Algorithm-driven, experiments run lights-out: Daina Technology’s “AI + Lights-out Laboratories” enables research to think for itself.

Dyna Technology

AI + LIGHTS - OUT LABORATORIES

In January 2025, Nature identified seven “technologies most worth watching” for the year: laboratory automation, urban ecological modeling, precision medicine, environmental remediation, and others. In September 2025, the China Science and Technology Information Institute released its report “Foresight on Disruptive Technologies 2025,” which outlined 40 disruptive technologies, including “dark‑factory laboratories—fully automated, unmanned labs that achieve high‑level automation across the entire R&D, experimentation, and production process.”

Breaking Barriers: AI Reconfigures the Research Decision-Making Chain

The fundamental challenge of智能化 in traditional laboratories lies in the tension between “data silos” and “decision‑making delays.” Daina Technology’s self‑developed AI decision hub addresses this by establishing a cross‑modal perception network that seamlessly integrates heterogeneous data—such as microscopic images, environmental parameters, and equipment status—in real time, thereby creating a closed-loop system of “experiment–data–decision.” This breakthrough enables laboratories to achieve “autonomous reasoning” for the first time: AI is no longer a passive tool but a “research partner” capable of dynamically adjusting experimental parameters and optimizing workflows based on research objectives.

Fusion: Activating the Data Asset Industry Ecosystem

The ultimate value of laboratory intelligence lies in transforming experimental processes into reusable digital assets. Daina Technology’s AI + Lights-out Laboratories, powered by AI algorithms, achieves full-lifecycle management of experimental data: from sample collection to result analysis, data at every stage is encrypted and tamper-proof, creating a traceable “research digital footprint.” This innovation not only boosts the efficiency of individual laboratories but also fosters an industry‑wide data‑sharing ecosystem—through standardized interfaces, experimental parameters from different institutions can be accessed across platforms, turning even “failed experiences” into industry‑wide knowledge.

AI + LIGHTS - OUT LABORATORIES

As AI permeates the entire research pipeline—from experimental design and execution to data analysis—scientific research and production are undergoing a fundamental transformation. The traditional linear “hypothesis–experiment–validation” workflow is being replaced by a cyclical process of “AI‑generated hypotheses–robotic validation–data‑driven model optimization.” Daina Technology’s AI algorithms, leveraging reinforcement learning, are shifting research from a “labor‑intensive” to an “intellect‑intensive” paradigm. Even more profound is the cross-disciplinary integration: when real-time chemical‑experiment data is combined with biological simulation algorithms, or when material‑characterization results are fed directly into climate models, AI is breaking down disciplinary silos and giving rise to a new paradigm—“computational experimental science.”

Daina Technology’s innovative practices reveal a fundamental truth: the essence of laboratory intelligence lies not in replacing humans, but in expanding the horizons of human cognition. As robotic arms perform precision tasks in the dark and algorithms unearth patterns within vast seas of data, researchers are freed from repetitive labor, enabling them to channel their creativity toward truly disruptive scientific challenges. Meanwhile, Daina Technology’s Black‑Light Laboratory Innovation Center integrates instrumented robotics with an AI‑driven scheduling platform, forging an “intelligent operating system” for the research domain—representing not merely a technological upgrade, but a transformative reimagining of the future research ecosystem.