AI, and solutions—and each area operates in close interdependence.

2.1.1 Hardware: The Body, the Senses, and Computing

This is the domain that forms the physical foundation of Physical AI. Sensors serve as the robot’s “sense organs” on top of the “body” built by robot makers, while edge computing supports real-time processing.

• Robot Makers: The most visible layer of the ecosystem, responsible for the physical body that carries out Physical AI’s actions. At CES 2026, robots of various form factors were showcased, including those from Boston Dynamics, Hyundai Motor Group Robotics Lab, and Unitree. These included humanoids designed to mimic humans, autonomous mobile robots (AMRs) for logistics sites, and collaborative robots that work alongside people.
• Sensor Makers: Provide hardware such as cameras, LiDAR, and radar that allow robots to perceive the external environment. This serves as the first gateway through which robots acquire environmental information.
• Embedded Computing: High-performance computing modules that enable robots to process massive volumes of collected data on-site in real time. Robot makers deploy modules such as NVIDIA’s Jetson Thor to control behavior and make low-latency decisions.

(Source: Hyundai Motor Group)

2.1.2 AI (Brain): Cognition, Thinking, and Simulation

This is the core software and model layer that brings intelligence to hardware. It is the domain Superb AI belongs to—enabling robots to understand the world, learn, and plan optimal actions.

• Vision AI (Visual Intelligence): The field that gives robots the “eyes” to see the world and the ability to interpret what they see—and where Superb AI is positioned as NVIDIA’s key partner. Superb AI processes visual data collected by robots, maximizes AI training efficiency through auto-labeling and curation, and supports higher-level cognition that understands the context of a situation.

(Example video where objects are detected in real time and logged in seconds by Superb AI’s model — CS WIND case)

• AI for Action Planning & Robot Control: The layer that determines a robot’s actual movements. Using large language models (LLMs) and vision-language models (VLMs), it breaks down abstract natural-language commands—such as “Bring me coffee”—into concrete subtasks. This enables robots to plan action sequences logically even in complex environments, and be controlled precisely in real time.
• Simulation & Software: The layer used to train and validate robots in virtual environments. Using NVIDIA Omniverse and Isaac Sim, teams build physics-based virtual worlds (Digital Twins) to reduce trial and error in the real world.

2.1.3 Solution: Industrial Integration and Services

This is the infrastructure and services layer that helps integrate Physical AI into real business environments and operate it at scale.

• Solution and Service Providers: Includes companies such as Accenture and Deloitte, which build Physical AI adoption strategies and implement systems tailored to each customer’s business challenges.
• Enterprise Software: Companies such as Microsoft, SAP, and Siemens connect robots to factory production management systems (MES) and enterprise resource planning (ERP) systems. This ensures robots do not operate in isolation, but instead support seamless data flow across the enterprise workflow.

3. Superb AI’s Core Capabilities: Why It Earned a Place in NVIDIA’s Ecosystem

In the NVIDIA ecosystem map above, Superb AI is positioned as a key partner in the Vision AI domain. That is because, as Physical AI evolves beyond simple automation into a complete agent capable of Cognition, Thinking, and Action, Superb AI’s technologies became essential.

Within NVIDIA’s ecosystem, Superb AI’s technical roles include the following:

3.1 Complete Cognition: 3D Spatial Intelligence and MTMC

For robots to operate in the real world, they must understand both the structure of the space they are in and the objects they need to handle—in three dimensions. Superb AI extracts accurate 3D information across both dimensions using only standard 2D camera footage, without relying on expensive 3D sensors.

• 3D Spatial Intelligence and 3D Reconstruction (Digital Twin): Even with 2D camera footage alone, Superb AI can reconstruct the 3D geometry of a space so robots can understand their operating environment and act accordingly—for example, avoiding obstacles along a driving route. It also precisely estimates the 3D shape and depth of individual objects so robots can handle items in front of them accurately. This is essential for calculating the correct gripping angle based on an object’s shape and manipulating it delicately without losing the target. (3D reconstruction video)
  
• MTMC (Multi-Target Multi-Camera Tracking): Going beyond the limitations of a single camera, MTMC integrates data from dozens of cameras installed across a site to track multiple targets simultaneously. Even with blind spots or lighting changes, it maintains uninterrupted tracking without losing objects—delivering standout performance for wide-area monitoring environments such as smart factories and city-scale surveillance.

3.2 Intellectual in Action: Context-Aware Agentic AI

For Physical AI to work like humans in the field, it must go beyond recognizing objects. It needs to understand context, synthesize complex signals, and make optimal judgments.

