Speaker
Description
Currently, AI technology is demonstrating a development trend of multipoint breakthroughs and interdisciplinary convergence. At the algorithm level, breakthroughs in large model technologies have driven generative AI to achieve qualitative leaps, while technologies such as deep reasoning and multimodal fusion continue to expand cognitive boundaries. At the computing level, the energy efficiency ratio of AI chips continues to improve, and extreme engineering optimization enables sustained computing power release. At the data level, high-quality industry datasets and synthetic data provide new momentum for model training and application development. Technological iterations are accelerating AI industrialization and driving intelligent applications across industries to flourish. AI technology is speeding up the "innovation-transformation-application" cycle, injecting new productive forces into various sectors and promoting the co-evolution of technological and economic systems, thereby reshaping industrial value networks. This presentation will cover the current state of AI development, challenges facing infrastructure, and future trends, aiming to exchange insights and discuss future prospects with all participants.
