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The Commercialization Path Is Gradually Clear

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In 2025, the deep integration of humanoid robots and artificial intelligence technology is changing the industrial landscape at an unprecedented pace. Against the backdrop of Tesla’s Optimus entering mass production and Huawei increasing its capital investment in its humanoid robot subsidiary to 3.89 billion yuan, the industry has moved from the “concept verification stage” to the “commercialization implementation stage.”

Meanwhile, breakthroughs in large AI model technology have provided humanoid robots with a more powerful “brain,” while humanoid robots offer AI a “body” to interact with the physical world. The coordinated development of the two is opening up a brand – new era of “embodied intelligence.” According to Wind data, in the first half of 2025, the average revenue of the A – share humanoid robot concept sector increased by 9.72% year – on – year, and the average revenue growth rate in the AI application field reached 18.7%, significantly higher than the overall level of A – shares.

This wave of technological innovation has not only attracted high attention from the capital market but also begun to release real value in scenarios such as industrial manufacturing, healthcare, and household services. Can the rapid implementation of AI and humanoid robot technologies turn science fiction into reality?

01 AI Applications: From Technological Empowerment to Value Creation

2025 is regarded as a crucial turning point for AI applications to shift from the popularization of technological concepts to in – depth industry integration. IDC data shows that the global AI market size is expected to reach $221.87 billion in 2025, with a compound annual growth rate of approximately 26.2%, and the Chinese market is becoming an important engine for this growth.

Technologically, AI applications are characterized by “full – scale expansion and high – value – added leadership.” In the field of computing infrastructure, ZTE Corporation (000063.SZ)’s liquid – cooled servers and AI servers have become industry benchmarks.

In the area of multimodal content generation, Wondershare Technology Group Co., Ltd. (300624.SZ) achieved AI – native application revenue of 60 million yuan with its Tianmu 2.0 multimodal model, and the number of paying users increased by 200% year – on – year. In the field of industrial digitalization, Taiji Computer Corporation (002368.SZ)’s government big data platform solutions have served more than 30 provinces and municipalities across the country. In terms of enterprise – level intelligent agents, Hand Enterprise Solutions Co., Ltd. (300170.SZ) has launched nearly a hundred mature intelligent agents, with a contract value exceeding 25 million yuan.

With the unremitting efforts of leading enterprises, technological breakthroughs in the industry are particularly significant. Tencent’s Hunyuan TurboS adopts a Transformer – Mamba hybrid architecture, doubling the inference efficiency. When Hong Technology Co., Ltd. (300441.SZ)’s ultra – high – definition video AI processing solution has a market share of 35%. The sales volume of Rokid AI glasses has exceeded one million units, and the average price has dropped below 2,000 yuan, marking the popularization of edge – side AI applications.

Of course, in addition to development, the industry also faces multiple challenges. Firstly, there is the issue of data privacy. An IBM report shows that 16% of data breaches in 2025 involved the use of AI tools. Secondly, there is the risk of algorithmic bias, which may lead to unfair results in financial credit approval and medical diagnosis. Thirdly, regulatory policies are tightening. A cross – border AI enterprise was fined 20 million yuan for non – compliant data transfer overseas, which serves as a warning of the compliance risks in the industry.

Notably, 54% of enterprises still cannot quantify the return on AI investment (according to Deloitte data), indicating that the industry still needs to make breakthroughs in validating commercial value. However, with the deep integration of AI technology and industry know – how, especially in data – intensive fields such as finance and healthcare, AI applications are shifting from “auxiliary tools” to “business partners,” and the path to value creation is becoming increasingly clear.

02 Humanoid Robots: From Technological Verification to Scenario Implementation

If 2024 was the “year of technological breakthrough” for humanoid robots, then 2025 is undoubtedly the “first year of commercialization.” The “Opinions on Deeply Implementing the ‘Artificial Intelligence +’ Initiative” issued by the State Council clearly supports the development of intelligent robots. Beijing has even established a humanoid robot innovation center and released the world’s first “Intelligent Classification Standard for Humanoid Robots,” providing policy support for the industry’s development.

Driven by policy support and the market, all aspects of the humanoid robot industry chain are accelerating their improvement. Among them, significant progress has been made in the localization of core components. The localization rate of harmonic reducers produced by Green Harmonic Drive Systems Co., Ltd. (688017.SH) has reached 25%. In the first half of 2025, its revenue was 251 million yuan, with a gross profit margin of 34.77%. KeLi Sensing Co., Ltd. (603662.SH) has deployed nearly 20 types of robot sensors, and the measurement error of its six – axis force sensor is less than 1%. The company’s revenue in the first half of the year was 685 million yuan, a year – on – year increase of 23.4%. Beit Automotive Co., Ltd. (603009.SH) has achieved a fine – grinding accuracy of ±0.001mm in the field of planetary roller screws. The localization of core components has reduced the BOM cost of the whole machine by 30 – 40%, laying the foundation for commercialization.