• Instant Intent Understanding with the Vision Foundation Model, ZERO: Superb AI’s proprietary vision foundation model, ZERO, can immediately understand and execute user intent. Even for objects it has not been trained on, users can simply type a text prompt such as “Find damaged boxes,” and ZERO will detect and locate the target on the spot (zero-shot detection). ZERO delivers outstanding performance across diverse domains such as manufacturing, logistics, and security without additional fine-tuning, and it has proven its competitiveness through multiple awards—including a runner-up finish at a CVPR 2025 challenge, one of the world’s largest Vision AI conferences. This dramatically removes the inefficiency of having to retrain AI models repeatedly in industrial environments where conditions change constantly. (More on ZERO)
  
• Complex Reasoning and Control with Agentic AI: Real-world problems cannot be solved with a single AI model alone. Superb AI builds an agentic AI system in which detection, vision-language understanding (VLM), control, and comparison models for compliance with regulations and procedures work together as an integrated whole. When a target is hard to see, the AI can decide on its own to move a robot arm or control the camera zoom and angle to secure the best view. It can also compare against historical records in a database (DB) or reference a company’s standard operating procedures (SOP) to infer and judge, holistically, whether “the worker is following the required procedure.”

3.3 Turning Video Into Actionable Data: Video Search and Summarization (VSS)

Traditional VMS systems typically store footage for a fixed retention period—such as “the last 90 days”—without structure, forcing teams to manually review thousands of hours of recordings when an incident occurs. Superb AI’s technology transforms this workflow in two steps, maximizing the usability of video data.

• Captioning, Summarizing, and Storing: AI analyzes CCTV footage in real time and stores text-based descriptions and summaries of what is happening—for example, “A worker is moving while wearing a safety helmet,” or “A forklift is exceeding the speed limit.” Instead of saving meaningless static frames, it builds a meaningful database centered on key events in advance. (VSS demo video)
  
• Efficient, Precise Search through Natural Language: When a user simply asks, “Find forklift speeding scenes from last week,” the system instantly retrieves the exact matching clips from the summarized database. This allows managers to confirm the moment they need with a single search—without digging through massive volumes of video—and quickly gain operational insights.

4. Superb AI and NVIDIA: Maximizing Technical Synergy

If NVIDIA is an “infrastructure company” that provides powerful hardware (GPUs) and a general-purpose AI software platform, Superb AI is a key partner that packages these capabilities into application solutions that B2B customers can adopt immediately. Applying NVIDIA’s advanced technologies to real industrial environments involves high technical barriers, and Superb AI fills that gap—creating complementary, end-to-end synergy. By deeply integrating NVIDIA’s four core technology stacks into the Superb Platform, Superb AI delivers the following value.

4.1 NVIDIA Isaac Sim: Real-World Data, Built in Virtual Environments

Collecting training data for robots in the real world is not only expensive, but also limited by the need to recreate high-risk scenarios such as fires or collisions. Superb AI addresses this challenge using synthetic data powered by NVIDIA Isaac Sim.

• Overcoming the Challenges of Edge Cases: Rare defect or accident data—occurring in less than 1% of real-world situations—can be generated at scale in a virtual environment. Within Isaac Sim, physical variables such as lighting, weather, and obstacle placement can be adjusted freely, enabling AI training under conditions even harsher than reality.
• Building a Data Flywheel: Superb AI goes beyond generating data by connecting it with its data curation technology. From tens of thousands of simulated images, AI selects only the data with the highest training value. In the other direction, it analyzes data collected in real operations to refine and upgrade virtual scenarios—establishing a complete, self-reinforcing feedback loop.

4.2 NVIDIA Cosmos: A Robot Brain That Understands the Laws of Physics

NVIDIA Cosmos is not a single model, but rather a family of foundation models designed for various purposes. It includes specialized models such as Cosmos WFM (World Foundation Model), which understands physical-world dynamics, and Cosmos Reason, which infers causal relationships in complex situations. Superb AI optimizes these models for each customer’s real business environment.

• Using Specialized Models Where They Fit Best: NVIDIA offers a lineup of models tailored for specific functions, such as physical-law prediction and logical reasoning. Superb AI selects the most suitable Cosmos model based on the customer’s specific challenge (e.g., precision assembly, risk prediction) and integrates it into the solution.
• Efficient Fine-Tuning through Data Selection and MLOps: Foundation models cannot be expected to fully capture the unique data characteristics of every industrial site. Superb AI uses its MLOps platform and advanced data selection to extract only the core data that is essential to improving model performance. This enables rapid, efficient fine-tuning of Cosmos models with minimal data and resources—delivering a dedicated AI system tailored to each customer’s site.

