{"id":6663,"date":"2025-01-30T08:42:18","date_gmt":"2025-01-30T15:42:18","guid":{"rendered":"https:\/\/whitespark.ca\/?p=6663"},"modified":"2025-01-30T08:42:20","modified_gmt":"2025-01-30T15:42:20","slug":"gemini-vs-vision-ai-which-one-is-better-at-identifying-images","status":"publish","type":"post","link":"https:\/\/whitespark.ca\/blog\/gemini-vs-vision-ai-which-one-is-better-at-identifying-images\/","title":{"rendered":"Gemini vs. Vision AI: Which One Is Better at Identifying Images?"},"content":{"rendered":"\n

In part 1 of this 2-part series, we looked at the power of photos on your Google Business Profiles<\/a> (GBPs) and I shared some screenshots of Google\u2019s Cloud Vision API<\/a> not being able to identify two famous landmarks in San Francisco, California: the Golden Gate Bridge and the Japanese Tea Garden. It identified details about the images, but did not label the overall entities by name.<\/p>\n\n\n\n

Why does this matter to local brands and their marketers? Because your local SEO tasks now need to include discovering whether your image content is intelligible to AI. We want to be sure that Google understands the contents of our images as clearly as possible so that they will be able to mix and match our GBP photos to a variety of user intents across multiple image-based local business listing features.<\/p>\n\n\n\n

Thus, if Google doesn\u2019t appear to recognize that we\u2019re trying to market a landmark like the ones in my previous examples, we\u2019re in a bit of a conundrum, and that\u2019s why Darren Shaw took to Google\u2019s Gemini<\/a> to see if it could parse the Japanese Tea Garden image. We were both pleasantly surprised to see this:<\/p>\n\n\n\n

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When Darren specifically asked the app if it could identify this place, it said it resembled the Japanese Tea Garden, but that it couldn\u2019t be 100% sure. Now here\u2019s something interesting: when I also went to Gemini and uploaded the image without asking a question<\/strong>, here\u2019s what I got:<\/p>\n\n\n\n

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Gemini wasn\u2019t totally certain what Darren was showing it when he asked, but when I asked nothing and just uploaded the image, there was no uncertainty. The app correctly identified the image as this famous landmark. And, even though the Cloud Vision API couldn\u2019t identify the Golden Gate Bridge, Gemini instantly could:<\/p>\n\n\n\n

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I think it would be interesting to run some more tests in the future to see whether asking a question isn\u2019t actually the best way to see if Gemini understands an image. Maybe it\u2019s better just to plug in the picture and let the App run with it. But, a larger question looms\u2026<\/p>\n\n\n\n

So, what is going on here with the Vision API vs. Gemini?<\/h3>\n\n\n\n

I wanted to see if anyone else was noticing this difference of Gemini being able to readily identify an entire entity while Vision was only able to identify objects within the image, and I came across this video from a YouTube channel called Learn Google Cloud with Mahesh<\/em>:<\/p>\n\n\n\n

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