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● Robo-Brain Drain- Korea’s Crisis, Opportunity

Nvidia Leads the Future of Robots and Artificial Intelligence with Data Amplification

1. Nvidia’s Data Amplification System

Nvidia’s message is that it will amplify the vast amounts of data needed in the robotics field.
It replicates real-world situations tens of thousands of times in a virtual space using simulation and digital twin technology.
Thanks to this amplified data, artificial intelligence model learning becomes much faster and more precise.
It is emphasized that Nvidia’s GPU and CUDA process play a key role.
As a result, the robot’s imitation learning ability is maximized, enabling real-time control of humanoids.

2. Precise Hand Mechanism of Humanoid Robots

A robot’s hand is a key component that must operate as delicately as a human.
The higher the degree of freedom, the more complex gripping motions and various tasks can be performed.
Existing entry-level hands have about 20 to 30 degrees of freedom, but the latest developments are trying to implement two degrees of freedom per finger.
This technology enables humanoid robots to accurately handle water bottles, tools, and even laundry.
The precise actuation of the hand will determine competitiveness in the robot industry.

3. Imitation Learning and Application of Artificial Intelligence

Imitation learning is a learning method in which a robot follows what a human demonstrates.
Technology that synchronizes a person’s vision and movements with a robot using a VR headset is noteworthy.
We are acquiring a lot of data so that the same operation can be applied in various environments.
As the amount of data increases, the accuracy and applicability of artificial intelligence models increase.
Thanks to this method, robots can make autonomous judgments even in various situations.

4. Collaboration Between Humans and Robots, The Future of Industrial Field Application

In the industrial field, robots create synergy through collaboration with humans rather than working alone.
Real-time robot soccer games and production line input cases show this well.
When robots and humans work together, it helps solve the problem of population cliffs and labor shortages.
Through collaboration, the work efficiency and mission range of robots are expected to be further expanded.
This collaboration model will be a key strategy in various industries as well as manufacturing in the future.

5. Nvidia and Humanoid Robot Collaboration: New Package and Highway Strategy

Nvidia is trying to provide solutions that go beyond simple data amplification.
A small, power-efficient computer (Esso) will be installed in the robot.
This system makes it easy to install artificial intelligence models trained in the cloud on robots.
In addition, it emphasizes the perfect combination of hardware and software, like Nvidia’s highway strategy.
Ultimately, this collaboration is expected to greatly improve the robot’s imitation learning and real-time inference performance.

< Summary >
Nvidia presents a new paradigm for artificial intelligence model learning by amplifying vast amounts of data through simulation and digital twins.
Humanoid robots are trying to implement delicate hand functions like humans, and high-degree-of-freedom design is key.
Using imitation learning technology, the VR-based synchronization system allows robots to reproduce human movements and be applied in diverse environments.
In the industrial field, we are moving toward maximizing production efficiency and solving labor shortages through collaboration between humans and robots.
Finally, Nvidia's small computers and highway strategies are expected to innovatively support robots' real-time reasoning and control capabilities.

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Humanoid Robots, Key to the Future Industry

*YouTube Source: [와이스트릿 – 지식과 자산의 복리효과]

– “또 놀랄 겁니다” 로봇 기술, 한국의 큰 위기이자 기회인 이유…”미국행 아니면 의대행” 수준 높은 로봇 인재들이 한국을 탈출하는 이유 / 한재권 교수 (풀버전)