4.3 NVIDIA Metropolis & MTMC: Seamless Tracking and Scalability

NVIDIA Metropolis sets a standard for Edge-to-Cloud architecture and application frameworks designed to process massive volumes of video data efficiently. Superb AI has independently developed a high-performance video monitoring solution that aligns closely with this architectural philosophy.

• Edge-to-Cloud Flexibility: Like the structure Metropolis pursues, Superb AI’s solution is designed to ingest large-scale real-time video streams, run inference with multiple AI models simultaneously, and generate immediate insights from the results. Because of this architectural alignment, security-sensitive data can be processed instantly on on-site Jetson edge devices, while deeper analytics can be connected to the cloud—enabling flexible hybrid operations.
• City-Scale Wide-Area Tracking: Superb AI’s MTMC (Multi-Target Multi-Camera Tracking) maintains continuous IDs for objects (people, vehicles, robots) by linking footage from nearby cameras even when a target leaves a single camera’s field of view. In particular, MTMC is designed to be fully compatible with the tracking pipelines and analytics libraries provided by NVIDIA Metropolis, enabling efficient deployment of wide-area monitoring systems that integrate complex cities or large-scale factory sites into a single connected space. (MTMC video)

4.4 NVIDIA VSS Blueprint: Delivering the Next Standard for Video Search

NVIDIA’s VSS (Video Search and Summarization) blueprint sets a new standard for next-generation AI architecture—enabling video data to be searched and summarized as freely as text documents. Superb AI has built video understanding and search solutions aligned with this direction and commercialized them into real-world products.

• Context-Aware Semantic Search: As envisioned by VSS, Superb AI’s solution uses its proprietary VLM to analyze video and text within the same vector space. When a user enters a natural-language query such as “A dangerous situation where a worker runs while not wearing a safety helmet,” the AI understands both the action and the context in the video and retrieves the exact matching scene. (VSS Search demo video)
  
• Instant Insights, Not Just Search Results: Beyond retrieving clips, the AI can analyze video and generate highlights in response to requests like, “Summarize the safety incidents that happened today.” This eliminates the inefficiency of manually reviewing thousands of hours of footage and enables faster, data-driven decision-making.

4.5 Manufacturing Innovation Powered by NVIDIA: Global Company P

The technical synergy between Superb AI and NVIDIA described above does not remain at the research stage. NVIDIA identified Superb AI as the partner best positioned to leverage its technology ecosystem and directly facilitated a collaboration with Company P, a Fortune 50 food-and-beverage company.

Company P aimed to adopt AI on-site to improve productivity and eliminate inefficiencies. In response, Superb AI is driving the following operational innovations through a customized solution integrated with NVIDIA technologies:

• Real-Time Anomaly Detection and Tracking: Video data from production lines is analyzed immediately on edge devices to deliver results without delay. This enables a system designed not only to manage productivity by tracking forklift routes and cargo movement speed, but also to prevent accidents by detecting, in real time, missing PPE (helmets, vests), abnormal equipment overheating, sparks, and more. In collaboration with Superb AI, the company plans to deploy the integrated system soon.
  

• Conversational Data Analysis: When a manager asks, “Show me what caused line stoppages in the last 24 hours,” the system instantly finds the relevant footage and generates a summarized report. This can reduce post-incident analysis time from hours to just minutes.

This case demonstrates that Superb AI is leveraging NVIDIA’s technology ecosystem to deliver tangible business value for customers.

5. Physical AI: A Clear Path Toward the Future

Jensen Huang’s “ChatGPT moment for robotics,” declared at CES 2026, is not a far-off vision—it is a reality that has already begun. And that reality is being built not by any single company, but on a robust ecosystem where hardware, AI, and solution providers come together as an integrated whole.

Within this massive ecosystem, Superb AI plays a critical role—providing robots with the “eyes” (Vision) to see the world and the “brain” (Brain) to judge what is happening. The combination of NVIDIA’s powerful infrastructure (Isaac Sim, Cosmos, Metropolis) and Superb AI’s practical application technologies (MTMC, VLM, VSS) has successfully brought lab-stage innovation into real industrial deployment—just as shown in the global Company P case above.

From defect detection in manufacturing sites to city-scale safety monitoring and last-mile delivery for autonomous robots, Superb AI’s technologies are reaching wherever Physical AI is needed.

Superb AI will continue to solve the toughest challenges of the physical world through close technical collaboration with NVIDIA. Our philosophy—“making the most advanced AI technology the easiest to adopt”—will serve as the most reliable compass for companies navigating the complexity of the Physical AI era. We invite you to be at the center of the Physical AI era that NVIDIA and Superb AI will build together.