Among the whole – machine manufacturers, Estun Automation Co., Ltd. (002747.SZ)’s 31 – degree – of – freedom robot has a 23% market share in the medical exoskeleton field, with revenue of 2.549 billion yuan in the first half of the year. Midea Group Co., Ltd. (000333.SZ), with its combination of “embodied intelligence algorithm + KUKA hardware,” has sent its robots to the Jingzhou factory to participate in standardized operations such as equipment maintenance and material handling. Fourier GR – 3 focuses on household services and plans to enter offline stores in the second half of the year to provide services.

Technologically, the H1 robot of Unitree Robotics has significantly increased its degrees of freedom and enhanced its movement flexibility. Orbbec’s 3D vision sensor can model complex environments, significantly improving accuracy. These technological advancements have initially verified the application value of robots in scenarios such as industrial manufacturing and logistics sorting.

However, despite the progress, the industry still faces significant challenges. Core components such as high – end sensors and high – performance motors still rely on imports. The movement accuracy of robots in complex environments is less than 90%, still falling short of industrial standards. In addition, although some components have been domestically substituted, the unit cost of humanoid robots remains as high as 199,000 yuan, which is unaffordable for most families. As Soochow Securities pointed out, the global sales volume of humanoid robots in 2025 is expected to be less than 30,000 units, still far from large – scale popularization.

03 Integration and Breakthrough: The Commercialization Path of AI + Humanoid Robots

Amid the challenges, the deep integration of humanoid robots and AI technology is becoming the key force to drive the industry forward. On the one hand, large AI models provide humanoid robots with more powerful decision – making capabilities. On the other hand, humanoid robots offer AI a carrier to interact with the physical world. The synergy between the two will open up a closed – loop of “perception – decision – execution.”

In terms of technological integration, large models such as Tencent’s Hunyuan TurboS have doubled the inference efficiency, enabling robots to handle complex tasks more quickly. Multimodal large models have enhanced robots’ ability to understand the environment, allowing them to process multiple types of information such as vision and voice simultaneously. Enterprises such as Huawei and Midea are actively exploring the path of “embodied intelligence,” deeply integrating AI algorithms with robot hardware.

However, to truly enable AI technology and humanoid robots to benefit humanity, the following problems need to be solved. Firstly, the acceleration of domestic substitution of components. Currently, the localization rate of core components for humanoid robots is generally low, with 25% for harmonic reducers, 15% for planetary roller screws, and 10% for six – axis force sensors. With increased policy support and capital investment, it is expected that the localization rate of core components will exceed 50% by 2027. Enterprises such as Green Harmonic Drive Systems and KeLi Sensing are accelerating technological research to support cost reduction in the industry.

Secondly, a breakthrough in large – scale mass production is needed. Goldman Sachs predicts that the compound annual growth rate of global humanoid robot sales from 2025 to 2035 can reach 94%, but this is based on achieving “tens of thousands of units” of mass production. Tesla’s Optimus mass production has set a benchmark for the industry, and domestic manufacturers such as Ubtech Robotics (9880.HK) and Unitree Robotics are also actively deploying. As production volume increases, the scale effect will significantly reduce the unit cost.

Finally, the focus on scenarios and value verification of humanoid robots are crucial. The industrial scenario, with its high degree of standardization and clear ROI, has become the first area for humanoid robots to be implemented. The application of Midea’s robots in the Jingzhou factory has proven their value in scenarios such as equipment maintenance and material handling. In the future, as costs decrease and technology advances, scenarios such as household services and medical rehabilitation will also be gradually expanded.

Looking ahead, the deep integration of humanoid robots and AI applications will give rise to new business models and industrial ecosystems. CITIC Securities believes that 2025 is the year of mass production for humanoid robots, and the industry will enter a period of rapid development. CITIC Construction Investment points out that the main investment line for AI should revolve around “computing power as the foundation, self – controllability as an inevitable trend, and the rise of Agent and B – end applications.”

Although the industry still faces challenges in terms of technological maturity, cost control, data privacy, and ethical regulations, the huge potential shown by humanoid robots and AI applications has gained high – level consensus in the capital market. As Goldman Sachs predicts, by 2035, the global humanoid robot market size is expected to reach $38 billion or even $154 billion.

2025 may be the beginning of a great era that turns science fiction into reality. For investors, paying attention to enterprises with rapid commercialization of large AI models, core component enterprises that have entered the supply chains of Tesla and Ubtech, and whole – machine manufacturers with full – industry – chain capabilities may enable them to share the dividends of this technological wave.

This article is from the WeChat official account “Investor Network – Thinking Finance.” Author: Wu Wei. Republished by 36Kr with permission.



