Alibaba Steps Into ‘Physical AI’ With New Robotics Model

China’s Alibaba has taken a decisive step into the fast‑emerging field of ‘physical AI’ with the launch of a new foundation model designed specifically to power real‑world robots.

The model, known as RynnBrain*, marks one of the company’s most ambitious moves since restructuring its cloud and research divisions, and signals China’s intention to compete directly with the United States in embodied artificial intelligence.

Unlike traditional large language models, which operate entirely in digital environments, RynnBrain is built to interpret and act within the physical world.

It combines vision, language and spatial reasoning, enabling robots to recognise objects, understand their surroundings and plan multi‑step actions.

DAMO Acadamy

In demonstrations released by Alibaba’s DAMO Academy, the model guided a robot through tasks such as identifying fruit and sorting it into containers — a deceptively simple exercise that requires sophisticated perception and motor control.

The company describes RynnBrain as a ‘general‑purpose embodied intelligence model’, capable of supporting a wide range of robotic applications, from warehouse automation to domestic assistance.

Crucially, Alibaba has opted to open‑source the model, a strategic decision that invites global developers to build on its capabilities and accelerates the creation of a broader ecosystem around Chinese robotics research.

Physical AI

The timing is significant. Over the past year, major technology firms including Google, Nvidia and OpenAI have begun to emphasise physical AI as the next frontier of artificial intelligence.

The shift reflects a growing belief that the most transformative applications of AI will not be confined to screens, but will instead involve machines that can navigate, manipulate and collaborate within human environments.

Alibaba’s entry adds competitive pressure to a field already heating up. While U.S. companies currently dominate embodied AI research, China has made robotics a national priority, viewing it as a strategic industry with implications for manufacturing, logistics and economic resilience.

RynnBrain

By releasing RynnBrain openly, Alibaba positions itself as both a contributor to global research and a catalyst for domestic innovation.

The launch also highlights a broader trend: the convergence of AI models with physical systems. As robots become more capable and more affordable, the line between software intelligence and mechanical action is beginning to blur.

RynnBrain is an early example of this shift — a model designed not just to understand language or images, but to translate that understanding into purposeful action.

Whether Alibaba’s approach will reshape the global robotics landscape remains to be seen, but the message is clear: the race to build the brains of future machines is accelerating, and China intends to be at the forefront.

Other Major Players in Physical AI

Physical AI — AI that can perceive, reason and act in the real world — has become the next strategic battleground for global tech giants. Alibaba is far from alone.

Several companies are racing to build the ‘general‑purpose robot brain’.

Below are the most significant players.

1. Google DeepMind

Focus: Embodied AI, robotics‑ready multimodal model’s Key systems:

RT‑2 (Robotic Transformer)

Gemini‑based robotics extensions

Google has been working on robotics for over a decade. RT‑2 was one of the first models to show that a language model could directly control a robot arm, interpret objects, and perform multi‑step tasks.

DeepMind is now integrating robotics capabilities into the Gemini family.

2. OpenAI

Focus: General‑purpose embodied intelligence Key systems:

OpenAI Robotics (revived internally)

Vision‑language‑action research

OpenAI paused robotics in 2020 but has quietly restarted the programme. Their models are being trained to understand video, track objects and perform physical tasks. They are also working with hardware partners to test embodied versions of their models.

3. Nvidia

Focus: The infrastructure layer for physical AI Key systems:

Nvidia Isaac (robotics platform)
Cosmos models
Omniverse simulation

Nvidia is not building consumer robots; it is building the entire ecosystem for everyone else. Its simulation tools, training environments and robotics‑ready AI models are becoming the backbone of the industry.

4. Tesla

Focus: Humanoid robotics Key system:

Optimus (Tesla Bot)

Tesla is training its robot using the same AI stack as its autonomous driving system. The company claims Optimus will eventually perform factory and household tasks.

It is one of the most visible attempts to build a general‑purpose humanoid robot.

