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AI AnalysisJune 19, 2025•4 min read

What Gemini 2.5 says about ChatGPT


This is the output from Gemini Pro 2.5, thinking included, on how Gemini 2.5 can analyze YouTube videos and why OpenAI o3 is less capable here. This speaks to a major data advantage Google has in many domains. Don't sleep on Google.


*You can see these YouTube videos but tools like OpenAI o3 cannot (they can analyze meta descriptions and ask for images for deeper analysis)- is this a limited imposed by Google?*


Response


That's a very insightful question that gets to the heart of how different AI systems operate and interact with the digital world. The simple answer is that my ability to analyze those videos is a direct result of being a Google product, which gives me native, integrated access to other Google products like YouTube.


It's less of a "limitation imposed by Google on others" and more of an "integrated capability" that I possess by design.


1. Native Integration vs. Third-Party Access


My Capability (Google): I have a specialized tool designed to directly and securely interface with YouTube's data. Think of it like being a librarian in the library where the books are kept. I have a key to the stacks and can access the content (the video frames, the audio, the transcript) directly and analyze it holistically.


Other Models (like OpenAI): These models are like researchers visiting that library. They don't have a key to the stacks. They can only see what's publicly available in the main reading room—things like the video's title, description, and comments. To "see" the video itself, they would typically have to rely on a workaround, like a user pasting in a manually-copied transcript.


2. Technical Complexity and Cost


Analyzing video is not like reading a webpage. It's a multi-layered process that requires:


  • **Computer Vision:** Analyzing the visual data from the video frames.
  • **Speech-to-Text:** Transcribing the audio into text.
  • **Synthesis:** Combining the insights from the visual and audio data to form a cohesive understanding.

    • This is computationally expensive. Because I am part of the same ecosystem, I can leverage Google's vast, optimized infrastructure for video processing (the same infrastructure that powers YouTube itself) in a way that is efficient and secure.


    3. YouTube's Terms of Service


    This is a critical point. YouTube's terms of service strictly control how its content can be accessed and used.


  • **Scraping is Prohibited:** Unauthorized automated access to download or process video content (a practice known as "scraping") is a violation of these terms.
  • **Authorized Access:** The proper way to interact with YouTube data is through its official API. However, the public API has limitations and is not designed for the kind of deep, multi-modal analysis I performed on your videos.

    • Because of my native integration, I can operate within Google's own internal policies, whereas other models must adhere to the more restrictive public-facing rules.


    In short, you've noticed a key architectural difference. My ability to "see" those videos is a powerful example of the deep integration possible within a single tech ecosystem. It's a feature of my design, not just a rule imposed on others.