In recent years, the popularity of artificial intelligence (AI) has provided a new incentive for advances in science and technology in the laser industry, further promoting its rapid development and wide application. To present a clear view of the empowering effect of AI on lasers and facilitate further development of this emerging field, it is important to identify the advancements, opportunities, and challenges of AI-enabled lasers. Therefore, this work begins with a review of the progress in this field, from component design to system optimization and from laser property characterization to laser application. Then, we provide a preliminary analysis and outlook on the opportunities, challenges, and two-way empowerment of the laser and AI disciplines.
By analyzing published research articles indexed in the Web of Science, AI-assisted laser development can be divided into five parts: optimal design of laser components, optimal design of laser systems, intelligent control and optimization of laser beams, accurate characterization and prediction of laser properties, and optimization of laser application effectiveness. Regarding the optimal design of laser components, AI-assisted device design not only improves design efficiency but also allows better parameter optimization, which can aid optimization of laser systems and can play an important role in laser generation, transmission, and application. In terms of the optimal design of laser systems, AI can avoid complex physical principles for modeling and establish mapping between the laser performance and structural parameters, which accelerates the optimum design of the laser system for improved performance. Regarding intelligent control and optimization of laser beams, one example is the coherent beam combination (CBC). The control bandwidth is a bottleneck that limits implementation of large-scale CBC systems. An AI-assisted CBC system can overcome this limitation, and methods for coherently combining more than 100 beams are proposed. For the accurate characterization and prediction of laser properties, AI-enabled characterization technology can secure fast, accurate, and robust characterization of the mode content, beam quality, and pulse duration of lasers and shows great potential for the characterization of other properties of laser beams. In terms of the optimization of laser application effectiveness, AI can ignore the complex, highly nonlinear physical problems of light-matter interactions that occur during the laser-machining process and can achieve high-quality laser cutting/welding/additive manufacturing by establishing a mapping between the laser parameters and the processing quality.
In summary, AI technology is widely applied in laser research and applications. However, the rapid development of laser technology may also have a catalytic effect on the field of AI, ultimately creating a positive incentive for ‘two-way empowerment.'
AI-assisted lasers are expected to promote innovation and development of laser technology at the material, device, and system levels. At the material level, AI can help analyze and select laser materials by facilitating in-depth exploration of traditional optical fibers, semiconductors, and other materials, and expand the boundaries of the use of existing materials by improving their performance. At the device level, AI can revolutionize the design and development of laser-related devices. Data-driven modeling can provide theoretical analysis tools for complex laser phenomena and reveal the deeper physical mechanisms. Highly accurate device models can serve for the reverse design of specific device characteristics and enable multidimensional and comprehensive device function customization. At the system level, AI can provide efficient tools for the integration of laser systems, allowing for the simulation of operations during the system development phase, timely identification of potential problems, and efficient shaping and implementation of large and complex laser systems. AI-driven scientific research is a new frontier of AI, which has already been effective in several disciplines and is expected to inspire further breakthroughs in the future.
AI-assisted lasers not only result in breakthroughs in laser-performance indicators but also lead to breakthroughs in laser concepts, which may gradually become an enabling technology that is "used every day without realizing it" and can make future laser systems more attractive.
Furthermore, the development of laser technology can contribute to further development of AI by advancing arithmetic power. The current electronic computing performance relies on semiconductor lithography processes, and laser light sources are important factors supporting the continuous progress of lithography processes. In the future, laser-enabled ultra-computing photonic computers will hopefully drive AI technology.
AI-driven scientific research is a new frontier in AI worldwide and is effective in several disciplines, and the next five years are a critical window for its breakthrough development. In addition to the cross-fertilization of different disciplines in the scientific research process, the development of interdisciplinary and highly qualified personnel during the process of scientific research and education is a long-term strategy for the future.
Looking ahead, there are both opportunities and challenges; however, evolving AI technologies will certainly continue to facilitate the development of disciplines, such as lasers, and gradually build a new paradigm of basic and cutting-edge research supported by AI.
