NVIDIA CEO Jensen Huang announced on the 13th that he won the Luminary Award at the Precision Medicine International Conference (PMWC) held in Santa Clara, California on the 7th (local time).

NVIDIA was recognized for its contributions to accelerating medical imaging, genomics, computational chemistry, and AI-based robotics. PMWC is an international conference that brings together healthcare leaders, researchers, and innovators in the biotechnology field, and the Luminary Award is given to an innovator who has contributed to the advancement of precision medicine.

NVIDIA has been advancing healthcare for over 20 years, building devices that help scientists better understand life sciences, medical imaging, and genomics.

“We have built a programmable scientific instrument for researchers and scientists who are trying to better understand life in the universe,” said CEO Jensen Huang in his acceptance speech.

Accelerated computing has been used in the life sciences field since the 2000s, and the introduction of the NVIDIA CUDA platform in 2006 suggested the possibility of utilizing GPUs in the field of medical imaging.

“NVIDIA is contributing to changing the world, including precision medicine, by developing GPUs that are at the core of AI and machine learning,” said Dr. Gad Getz of Massachusetts General Hospital. “NVIDIA AI and accelerated computing are impacting genome sequencing data analysis and interpretation, new drug development, and more, and are also contributing to educational LLMs.”

CEO Jensen Huang presented various ways in which AI can contribute to the advancement of medicine. He explained that AI investment can build a powerful flywheel that can continuously improve accuracy, efficiency, and insights through data and feedback from experts who interact with AI.

He said, “AI will revolutionize the healthcare industry, providing groundbreaking help in disease prediction, diagnosis, and treatment, and will also enable tumor evolution modeling and personalized treatment prediction through digital twins.” He also predicted, “It will be possible to understand all cells before 2030, and cell modeling, understanding cellular language, and predicting the future will become possible.”

He predicted that advances in medicine could be accelerated by surgical robots, robot caregivers, and robot laboratories, adding that AI assistants could help doctors focus on patients.