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The AI in Business Podcast

[Beyond GPU] A Closer Look at Manufacturing Challenges for Computer Vision - with Peter Tu of GE Research

Sep 23, 2023
19:29
Snipd AI
In this episode, Peter Tu, Chief Scientist of Computer Vision at GE Research, discusses the advances in real-time cloud computing for computer vision in manufacturing. He explores the challenges of incorporating subjective questions into computer vision systems and the process of implementing these systems. Tu also highlights the importance of understanding the environment and ontology of objects and actions when adopting AI in manufacturing. Finally, he explores the role of computer vision in predictive inventory and teases upcoming episodes in the Beyond GPU series.
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Podcast summary created with Snipd AI

Quick takeaways

  • Data annotation and complexity pose challenges for computer vision in manufacturing.
  • Integration of subject matter experts and understanding data structures are crucial for AI adoption in manufacturing.

Deep dives

Challenges in Computer Vision for Manufacturing

One of the main challenges in computer vision for manufacturing is dealing with the complexity and judgment-based nature of the tasks. While some manufacturing decisions can be straightforward, others require more subjective judgment. This poses a challenge in defining and annotating the data with clarity. Another challenge is the increasing amount of data required to support these tasks, as models are getting bigger and demand larger datasets. Although few-shot learning approaches are emerging, the reliance on large datasets and highly skilled annotations still persists.

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