Source: Alpha Factory Research Institute.

As the world's leading Semiconductor company faces intensified competition in its core AI chip business, $NVIDIA (NVDA.US)$ it is betting on Siasun Robot&Automation technology as a key driver for its next growth step.

This USA Technology giant is known for its infrastructure supporting the AI boom and plans to launch its latest generation of compact computers for humanoid robots, Jetson Thor, in the first half of 2025.

NVIDIA is committed to becoming the leading platform for the upcoming robotic revolution. The company sells a "full-stack" solution, from the software layer needed for training AI-driven robots to the chips embedded within.

"The 'ChatGPT moment' for physical AI and robot technology is coming soon," said Deepu Talla, Vice President of NVIDIA's robot business, in an interview with the FT, believing that the market has reached a 'critical point.'

NVIDIA is entering the Siasun Robot&Automation field just as it faces competition in the core AI chip market from rivals like $Advanced Micro Devices (AMD.US)$ and other chip manufacturers, as well as$Amazon (AMZN.US)$、$Microsoft (MSFT.US)$and $Alphabet-C (GOOG.US)$ Competition among Cloud Computing giants. These companies are seeking to reduce their dependence on USA semiconductor giants.

With the surging demand for its AI chips, NVIDIA's Market Cap has exceeded 3 trillion USD, and it is now positioning itself as an investor in the 'Physical AI' space, aiming to help the next generation of robot companies grow.

In February of this year, NVIDIA, along with companies like Microsoft and OpenAI, invested in the humanoid robot company Figure AI, which was valued at 2.6 billion USD at the time.

So far, robotics technology remains an emerging niche market that has yet to generate large-scale returns. Many startups in this field are struggling to address challenges related to scaling, cost reductions, and improving robotic product accuracy.

Although NVIDIA does not separately disclose sales figures for its robot products, the robotics Business currently accounts for a relatively small portion of overall revenue. The Datacenter revenue, primarily from NVIDIA's AI GPU chips, already accounted for 88% of its total sales of 35.1 billion USD in Q3 2023.

However, Tara stated that the transformation of the robotics market is driven by two technological breakthroughs: the explosive development of generative AI models and the enhancement of robot capabilities using simulated environments for training on these foundational models.

The latter is especially significant as it helps to address the 'Sim-to-Real gap' referred to by roboticists, ensuring that robots trained in virtual environments can effectively operate in the real world.

"In the past 12 months... [this gap] has matured enough that we can experiment in simulation, combined with Generative AI, to perform tasks that were impossible two years ago," Tara said. "We provide a platform that enables all these companies to accomplish these tasks."

Tara joined NVIDIA in 2013 and began working on the development of the Tegra chip, which initially targeted the Smart Phone market.

However, NVIDIA quickly shifted its focus, with Tara leading the redeployment of around 3,000 engineers into the field of AI and autonomous driving training (for example, self-driving Autos). This also marked the birth of Jetson, NVIDIA's series of robotic 'brain' modules, which was first showcased in 2014.

NVIDIA provides tools across three phases of robot development: Software for training foundational models (from NVIDIA's DGX systems); technology for simulating real-world environments on its Omniverse platform; and Hardware as the robot's 'brain.'

Apptronik uses NVIDIA's technology in its humanoid robot development and announced a strategic partnership with Alphabet-C in December to improve its products.

According to data from the USA market research firm BCC, the current valuation of the Global robot market is approximately $78 billion, and it is expected to reach $165 billion by the end of 2029.

Amazon has deployed NVIDIA's robotic simulation technology in three warehouses in the USA, and companies such as Toyota and Boston Dynamics are also customers of NVIDIA's training Software.

David Rosen, the head of the Robust Autonomous Laboratory at Northeast University, said that the robot market still faces significant challenges, including training models and verifying whether the robot can ensure safety after deployment.

"Currently, we do not have very effective tools to verify the safety and reliability of machine learning systems, especially robotic systems. This is a major scientific issue in the field," Rosen stated.

Editor/rice