A humanoid robot works on a factory line, showcasing advanced automation in real-world production. PHOTO: AGIBOT
Robots that learn on the job: AgiBot tests reinforcement learning in real-world manufacturing.
Updated
November 27, 2025 3:26 PM
A humanoid robot works on a factory line, showcasing advanced automation in real-world production. PHOTO: AGIBOT
Shanghai-based robotics firm AgiBot has taken a major step toward bringing artificial intelligence into real manufacturing. The company announced that its Real-World Reinforcement Learning (RW-RL) system has been successfully deployed on a pilot production line run in partnership with Longcheer Technology. It marks one of the first real applications of reinforcement learning in industrial robotics.
The project represents a key shift in factory automation. For years, precision manufacturing has relied on rigid setups: robots that need custom fixtures, intricate programming and long calibration cycles. Even newer systems combining vision and force control often struggle with slow deployment and complex maintenance. AgiBot’s system aims to change that by letting robots learn and adapt on the job, reducing the need for extensive tuning or manual reconfiguration.
The RW-RL setup allows a robot to pick up new tasks within minutes rather than weeks. Once trained, the system can automatically adjust to variations, such as changes in part placement or size tolerance, maintaining steady performance throughout long operations. When production lines switch models or products, only minor hardware tweaks are needed. This flexibility could significantly cut downtime and setup costs in industries where rapid product turnover is common.
The system’s main strengths lie in faster deployment, high adaptability and easier reconfiguration. In practice, robots can be retrained quickly for new tasks without needing new fixtures or tools — a long-standing obstacle in consumer electronics production. The platform also works reliably across different factory layouts, showing potential for broader use in complex or varied manufacturing environments.
Beyond its technical claims, the milestone demonstrates a deeper convergence between algorithmic intelligence and mechanical motion.Instead of being tested only in the lab, AgiBot’s system was tried in real factory settings, showing it can perform reliably outside research conditions.
This progress builds on years of reinforcement learning research, which has gradually pushed AI toward greater stability and real-world usability. AgiBot’s Chief Scientist Dr. Jianlan Luo and his team have been at the forefront of that effort, refining algorithms capable of reliable performance on physical machines. Their work now underpins a production-ready platform that blends adaptive learning with precision motion control — turning what was once a research goal into a working industrial solution.
Looking forward, the two companies plan to extend the approach to other manufacturing areas, including consumer electronics and automotive components. They also aim to develop modular robot systems that can integrate smoothly with existing production setups.
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Can SPhotonix’s optical memory technology protect data better than today’s storage?
Updated
December 17, 2025 2:47 PM
SPhotonix's 5D Memory Crystals™. PHOTO: SPHOTONIX
SPhotonix, a young deep-tech startup, is working on something unexpected for the data storage world: tiny, glass-like crystals that can hold enormous amounts of information for extremely long periods of time. The company works where light and data meet, using photonics—the science of shaping and guiding light—to build optical components and explore a new form of memory called “5D optical storage”.
It’s based on research that began more than twenty years ago, when Professor Peter Kazansky showed that a small crystal could preserve data—from the human genome to the entire Wikipedia—essentially forever.
Their new US$4.5 million pre-seed round, led by Creator Fund and XTX Ventures, is meant to turn that science into real products. And the timing aligns with a growing problem: the world is generating far more digital data than current storage systems can handle. Most of it isn’t needed every day, but it can’t be thrown away either. This long-term, rarely accessed cold data is piling up faster than existing storage infrastructure can manage and maintaining giant warehouses of servers just to keep it all alive is becoming expensive and environmentally unsustainable.
This is the problem SPhotonix is stepping in to solve. They want to store huge amounts of information in a stable format that doesn’t degrade, doesn’t need electricity to preserve data and doesn’t require constant swapping of hardware. Instead of racks of spinning drives, the idea is a durable optical crystal storage system that could last for generations.
The company’s underlying technology—called FemtoEtch™—uses ultrafast lasers to engrave microscopic patterns inside fused silica. These precisely etched structures can function as high-performance optical components for fields like aerospace, microscopy and semiconductor manufacturing. But the same ultra-controlled process can also encode information in five dimensions within the crystal, transforming the material into a compact, long-lasting archive capable of holding massive amounts of information in a very small footprint.
The new funding allows SPhotonix to expand its engineering team, grow its R&D facility in Switzerland and prepare the technology for real-world deployment. Investors say the opportunity is significant: global data generation has more than doubled in recent years and traditional storage systems—drives, disks, tapes—weren’t designed for the scale or longevity modern data demands.
While the company has been gaining attention in research circles (and even made an appearance in the latest Mission Impossible film), its next step is all about practical adoption. If the technology reaches commercial viability, it could offer an alternative to the energy-hungry, short-lived storage hardware that underpins much of today’s digital infrastructure.
As digital information continues to multiply, preserving it safely and sustainably is becoming one of the biggest challenges in modern computing. SPhotonix’s work points toward a future where long-lasting, low-maintenance optical data storage becomes a practical alternative to today’s fragile systems. It offers a more resilient way to preserve knowledge for the decades ahead.