5. Amazon

Focus: Warehouse automation and domestic robotics Key systems:

Proteus (autonomous warehouse robot)
Astro (home robot)

Amazon is integrating multimodal AI into its logistics robots and experimenting with home assistants that can navigate physical spaces.

6. Figure AI

Focus: General‑purpose humanoid robots’ Key system:

Figure 01

Backed by OpenAI, Microsoft and Nvidia, Figure is developing a humanoid robot designed to perform everyday tasks.

Their recent demos show robots manipulating objects and responding to natural language instructions.

7. Boston Dynamics

In partnership with Google’s DeepMind Boston Dynamics is also building a ‘foundation model intelligence’ robot brain.

The Big Picture

Alibaba is entering a field dominated by U.S. companies, but the global race is wide open. Physical AI is becoming the next strategic platform — the equivalent of smartphones in the 2000s or cloud computing in the 2010s.

*RynnBrain explained

RynnBrain is Alibaba’s open‑source ‘physical AI‘ framework designed to give robots far more capable real‑world intelligence, enabling them to plan, navigate, and manipulate objects across dynamic environments such as factories and homes.

Developed by the company’s DAMO Academy, it competes directly with Google’s Gemini Robotics and Nvidia’s Cosmos‑Reason models, with Alibaba claiming stronger benchmark performance.

The system is released openly on platforms like GitHub and Hugging Face, offered in configurations from lightweight 2‑billion‑parameter models to advanced mixture‑of‑experts variants, and includes specialised versions—Plan, Nav, and CoP—targeting manipulation, navigation, and spatial reasoning respectively.

Its launch signals China’s ambition to lead global robotics and embodied AI development.

August 5, 2025September 12, 2025

China’s new AI model GLM-4.5 threatens DeepSeek – will it also threaten OpenAI?

In a bold move reshaping the global AI landscape, Chinese startup Z.ai has launched GLM-4.5, an open-source model touted as cheaper, smaller, and more efficient than rivals like DeepSeek.

The announcement, made at the World Artificial Intelligence Conference in Shanghai, has sent ripples across the tech sector.

What sets GLM-4.5 apart is its lean architecture. Requiring just eight Nvidia H20 chips—custom-built to comply with U.S. export restrictions—it slashes operating costs dramatically.

By comparison, DeepSeek’s model demands nearly double the compute power, making GLM-4.5 a tantalising alternative for cost-conscious developers and enterprises.

But the savings don’t stop there. Z.ai revealed that it will charge just $0.11 per million input tokens and $0.28 per million output tokens. In contrast, DeepSeek R1 costs $0.14 for input and a hefty $2.19 for output, putting Z.ai firmly in the affordability lead.

Functionally, GLM-4.5 leverages ‘agentic’ AI—meaning it can deconstruct tasks into subtasks autonomously, delivering more accurate results with minimal human intervention.

This approach marks a shift from traditional logic-based models and promises smarter integration into coding, design, and editorial workflows.

Z.ai, formerly known as Zhipu, boasts an impressive funding roster including Alibaba, Tencent, and state-backed municipal tech funds.

With IPO ambitions on the horizon, its momentum mirrors China’s broader push to dominate the next wave of AI innovation.

While the U.S. has placed Z.ai on its entity list, stifling some Western partnerships, the firm insists it has adequate computing resources to scale.

As AI becomes a battleground for technological and geopolitical influence, GLM-4.5 may prove to be a powerful competitor.

But it has some way yet to go.

August 1, 2025September 12, 2025

China reportedly concerned about security of Nvidia AI chips

China has reportedly voiced concerns about the security implications of Nvidia’s cutting-edge artificial intelligence chips, deepening the tech cold war between Beijing and Washington.

The caution follows increasing scrutiny of semiconductors used in defence, infrastructure, and digital surveillance systems—sectors where AI accelerators play an outsized role.

While no official ban has been announced, sources suggest that Chinese regulators are examining how Nvidia’s chips—known for powering generative AI and large language models—might pose risks to national data security.

At the core of the issue is a growing unease about foreign-designed hardware transmitting or processing sensitive domestic information, potentially exposing it to surveillance or manipulation.

