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Wang Naiyan, Head of ADS Technology at Xiaomi Auto, Resigns

Sources familiar with the matter revealed that Wang Naiyan, head of autonomous driving technology at Xiaomi Auto, has submitted his resignation to Xiaomi Auto and is awaiting approval from the company’s management.

Xiaomi Auto

As Xiaomi Auto continues to deliver mass-produced models and intelligent driving becomes a core competitive advantage for the brand, a large-scale intelligent driving R&D team of over a thousand people supports Xiaomi’s complete technological layout, from highway NOA (Noise, Assessment, and Assistance) and urban navigation to advanced L3 autonomous driving. Dr. Wang Naiyan, as the head of Xiaomi’s L3 intelligent driving technology, is a key figure in this impressive R&D team, connecting cutting-edge algorithms, mass production implementation, and regulatory safety. From a leading scholar in computer vision to CTO of commercial vehicle autonomous driving, and then to the head of Xiaomi’s advanced intelligent driving efforts for passenger vehicles, his career trajectory perfectly reflects Xiaomi Auto’s complete path to fill the gaps in its top-level autonomous driving capabilities and strive to join the industry’s first tier.

Wang Naiyan possesses a solid academic foundation and is recognized as a top young researcher in the field of computer vision in China. He graduated with a PhD in Computer Science from the Hong Kong University of Science and Technology in 2015. After graduation, he joined TuSimple, an autonomous driving startup, leading the establishment of its Beijing algorithm team. In 2019, he was promoted to CTO of TuSimple China, coordinating both L2 assisted driving and L4 autonomous truck R&D lines. His years of experience in commercial vehicle R&D have given him a comprehensive understanding of the entire algorithm chain, including perception, prediction, planning, and control. He has also accumulated mature experience in large-scale fleet verification, functional safety systems, and extreme scenario testing, making him one of the very few composite technical managers in the industry who is proficient in both L2 mass production deployment, L4 autonomous systems, and regulatory compliance verification.

In May 2024, Xiaomi officially announced Wang Naiyan’s joining the company as the head of Xiaomi’s Intelligent Driving L3 technology, reporting directly to Ye Hangjun, Chairman of Xiaomi’s Technical Committee and head of Autonomous Driving. This talent acquisition is seen by the industry as a landmark event in Xiaomi’s accelerated advancement in intelligent driving. Within Xiaomi’s intelligent driving team of over 1,800 people and its R&D matrix comprised of 108 PhDs, four core leaders have a clear division of labor: Ye Hangjun oversees the overall business architecture, Chen Guang focuses on end-to-end mass production algorithms, Chen Long is responsible for cutting-edge VLA visual language models, and Wang Naiyan independently spearheads the entire L3 process, forming a three-pronged technical layout of “mass production implementation + cutting-edge pre-research + advanced access.”

Having joined Xiaomi for over two years, Wang Naiyan’s work has been running on two parallel tracks: on the one hand, steadily advancing L3 passenger vehicle technology R&D and compliance certification, continuously improving the advanced assisted driving capabilities of existing mass-produced models; on the other hand, leading the verification of autonomous driving technology under extreme conditions, refining the underlying control model through rigorous testing.

2026-07-03
Galbot’s IPO Revenue Halved by Auditor

Sources familiar with the matter revealed that Galbot, in its IPO preparation, brought in investment banks and accounting firms for guidance. However, during the financial audit, Galbot’s revenue was halved due to nearly half of its revenue being of low quality, consisting of related-party transactions and miscellaneous income.

Galbot

The impact of this revenue halving on Galbot’s IPO is currently unclear. This leading avatar company is valued at tens of billions, and investors are waiting for the IPO to exit.

However, if it affects Galbot’s IPO, it will undoubtedly be a heavy blow to the current booming investment and financing in the avatar industry.

This year, many leading avatar companies set very aggressive delivery targets to boost revenue for their IPOs, ranging from as high as 10,000 units to 1,000 units. Achieving 1,000 units would generate hundreds of millions in revenue, significantly boosting IPO prospects.

