Ed Goffin

The development of machine vision interfaces highlights new technologies, such as PCIe and Thunderbolt, that improve performance and integration across various applications. Additionally, the upcoming GigE Vision 3.0 standard aims to enhance CPU utilization through the use of RDMA technology.

AI, despite its hype, often causes delays in manufacturers' automation strategies due to confusion and fear. Fundamentally, AI complements machine vision, which uses handcrafted algorithms needing new formulas and trial-and-error development for each product type or feature.

As technology gets easier to use, vision and AI application design is no longer restricted to expert-level developers. A quality manager or IT operations staff can design, train, and deploy their own customizable workflow.

Brand appearance plays a significant role in consumer choice, and the manufacturer competes against larger players with much deeper marketing budgets.

Manufacturers and brand owners are under tremendous pressure to ensure premium end-to-end product quality, especially as consumers increasingly demand perfection. And a great deal of that product quality pressure still falls on human visual inspection.

While artificial intelligence (AI) is gaining favor as a solution to quality problems, it brings a number of new, sometimes confusing, terms. As a first step, many manufacturers ask “What is AI?”

Artificial intelligence (AI) is one of the most hyped technologies of recent years, and while it promises new cost and process benefits for inspection applications, deployment remains a challenge.

Thanks in large part to its ease of use, USB dominates consumer-to-computer connectivity applications and is being rapidly adopted across other markets. 

Video interfaces and cabling have played a significant role in bringing new capabilities to machine vision and supporting automation’s migration into a broadening range of markets.