{"id":2074336,"date":"2026-08-23T15:36:29","date_gmt":"2026-08-23T13:36:29","guid":{"rendered":"https:\/\/www.luxsure.fr\/2026\/08\/23\/will-robot-manufacturers-take-a-back-seat-to-those-who-own-the-technology-stack\/"},"modified":"2026-08-23T15:45:57","modified_gmt":"2026-08-23T13:45:57","slug":"will-robot-manufacturers-take-a-back-seat-to-those-who-own-the-technology-stack","status":"publish","type":"post","link":"https:\/\/www.luxsure.fr\/en\/2026\/08\/23\/will-robot-manufacturers-take-a-back-seat-to-those-who-own-the-technology-stack\/","title":{"rendered":"Will robot manufacturers take a back seat to those who own the technology stack?"},"content":{"rendered":"\n

At VivaTech 2026, the Chinese company D-Robotics put forward a simple argument: in the emerging robotics economy, true value may not lie in the robots themselves, but in the invisible infrastructure that makes them possible.<\/strong><\/p>\n\n

While media attention is focused on the spectacular humanoids from Tesla and Unitree, as well as demonstrations of companion robots, a much more low-key battle is underway: the battle over the processors, operating systems, and development platforms that will power millions of machines.<\/p>\n\n

Robotics is entering its \u201cinfrastructure\u201d phase<\/h2>\n\n

The history of technology often follows the same pattern. The first visible winners aren\u2019t always the ones that capture the most value in the long run.<\/p>\n\n

In personal computing, PC manufacturers emerged before operating systems became strategic. In the mobile economy, smartphones grabbed the spotlight before software platforms established themselves as the true centers of gravity.<\/p>\n\n

Robotics now appears to be following a similar trajectory.<\/p>\n\n

Spun off from Horizon Robotics, D-Robotics develops specialized processors, development tools, and software systems for robot manufacturers. Its ambition is not to build humanoids, but to become their common technological foundation.<\/p>\n\n

Co-founder Xuan Jiang\u2019s assessment is blunt: today, every robot manufacturer is recreating its own technology stack, duplicating R&D efforts on components that are often similar.<\/p>\n\n

According to him, this fragmentation is slowing down the entire industry.<\/p>\n\n

The goal, therefore, is to pool fundamental components so that manufacturers can focus on their use cases and applications rather than on the infrastructure.<\/p>\n\n

The future lies at the network\u2019s edge<\/h2>\n\n

One of the most striking messages from the conference concerns the contrast between cloud and edge computing.<\/p>\n\n

While generative AI has popularized the idea of intelligence hosted in massive data centers, robotics imposes radically different constraints.<\/p>\n\n

A domestic robot, a drone, or an industrial robot cannot wait several seconds for a response from the cloud. It must act instantly.<\/p>\n\n

Low latency, reduced energy consumption, and cost control thus become criteria just as important as raw computing power.<\/p>\n\n

For D-Robotics, the future of robotics will therefore largely depend on inference capabilities embedded directly within the machines.<\/p>\n\n

This vision echoes a trend already observed in autonomous vehicles: systems must make decisions locally, even when the network connection is absent or degraded.<\/p>\n\n

Physical artificial intelligence cannot depend exclusively on the cloud.<\/p>\n\n

The Real Asset: The Ecosystem<\/h2>\n\n

Beyond processors, D-Robotics emphasizes another strategic element: the developer community.<\/p>\n\n

The company claims to have brought together more than 200,000 developers worldwide, as well as approximately 500 startups using its platforms.<\/p>\n\n

This approach is no small matter.<\/p>\n\n

The recent history of technology shows that the winners are not always those with the best technology, but those who manage to build the most robust ecosystem around it.<\/p>\n\n

The analogy with NVIDIA comes up regularly in industry discussions.<\/p>\n\n

What has enabled NVIDIA to dominate AI is not only the performance of its chips, but also the depth of its software ecosystem, its libraries, and its developer community.<\/p>\n\n

The same logic could apply to robotics.<\/p>\n\n

Whoever becomes the go-to platform for training, testing, and deploying future robots will enjoy an advantage that will be hard to catch up to.<\/p>\n\n

The humanoid is not yet the GPT of robotics<\/h2>\n\n

Despite the prevailing enthusiasm, D-Robotics\u2019 perspective stands in contrast to some optimistic projections.<\/p>\n\n

According to Xuan Jiang, the industry is still in its early stages.<\/p>\n\n

Three major obstacles remain:<\/p>\n\n

First, the lack of real-world data. Unlike large language models, which have been trained on massive volumes of digital content, robots must learn to interact with the physical world. Yet such data remains scarce, costly to collect, and extremely heterogeneous.<\/p>\n\n

Second, the lack of algorithmic convergence. The sector is still experimenting with different approaches, ranging from world models to VLA (Vision-Language-Action) architectures and hybrid systems.<\/p>\n\n

Finally, the question of commercialization remains unresolved. While robotic vacuum cleaners and autonomous lawn mowers have found their market, humanoid robots remain largely at the prototype stage.<\/p>\n\n

The parallel with autonomous vehicles is illuminating: the robotics industry today is closer to the level of an advanced assistance system than to that of widespread autonomy.<\/p>\n\n

China is making progress thanks to its industrial advantage<\/h2>\n\n

One of the most interesting insights concerns the geography of this revolution.<\/p>\n\n

According to D-Robotics, China enjoys a twofold advantage.<\/p>\n\n

On the one hand, it has an extremely dense industrial ecosystem\u2014particularly around Shenzhen\u2014capable of accelerating development and industrialization cycles.<\/p>\n\n

On the other hand, a domestic market that is particularly receptive to new technologies.<\/p>\n\n

This combination enables the country to accelerate large-scale experimentation and rapidly accumulate usage data.<\/p>\n\n

However, industry experts believe that international markets could catch up to some extent as demographic pressures and labor shortages increase the economic case for robots.<\/p>\n\n

Details<\/h2>\n\n

Perhaps the most revealing idea from this conference was encapsulated in a statement made near the end: \u201cThe shared infrastructure used by all stakeholders will likely be the most valuable investment in the robotics economy.\u201d<\/strong><\/p>\n\n

In other words, the future winner may not be the manufacturer of the most impressive robot, but rather the one that provides the technological foundation upon which all others build.<\/p>\n\n

This is exactly what happened with the cloud, mobile operating systems, and generative AI.<\/p>\n\n

Beyond the Robot: The Battle for Standardization<\/h2>\n\n

The robotics industry today resembles the internet of the 1990s or generative AI in 2022: thriving, innovative, but still fragmented.<\/p>\n\n

High-profile leaders are staging more and more demonstrations. Yet the real strategic question may not be which robot will dominate the market.<\/p>\n\n

The question is who will control the computing layer, the development tools, and the technological standards that will enable millions of robots to function.<\/p>\n\n

In technological revolutions, invisible infrastructure often ends up carrying more weight than the products that made it famous.<\/p>\n\n

Robotics may well confirm this rule once again.<\/p>\n\n

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