基本信息
- 来源: blogs_podcasts
- 原始来源: https://aws.amazon.com/blogs/machine-learning/scaling-data-annotation-using-vision-language-models-to-power-physical-ai-systems
来源摘要/节选
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Critical labor shortages are constraining growth across manufacturing, logistics, construction, and agriculture. The problem is particularly acute in construction: nearly 500,000 positions remain unfilled in the United States, with 40% of the current workforce approaching retirement within the decade. These workforce limitations result in delayed projects, escalating costs, and deferred development plans. To address these constraints, organizations are developing autonomous systems that can perform tasks that fill capacity gaps, extend operational capabilities, and offer the added benefit of around-the-clock productivity.
Building autonomous systems requires large, annotated datasets to train AI models. Effective training determines whether these systems deliver business value.…
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