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How Can GenAI Revolutionize Visual Recognition Technology?



While AI vision capabilities like Google Cloud Vision or Python libraries have been available for over a decade, helping perform text, object classification, and image recognition, a new wave of "GenAI Vision" (GPT4 Vision, Gemini 1.5, Claude) models is taking things to another level and at a cost point that makes it available to small and mid-sized businesses.

 

What sets GenAI Vision apart? It goes beyond just identifying objects, text, or labels in an image. GenAI can analyze an image, comprehend the contents, and then generate new content explaining, interpreting, and expanding on what it perceives.

 

Here are some of the ways we see GenAI vision working:

 

  • Architecture & Design Feed it an architectural drawing or blueprint, and GenAI Vision can describe the proposed design, analyze the materials and techniques, and even suggest potential improvements or modifications.  Still a work in progress, but very promising over the next 6-9 months.

 

  • Manufacturing & Assemblies For complex equipment, wiring, or machine assemblies, GenAI can study an image, understand the components and how they fit together, and provide insights into the engineering behind it.

 

  • Industrial Equipment Analysis Give it a photo of a manufacturing line or heavy machinery, and it can interpret what it sees - identifying components, evaluating operational status, and troubleshooting potential issues and risks.

 

  • Inspection Utilizing GenAI's visual intelligence capabilities, inspections in sensitive environments like restaurants or high-risk facilities can now be conducted remotely and automatically generate detailed status reports or alerts in natural language.

 

GenAI can comprehensively analyze the visual data and generate rich, contextualized assessments summarized in natural language by ingesting images or video feeds from a location.

 

The true power of GenAI Vision lies in its ability to not just perceive objects, but to understand their significance and relationships within the broader context. While conventional computer vision might label components like "pipes" or "wire", GenAI takes it further by explaining: "These appear to be high-pressure hydraulic actuators integrated into an industrial stamping machine assembly line."

 

This deeper comprehension unlocks insights previously inaccessible to AI. However, for certain tasks like precise OCR text extraction, traditional cloud vision models can still outperform GenAI's current capabilities. But by further finetuning on visual data, GenAI vision models may eventually supersede legacy solutions entirely.

 

Whether operating standalone or seamlessly integrating with existing AI, GenAI introduces transformative new opportunities to extract rich, contextual intelligence from visual data. And it does so at a cost and implementation ease previously unattainable with cutting-edge technology.

 

Across engineering, manufacturing, architecture, and countless other domains - we are entering an era where GenAI vision will be indispensable for analyzing and gleaning insights from the visually informative world around us. The age of perceptive, generative AI vision has arrived.

 

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