However, the reality is far from ideal. With the first half of the year almost over, even delivering 100 units is proving difficult.

While VLA and world models are very eye-catching in performance demos, they are ineffective in real-world scenarios, exhibiting poor success rates and reliability in task operations. Therefore, many embodied companies have begun poaching engineers from the traditional algorithm industry within the autonomous driving sector, using autonomous driving rule-based algorithms (perception, PNC, SLAM) for overfitting in an attempt to achieve commercialization.

For embodied companies that are currently enjoying a surge in funding, this marks a critical juncture. Whether they can deliver on their IPO promises to investors will significantly impact future fundraising. Failed IPOs will severely damage investor confidence.

2026-07-02
Galaxea AI Co-founder Zhao Xing to Start His Own Company

Sources familiar with the matter revealed that Zhao Xing, co-founder of Galaxea AI, will be leaving to start his own business. As co-founder and chief scientist of Galaxea AI, Zhao was primarily responsible for Galaxea AI’s humanoid robot technology. In early 2026, Xu Huazhe, co-founder and chief scientist of Xinghaitu, also left to start his own company, which will focus on the embodied intelligence consumer application market.

Galaxea AI

Currently, Galaxea AI is preparing for its Hong Kong IPO. Zhao Xing’s departure will significantly impact its IPO process. Furthermore, Galaxea AI’s second-largest customer has also started developing its own humanoid robots. This not only means losing a major client’s revenue but also further consolidation in the humanoid robot market, with players in the 3C consumer electronics sector entering the fray.

Galaxea AI’s second-largest customer is a leading mobile phone manufacturer. Leveraging its hardware capabilities accumulated in 3C consumer electronics, the manufacturer not only developed its own humanoid robot but also won a championship in a robot marathon. Mobile phone manufacturers possess stronger hardware capabilities; for example, in addressing the industry-wide headache of heat dissipation, this leading mobile phone manufacturer, with its accumulated heat dissipation technology in 3C products, has solved the heat dissipation problem much better than embodied robot companies. It’s safe to say that the avatar industry will be incredibly competitive this year, as players with significantly stronger hardware capabilities have entered the fray.

As is well known, the avatar industry has undergone three major data transformations in 2025, from Yamato to Umi to Ego. In terms of models, it has evolved from the initial VLA to VLA and world models operating in parallel, and the emergence of native multimodal large models, among others.

While avatars are still in their early stages, primarily showcasing technological demos, new technologies emerge in data and models every few months. This requires industry players to maintain a keen sense of opportunity, quickly recognizing and adapting to new technologies to avoid falling behind.

However, this leading avatar company failed to react quickly enough and kept pace with industry changes. In early 2026, while other players were heavily investing in Umi or Ego data, this leading avatar company was still betting on Yamato. This bet was based on its desire to launch an IPO, which requires substantial revenue, currently achieved through selling more avatar robots. Galaxea AI lacks the performance scenario capabilities of companies like Unitree and Calcium Cloud, which require product and distribution capabilities. For Galaxea AI, its primary sales scenario is data acquisition, specifically digital data acquisition for mobile devices. Therefore, in its pursuit of an IPO and increased revenue, it’s betting heavily on mobile devices.

However, although lagging behind the leading companies in terms of pace, this hasn’t affected Galaxea AI’s fundraising. This year’s fundraising has been like a flood, with investors flocking to players large and small. Having secured a leading position early on, the company successfully completed a multi-billion yuan funding round.

2026-07-01
INNODIGYM OMNI X1 Review

On June 23, a smart fitness device called the OMNI X1 hit Kickstarter. Twelve hours later, it had raised $1.4 million. Five hundred sixty-one backers had already locked in their pledges, and several high-tier bundles sold out completely.

That velocity is impressive even by Kickstarter hardware standards. What makes it wilder is that this machine comes from a Xiamen-based company called Renhe Sports, which had already turned heads at domestic trade shows and Germany’s FIBO fitness expo.

So here is the real question: why are Western users throwing money at a Chinese home gym device?

