NVIDIA's Jensen Huang Heralds AI-Driven Industrial Revolution at HKUST Address

In a recent address at the Hong Kong University of Science and Technology, Jensen Huang, the founder and CEO of NVIDIA, discussed the transformative impact of artificial intelligence (AI) on science and industry. Huang highlighted that AI's influence is now acknowledged at the highest levels, with AI pioneers such as Geoffrey Hinton and John Hopfield being awarded the Nobel Prize in Physics for their groundbreaking work in neural networks. Other innovators, such as Demis Hassabis, have been recognized for advances in protein prediction, illustrating that these breakthroughs are just the beginning of AI's potential impact.

Huang elaborated on how companies worldwide are rapidly adopting AI to accelerate innovation and enhance productivity. He anticipates that AI agents will soon work alongside every team across diverse sectors such as marketing, sales, supply chain management, chip design, and software development. He emphasized the swift progress of cognitive AI foundational models, as well as the increasing investment in robotics technology due to new advancements in physical AI. Huang predicts that as AI transforms industries, we are on the brink of the robotic era.

Furthermore, Huang suggested that as AI revolutionizes various sectors, new industries will emerge, akin to how the industrial revolution prompted the rise of electrical power plants and the electricity industry. As AI continues to evolve, the emergence of AI factories and digital intelligence will become prominent. Reflecting on the 25 years since NVIDIA created the first GPU, Huang noted that they have redefined computing and ignited a new industrial revolution. He regards AI as the most vital technology of this era and potentially of all eras.

In his speech, Huang also described AI as inaugurating a new era of computing that touches every scientific domain and industry. AI is revolutionizing science by aiding in data analysis, accelerating simulations, providing real-time experimental control, and creating predictive models that have profoundly altered fields like drug discovery and genomics. Huang identified the redefinition of each layer of the computational stack, transitioning from logically programmed software to machine-learning models running on GPUs. The industry, according to Huang, is racing to modernize the traditional computing infrastructure through the implementation of machine learning and generative AI algorithms.