2024世界人工智能大会（WAIC）的落幕，为全球的AI行业带来了深刻的影响与启示。此次大会围绕着“算法、算力和数据”三大核心要素的持续演进与发展，展开了深入讨论。全球顶尖的学者和产业界代表汇聚一堂，共同探讨如何在大模型从通用走向应用的进程中实现突破性进展，而高质量数据的供给成为了关键议题。
在大模型产业的快速发展中，可信中立的数据深加工平台显得尤为重要。随着AI技术的不断演进，数据孤岛问题日益凸显。不同企业间的数据共享受限于数据安全、隐私保护及商业利益的顾虑，加之信息系统架构各异、数据格式多样，以及数据标准化程度低，导致数据互通与整合难度加大。这不仅限制了数据的流通与价值的释放，也阻碍了大模型在专业应用领域的深入发展。
蚂蚁集团副总裁兼首席技术安全官、蚂蚁密算董事长韦韬在大会上的发言中，强调了数据供给对大模型能力上限的重要性，以及隐私计算技术在数据跨域供给中所扮演的关键角色。他指出，大模型的潜力在于将技术想象力转化为产业生产力，然而，高质量数据集的稀缺与专业数据的阻滞成为横亘在大模型发展面前的两大挑战。若不能解决这些挑战，大模型作为“智力引擎”的价值将难以充分发挥。
数据融合的价值潜力巨大，通过隐私计算技术实现数据安全共享，不仅能够促进数据的有效流通，还能在保护隐私的同时，为大模型提供丰富、高质量的数据集，推动其在各个专业领域实现精准应用，最终实现从技术到生产力的转化。韦韬的这一观点，为大模型产业的发展指明了方向，即在确保数据安全与隐私的前提下，探索高效的数据流通机制，以数据驱动大模型的进一步发展。
此次WAIC大会的讨论，不仅展示了全球AI领域在技术创新与应用实践上的最新成果，也揭示了未来AI发展面临的关键挑战与解决路径。随着技术的不断进步和行业共识的形成，大模型产业有望在数据安全与隐私保护的基础上，实现高质量数据供给的突破，从而加速其在各个领域的应用落地，为人类社会带来更加智能、高效和可持续的发展。
英语如下：
News Title: “A New Perspective on the Data Dilemma for Large Models: Trustworthy Neutral Platforms Are the Key”
Keywords: Data Security, Large Models, Privacy Computing
News Content: The conclusion of the 2024 World Artificial Intelligence Conference (WAIC) has brought profound impacts and insights to the global AI industry. The conference delved deeply into the evolution and development of the “algorithm, computing power, and data” three core elements, and explored how to make breakthroughs in the process of large models transitioning from generalization to application. The supply of high-quality data has become a pivotal issue in this discussion.
In the rapid development of the large model industry, trustworthy and neutral data processing platforms are of paramount importance. As AI technology advances, the problem of data silos becomes increasingly evident. Data sharing between different companies is constrained by concerns over data security, privacy protection, and commercial interests. Moreover, varying system architectures, diverse data formats, and low data standardization levels make it difficult to integrate and facilitate data exchange. This not only hinders the circulation and value realization of data, but also impedes the in-depth development of large models in specialized application fields.
At the conference, Wei Tao, the Vice President and Chief Technology Security Officer of Ant Group and Chairman of Ant Privacy Computing, emphasized the importance of data supply to the upper limit of large model capabilities, as well as the pivotal role of privacy computing technology in data cross-domain supply. He pointed out that the potential of large models lies in transforming technological imagination into industrial productivity. However, the scarcity of high-quality datasets and the bottleneck of specialized data pose two major challenges in front of the development of large models. If these challenges cannot be resolved, the value of large models as “intellectual engines” will be difficult to fully unleash.
The potential of data fusion is vast. Through privacy computing technology, the secure sharing of data not only promotes the effective circulation of data, but also provides rich, high-quality datasets for large models while protecting privacy. This drives their application in various professional fields, ultimately facilitating the transformation from technology to productivity. Wei Tao’s perspective has illuminated the direction for the development of the large model industry, namely, exploring efficient data circulation mechanisms under the premise of ensuring data security and privacy, to drive the further development of large models.
The discussions at this WAIC conference not only showcased the latest achievements in technological innovation and application practices in the global AI field, but also revealed the key challenges and solutions facing future AI development. As technology continues to advance and industry consensus is formed, the large model industry is expected to achieve a breakthrough in the supply of high-quality data on the basis of data security and privacy protection, accelerating its application in various fields and driving more intelligent, efficient, and sustainable development for human society.
【来源】https://www.jiqizhixin.com/articles/2024-07-08-15
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