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AI algorithms can detect vision problems years before they actually appear, says ZEISS India

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Artificial intelligence (AI) algorithms and other deep-technologies can help detect vision problems years before even any traces of their symptoms appear and therefore future of eye care and maintaining good eyesight would significantly rely on predictive and preventive innovations driven by robotics, GenAI and deep-tech, said ZEISS India, a subsidiary Carl Zeiss AG, the German optics, opto-electronics, and medical technology company.

Traditionally, eye scans relied heavily on human analysis and significant efforts required to analyse huge volumes of data. “However, AI proposes to aid clinical community with its ability to analyse huge volumes of data with high accuracy and helps detect anomalies at early stages of disease onset and thereby solving one of the biggest challenges in eye care, late detention, seen in emerging economies, including India,” Dipu Bose, Head, Medical Technology, ZEISS India and Neighbouring Markets told The Hindu.

For example, he said, conditions like diabetic retinopathy, glaucoma, or macular degeneration often begin with subtle changes in the retina. AI would be able to catch early indicators (even traces of these) years before the patients become aware of having any symptoms and take timely action to prevent irreversible blindness.

According to Mr. Bose, AI, as a well-trained partner, would be able to analyse thousands of eye images in seconds, with high degree of accuracy. It learns patterns by analysing massive datasets of eye scans and medical records, and it becomes smart enough to spot the tiniest changes/things that the human eye might miss.

Future innovation would rely significantly on predictive and preventive innovations for eye care, where technology would play an essential role in formulating solutions that would allow for earlier detection, more accurate diagnoses, and tailored treatments, he forcast adding Indian eyecare professionals were increasingly adopting new age technologies to ensure better patient outcomes. As a result, AI, Gen AI, robotics and deeptech were causing a significant shift in clinical outcomes, he observed.

“This is precisely why we call it preventive blindness. In India, this is becoming increasingly relevant as the majority of the population do not go for regular eye check-ups and they visit an eye doctor only when their vision is already affected,” Mr. Bose said.

Early intervention would lead to better outcomes: reduce inefficiencies and reduced healthcare costs, he said. “ZEISS contributes to this by advancing medical technologies for diagnosis, surgical interventions, and visualization, ultimately improving patient outcomes and quality of life,” he claimed.

For instance, ZEISS Surgery Optimiser App, an AI-powered tool that allows young surgeons to learn from uploaded and segmented surgery videos of experienced cataract surgeons. Similarly, in diagnostics, ZEISS is also leveraging AI through the Pathfinder solution, an integrated deep learning and AI-based support tool. These technologies can support eye care professionals in making data-driven decisions by visualising and analysing clinical workflows. They leverage real-time surgical data to help young clinicians identify variations, optimise surgical steps, and improve procedural consistency.

“These insight-driven technologies are expected to help bridge experience gaps, improve surgical confidence, and ultimately enhance patient outcomes across the country,” Mr. Bose anticipated.

However, he added, tackling unmet needs and ensuring early diagnosis of diseases would require a fundamental shift: from reactive care to proactive and precision-driven eye-care. “This means leveraging technology not just to treat but to predict, prevent, and personalise patient care before even the symptoms of the disease show up,” he further said.

The eye-tech market is growing in India. The ophthalmic devices market was $943.8 million in 2024 and is expected to reach $1.54 billion by 2033, growing at 5.23% CAGR. The global eye-tech market was valued at approximately $74.67 billion in 2024 and is projected to reach $110.33 billion by 2030 at a CAGR of 6.9%.

Published – September 06, 2025 11:21 am IST



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AI and cybersecurity: India’s chance to set a responsible global digital standard

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India’s digital economy is experiencing extraordinary growth, driven by government initiatives, private enterprise, and widespread technological adoption across users from diverse socio-economic backgrounds. Artificial intelligence (AI) is now woven into the fabric of organisational operations, shaping customer interactions, streamlining product development, and enhancing overall agility. Yet, as digitisation accelerates, the nation’s cyber risk landscape is also expanding—fuelled by the very AI innovations that are transforming business.

In a rapidly evolving threat landscape, human error remains a persistent vulnerability. A recent cybersecurity survey revealed that 65% of enterprises worldwide now consider AI-powered email phishing the most urgent risk they face. India’s rapidly growing digital user base and surging data volumes create an environment for increased risks.

Yet, there’s a strong opportunity for India to leverage its unique technical strengths to lead global conversations on secure, ethical, and inclusive digital innovation. By championing responsible AI and cybersecurity, the country can establish itself not only as a global leader but also as a trusted hub for safe digital solutions.

The case for a risk-aware, innovation-led approach

While AI is strengthening security measures with rapid anomaly detection, automated responses, and cost-efficient scalability, these same advancements are also enabling attackers to move faster and deploy increasingly sophisticated techniques to evade defences. The survey shows that 31% of organisations that experienced a breach faced another within three years, underscoring the need for ongoing, data-driven vigilance.