Nvidia, whose H100 and A800 series dominate the high-performance AI landscape, has already faced restrictions from the U.S. government on exports to China.

In response, Chinese tech firms have been developing domestic alternatives, including chips from Huawei and Alibaba, though few match Nvidia’s sophistication or efficiency.

The situation highlights China’s larger strategy to reduce reliance on American technology, especially as AI becomes more integral to industrial automation, cyber defence, and public services.

It also underscores the dual-use dilemma of AI—where innovation in consumer tech can quickly scale into military applications.

While diplomatic channels remain frosty, the market implications are heating up. Nvidia’s shares dipped slightly on the news, and analysts predict renewed interest in sovereign chip initiatives across Asia.

For all the lofty aspirations of AI making the world smarter, it seems that suspicion—not cooperation—is the current driving force behind chip geopolitics.

As one observer quipped, ‘We built machines to think for us—now we’re worried they’re thinking too much, in all the wrong places’.

Nvidia reportedly denies there are any security concerns.

October 3, 2024September 12, 2025

What is China’s equivalent to Nvidia?

Chinese firms are reportedly intensifying their efforts to develop a competitive alternative to Nvidia’s AI chips, as part of Beijing’s ongoing initiative to reduce its reliance on U.S. technology.

China faces several challenges that are impeding its technological progress, including U.S. export restrictions that limit domestic semiconductor production. The lack of technical expertise is also reported to be a problem.

Analysts have identified companies including Huawei as the principal competitors to Nvidia in China

China’s counterparts to Nvidia, such as Huawei, Alibaba, and Baidu, are actively developing AI chips to compete in the same market. Huawei’s HiSilicon division is known for its Ascend series of data centre processors.

Huawei’s HiSilicon division is known for its Ascend series of data centre processors, and Alibaba’s T-Head has produced the Hanguang 800 AI inference chip. Other significant players include Biren Technology and Cambricon Technologies.

Alibaba’s T-Head has developed the Hanguang 800 AI inference chip. Other significant players include Biren Technology and Cambricon Technologies.

These Chinese firms are intensifying their efforts to create alternatives to Nvidia’s AI-powering chips. This is a big part of Beijing’s broader initiative to reduce its reliance on U.S. technology.

Nvidia’s surge in growth is attributed to the demand from major cloud computing companies for its server products, which incorporate graphics processing units, or GPUs.

These GPUs are crucial for entities like OpenAI, the creator of ChatGPT, which requires substantial computational power to train extensive AI models on large datasets.

AI models are crucial for chatbots and other AI applications

Since 2022, the U.S. has limited the export of Nvidia’s top-tier chips to China, with further restrictions imposed last year.

The U.S. sanctions and Nvidia’s market dominance pose significant obstacles to China’s ambitions, particularly in the short term, according to analysts. The U.S. has curbed the export of Nvidia’s most sophisticated chips to China since 2022, with increased restrictions implemented last year.

China’s GPU designers rely on external manufacturers for chip production. Traditionally, this role was filled by Taiwan Semiconductor Manufacturing Co. (TSMC). However, due to U.S. restrictions, many Chinese firms are now unable to procure chips from TSMC.

As a result, they have shifted to using SMIC, China’s largest chipmaker, which is technologically several generations behind TSMC. This gap is partly due to Washington’s limitations on SMIC’s access to essential machinery from the Dutch company ASML, necessary for producing the most advanced chips.

Huawei is driving the development of more sophisticated chips for its smartphones and AI, which occupies a significant portion of SMIC’s capacity.

Nvidia has achieved success not only through its advanced semiconductors but also via its CUDA software platform. The system enables developers to build applications for Nvidia’s hardware. This has fostered an ecosystem around Nvidia’s designs, which will be challenging for competitors to emulate.

Huawei leading the pack for China

Huawei is at the forefront as a leading force in China for its Ascend series of data centre processors. The current generation, named Ascend 910B, is soon to be succeeded by the Ascend 910C. This new chip may come to rival Nvidia’s H100.

