Grossi Enzo
Villa Santa Maria Foundation, Tavernerio, Italy.
Clin Exp Rheumatol. 2025 May;43(5):815-821. doi: 10.55563/clinexprheumatol/oamfed. Epub 2025 May 8.
Artificial intelligence (AI) has its roots in the history of philosophy and of applied mathematics of the 17th, 18th and 19th centuries. Throughout the 20th century, significant advancements in mathematics and computer science laid the groundwork for modern AI, culminating in the establishment of the field as a formal discipline during the Dartmouth Conference in 1956.This pivotal event brought together leading researchers who envisioned creating machines capable of simulating human intelligence, setting the stage for decades of research and innovation in the field. The development of early AI systems focused on problem-solving and symbolic reasoning, leading to the creation of programmes that could play games like chess and solve mathematical equations, which show-cased the potential of machines to perform tasks previously thought to require human intellect.As these foundational systems evolved, researchers began to explore more complex algorithms and learning models, paving the way for advancements in machine learning and neural networks that would eventually revolutionise AI applications across various fields among which medicine. The growth of big data and increased computational power further accelerated these advancements, enabling machines to analyse vast amounts of health information and learn from patterns at unprecedented speeds.The revolution of deep learning and soon after large language models has enabled machines to achieve remarkable feats, such as image and speech recognition, natural language processing, and even creative tasks like art generation, pushing the boundaries of what was once thought possible. As organisations grapple with these challenges, there is growing emphasis on developing frameworks that ensure responsible AI deployment while maximising its potential benefits for human health.
人工智能(AI)起源于17、18和19世纪的哲学与应用数学历史。在整个20世纪,数学和计算机科学的重大进展为现代人工智能奠定了基础,最终在1956年的达特茅斯会议上该领域作为一门正式学科得以确立。这一关键事件汇聚了顶尖研究人员,他们设想创造能够模拟人类智能的机器,为该领域数十年的研究与创新奠定了基础。早期人工智能系统的发展聚焦于问题解决和符号推理,催生了能够下国际象棋等游戏以及解数学方程的程序,展示了机器执行此前被认为需要人类智慧才能完成的任务的潜力。随着这些基础系统的演进,研究人员开始探索更复杂的算法和学习模型,为机器学习和神经网络的进步铺平了道路,而这最终将彻底改变包括医学在内的各个领域的人工智能应用。大数据的增长和计算能力的提升进一步加速了这些进步,使机器能够以前所未有的速度分析大量健康信息并从模式中学习。深度学习的革命以及随后的大语言模型使机器能够实现非凡成就,如图像和语音识别、自然语言处理,甚至艺术创作等创造性任务,突破了曾经被认为可能的界限。随着各组织应对这些挑战,人们越来越强调开发框架,以确保负责任地部署人工智能,同时最大限度地发挥其对人类健康的潜在益处。