Globally, regulators are deliberating on ensuring greater AI accountability, frameworks with tiered risk assessments, data traceability, and demands for transparent decision-making, as seen in the EU AI Act, the National Institute of Standards and Technology’s AI Risk Management Framework in the US, and the Ministry of Electronics and Information Technology’s AI governance guidelines in India.

India’s digital policy regime is evolving with the enactment of the Digital Personal Data Protection Act and other reforms. Its globally renowned IT services sector, increasing cloud adoption, and digital solutions at population scale are use cases for nations to leapfrog in their digital transformation journey. However, there is a continued need for collaboration for consistent standards, regulatory frameworks, and legislation. This approach can empower Indian developers as they build innovative and compliant solutions with the agility to serve Indian and global markets.

Smart AI security: growing fast, staying steady

The survey highlights that more than 90% of surveyed enterprises are actively adopting secure AI solutions, underscoring the high value organisations place on AI-driven threat detection. As Indian companies expand their digital capabilities with significant investments, security operations are expected to scale efficiently. Here, AI emerges as an essential ally, streamlining security centres’ operations, accelerating response time, and continuously monitoring hybrid cloud environments for unusual patterns in real time.

Boardroom alignment and cross-sector collaboration

One encouraging trend is the increasing involvement of executive leadership in cybersecurity. More boards are forming dedicated cyber-risk subcommittees and embedding risk discussions into broader strategic conversations. In India too, this shift is gaining momentum as regulatory expectations rise and digital maturity improves.

With the lines between IT, business, and compliance blurring, collaborative governance is becoming essential. The report states that 58% of organisations view AI implementation as a shared responsibility between executive leadership, privacy, compliance, and technology teams. This model, if institutionalised across Indian industry, could ensure AI and cybersecurity decisions are inclusive, ethical, and transparent.

Moreover, public-private partnerships — especially in areas like cyber awareness, standards development, and response coordination — can play a pivotal role. The Indian Computer Emergency Response Team (CERT-In), a national nodal agency with the mission to enhance India’s cybersecurity resilience by providing proactive threat intelligence, incident response, and public awareness, has already established itself as a reliable incident response authority.

A global opportunity for India

In many ways, the current moment represents a calling to create the conditions and the infrastructure to lead securely in the digital era. By leveraging its vast resource of engineering talent, proven capabilities in scalable digital infrastructure, and a culture of economical innovation, India can not only safeguard its own digital future but also help shape global norms for ethical AI deployment. This is India’s moment to lead — not just in technology, but in trust.

This article is authored by Saugat Sindhu, Global Head – Advisory Services, Cybersecurity & Risk Services, Wipro Limited.

Disclaimer: The views expressed in this article are those of the author/authors and do not necessarily reflect the views of ET Edge Insights, its management, or its members



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Nvidia says GAIN AI Act would restrict competition, likens it to AI Diffusion Rule

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If passed into law, the bill would enact new trade restrictions mandating exporters obtain licenses and approval for the shipments of silicon exceeding certain performance caps [File]
| Photo Credit: REUTERS

Nvidia said on Friday the AI GAIN Act would restrict global competition for advanced chips, with similar effects on the U.S. leadership and economy as the AI Diffusion Rule, which put limits on the computing power countries could have.

Short for Guaranteeing Access and Innovation for National Artificial Intelligence Act, the GAIN AI Act was introduced as part of the National Defense Authorization Act and stipulates that AI chipmakers prioritize domestic orders for advanced processors before supplying them to foreign customers.

“We never deprive American customers in order to serve the rest of the world. In trying to solve a problem that does not exist, the proposed bill would restrict competition worldwide in any industry that uses mainstream computing chips,” an Nvidia spokesperson said.

If passed into law, the bill would enact new trade restrictions mandating exporters obtain licenses and approval for the shipments of silicon exceeding certain performance caps.

“It should be the policy of the United States and the Department of Commerce to deny licenses for the export of the most powerful AI chips, including such chips with total processing power of 4,800 or above and to restrict the export of advanced artificial intelligence chips to foreign entities so long as United States entities are waiting and unable to acquire those same chips,” the legislation reads.

The rules mirror some conditions under former U.S. President Joe Biden’s AI diffusion rule, which allocated certain levels of computing power to allies and other countries.

The AI Diffusion Rule and AI GAIN Act are attempts by Washington to prioritise American needs, ensuring domestic firms gain access to advanced chips while limiting China’s ability to obtain high-end tech amid fears that the country would use AI capabilities to supercharge its military.

Last month, U.S. President Donald Trump made an unprecedented deal with Nvidia to give the government a cut of its sales in exchange for resuming exports of banned AI chips to China.



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