September 27, 2024September 12, 2025

China’s tech stocks rally to 13-month high on new stimulus

Chinese technology stocks, such as the previously underperforming Alibaba, have surged this week, reaching peaks not observed in over a year

The stock surge follows the announcement of stimulus measures by China’s central bank to boost the world’s second-largest economy.

On Thursday 26th September 2024 in the U.S., Alibaba’s shares closed above $100 for the first time since August 2023.

Tencent’s shares ended at their highest point in over two and a half years.

September 12, 2024September 12, 2025

The AI Race between China and the U.S.

Artificial Intelligence (AI) has become a pivotal battleground in the technological race between China and the United States.

“AI is expected to become a crucial component of economic and military power in the near future,” Stanford University’s Artificial Intelligence Index Report 2023 stated.

Both countries are significantly investing in AI research and development, striving to achieve a leading role in this revolutionary sector. This post looks at the major figures in China’s AI scene, their progress, and their comparison with their American counterparts.

China’s AI Landscape

China’s AI aspirations are propelled by a number of significant technology firms, each forging their own AI models and applications.

Baidu: Often referred to as the ‘Google of China,’ Baidu leads in AI development. Its premier AI model, ERNIE (Enhanced Representation through Knowledge Integration), fuels the Ernie Bot, a chatbot aimed to compete with OpenAI’s ChatGPT. Baidu asserts that ERNIE 4.0 matches GPT-4’s capabilities, demonstrating sophisticated understanding and reasoning abilities.

Alibaba: Alibaba’s AI model, Tongyi Qianwen (commonly known as Qwen), is a comprehensive set of foundational models adept at a range of tasks, from generating content to solving mathematical problems. Select versions of Qwen are open-source, enabling developers to utilize and modify them for various uses. Alibaba has announced that Qwen models are in use by over 90,000 enterprise clients.

Tencent: The Hunyuan model from Tencent is a prominent component of China’s AI landscape. Offered through Tencent’s cloud computing division, Hunyuan is tailored to facilitate a broad spectrum of applications, encompassing natural language processing and computer vision.

Huawei: In spite of considerable obstacles stemming from U.S. sanctions, Huawei persists in AI innovation. The firm has created its own AI processors, like the Kunlun series, to diminish dependence on international technology. Huawei’s AI features are incorporated into a diverse array of products, including smartphones and cloud solutions.

Comparison to the U.S.

The U.S. continues to be a dominant force in AI, with leading companies such as OpenA I, Microsoft, Google, Anthropic and Meta spearheading advancements.

Generative AI: U.S. firms have advanced significantly in generative AI, with OpenAI’s GPT-4 and Google’s Gemini at the forefront. These models excel in creating text, images, and videos from user inputs. Although Chinese models like ERNIE and Qwen are strong contenders, the U.S. maintains a slight lead in capabilities and market penetration.

Semiconductor Design: The U.S. leads the semiconductor design industry, vital for AI progress. U.S. companies command an 85% global market share in chip design, crucial for AI model training and system operation. China’s dependence on imported semiconductors is a notable obstacle, but there are ongoing efforts to create homegrown solutions.

Research and Innovation: Both nations boast strong AI research sectors, yet the U.S. edges out slightly in generating state-of-the-art AI products. U.S. tech giants frequently introduce AI breakthroughs to the market, with Chinese firms quickly gaining ground.

Government Support: The Chinese government ardently backs AI advancement, enacting strategies to spur innovation and lessen foreign tech reliance. Such support has spurred China’s AI industry’s rapid expansion, positioning it as a strong rival to the U.S.

Conclusion

The competition in AI development between China and the U.S. is escalating, as both countries achieve significant breakthroughs. Although the U.S. maintains a marginal lead in some respects, China’s swift advancement and state backing indicate that the disparity might keep closing. The quest for AI dominance by these nations is set to influence the worldwide technological and innovative landscape profoundly.

As of September 2024, it is estimated that China’s AI development is approximately nine months behind that of the U.S.