分析预训练模型应用，挖掘AI创新机会点
Exploring the Innovation Opportunities for Pre-trained Models
- 通过人机交互研究中的实际应用，识别预训练模型的可行场景
- 发现模型在真实需求、技术能力与伦理规避三方面表现突出
- 适合关注AI产品化落地的开发者和创新者参考
创新者通过理解服务如何有效满足用户需求，进而发现可靠的创新机会。预训练模型已改变AI创新格局，使新AI产品和服务的开发更迅速、更便捷。了解预训练模型的实际成功领域对支持AI创新至关重要。然而，当前预训练模型的炒作周期使人们难以判断其真正可行的应用场景。为此，我们以人机交互（HCI）研究者的应用为代理，分析具有潜力的商业化应用。这些研究应用展现了技术能力，回应了真实用户需求，并规避了伦理风险。采用物证分析法，我们对能力类型、创新领域、数据类型及新兴交互设计模式进行了分类，揭示了预训练模型在创新中的潜在空间。
原文摘要 · Abstract (English)
Innovators transform the world by understanding where services are successfully meeting customers' needs and then using this knowledge to identify failsafe opportunities for innovation. Pre-trained models have changed the AI innovation landscape, making it faster and easier to create new AI products and services. Understanding where pre-trained models are successful is critical for supporting AI innovation. Unfortunately, the hype cycle surrounding pre-trained models makes it hard to know where AI can really be successful. To address this, we investigated pre-trained model applications developed by HCI researchers as a proxy for commercially successful applications. The research applications demonstrate technical capabilities, address real user needs, and avoid ethical challenges. Using an artifact analysis approach, we categorized capabilities, opportunity domains, data types, and emerging interaction design patterns, uncovering some of the opportunity space for innovation with pre-trained models.
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