INNODIGYM OMNI X1 folds to just 14.5cm for compact storage

The Core Pitch: Squeezing a Commercial Gym into 1.1 Square Meters

The OMNI X1’s underlying logic is refreshingly direct—replace traditional iron weight stacks with servo motors, then deliver a commercial-grade strength training experience inside an ordinary living room.

Home fitness equipment has always faced a brutal trade-off. Treadmills and benches eat floor space. Resistance bands and cheap weight systems feel nothing like real gym equipment. Commercial cable machines feel amazing, but they will not fit in your apartment.

The OMNI X1 sidesteps this dilemma with dual servo motors that output up to 120kg of digital resistance per side, adjustable in 0.5kg increments. The resistance curve closely mimics the feel of barbells and cable machines. In plain terms, it tries to give you a gym-quality strength workout on your living room floor.

Moreover, the footprint matters. The unit occupies just 1.1 square meters, and when folded it shrinks to 14.5 centimeters thick. For urban apartments in Europe and North America where every square foot costs money, that compact profile is not a nice-to-have—it is essential.

AI Is Not a Gimmick Here, It Is a Barrier Killer

The hardware runs on a 360-degree multi-pulley system that supports squats, deadlifts, flyes, rows, and full-body movements. Yet the real differentiator from traditional strength gear is the AI layer.

OMNI X1 accessory bundle includes pull-up bar and training bench

The standout feature is an AI-assisted pull-up system powered by LiDAR. It tracks your joint angles in real time and automatically provides assistance when you hit muscle failure. The practical value is simple: it dramatically lowers the entry barrier for upper-body training, letting beginners perform pull-ups that would otherwise take months to build up to.

On top of that, the machine packs a full smart safety system and iterative AI training software. It corrects your form, logs your workout data, and pushes customized training programs. These features serve both hardcore lifters and absolute beginners—essentially, it tries to please the gym veteran and the three-day-old gym member at the same time.

Why Now? The Post-Pandemic Home Fitness Wave Is Still Rolling

The OMNI X1’s success is not an isolated case. The home fitness hardware sector has been heating up for years, driven by three structural forces.

First, time economics. Gym memberships in Europe and North America are expensive, and the commute adds another thirty minutes each way. Many users would rather train at home than burn time on the road.

Second, space constraints. Urban housing is compact, and traditional home equipment is either too bulky, too ugly, or too limited in function. The OMNI X1 combines commercial-grade feel, small-footprint storage, and AI assistance in one package. It lands squarely on the pain point.

Third, the intelligence trend. Fitness consumers increasingly want more than “lift and count.” They want data, feedback, and personalization. AI and digital resistance technology deliver exactly that incremental value.

Product Tiers and Pricing Strategy

The OMNI X1 comes in two base configurations: a Basic screenless version and a Pro flagship with a high-definition display. You can also add a training bench and pull-up bar to build a complete home gym setup. This tiered approach is smart—use the basic model to lower the entry barrier, then drive average order value with premium bundles.

However, explosive crowdfunding numbers are only the opening act. Mass production, servo motor supply chain stability, overseas logistics costs, and after-sales infrastructure remain open questions. The gap between 561 Kickstarter backers and becoming a staple in Western home gyms is still massive.

Conclusion: A New Template for Chinese Fitness Hardware Going Global

The OMNI X1’s success boils down to a simple formula: identify a sharp pain point, build genuine technical differentiation, then validate demand through crowdfunding. It proves that Chinese fitness hardware has real demand in overseas markets, and it proves that the “digital resistance plus AI assistance” technical path has commercial legs.

But crowdfunding hype is merely step one. Moving from 561 backers to a genuine household name in home fitness requires crossing three major hurdles: product reputation, brand recognition, and distribution channels.

Either way, this is a space worth watching. Because any Chinese fitness device that convinces Western users to hand over $1.4 million in half a day is already saying something important.

This review is based on publicly available product information and Kickstarter campaign data. Actual user experience may vary. AICrunchX will continue tracking developments in the AI fitness hardware space.

2026-06-30