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OpenAI’s GPT-5.2 and Image-gen-2: A Last Challenge to Google’s Dominance?

GPT 5.2 and Image-gen-2 from Open AI - A final swing at Google?

Welcome Back to Matt Vidpro AI

Hello everyone! Welcome back to another exciting episode on the Matt Vidpro AI YouTube channel. I hope you’re all having a fantastic day as we look ahead to 2026. As the year draws to a close, AI companies are racing to launch their final projects, eager to keep their competitive edge in this rapidly evolving landscape.

The AI Competition

This year’s biggest rivalry has been between Google and OpenAI, and things are heating up. Today, we’re diving into a newly designed human cell diagram created by Hazel Gen 2, a model shrouded in some mystery and currently sparking discussions in AI testing realms.

Community members are buzzing with confidence that this diagram is actually the work of OpenAI, reminiscent of their previous releases. It’s being compared to Google’s powerhouse, the Nano Banana Pro, which has set the bar incredibly high. Personally, I’ve been using Nano Banana Pro for my thumbnails, and I must say, it’s the most advanced AI image generator I’ve encountered to date.

Analyzing the Human Cell Diagram

The prompt for this diagram came from Simon Smith, who requested a fully labeled diagram of a human cell with at least ten elements, ensuring that the labels are precise and accurate. So, how well did Hazel Gen 2 execute this task?

Successes of the Diagram

Right off the bat, there are several elements that the model got right! The label “human cell” is correctly spelled at the top, and we can see the plasma membrane identified adequately, showing notable detail. Other elements noted include:

  • Cytoskeleton
  • Centrosome
  • Lysosome
  • Mitochondria
  • Golgi apparatus
  • Vesicle
  • Ribosomes
  • Smooth and rough endoplasmic reticulum

Overall, the text labels appear fairly accurate.

Areas for Improvement

Now, let’s take a closer look at some aspects that might need refinement. First up, the Golgi apparatus—its representation doesn’t seem entirely accurate. The diagram shows it as a scrambly, wavy structure, which leads me to question its labeling. And while ribosomes are marked, they are depicted quite simplistically as mere dots.

Another notable detail is that the model seems to confuse the vesicle with the mitochondria, which is a significant error in cell anatomy representation.

Conclusion

In summary, Hazel Gen 2 has done a commendable job in accurately labeling numerous components of the human cell diagram but still has some areas that need fine-tuning. As AI continues to develop, it will be exciting to see how these models improve and compete against industry giants like Google.

Thanks for tuning in! If you enjoyed today’s analysis, don’t forget to like and subscribe for more insights on the latest in AI technology. See you in the next video!



#GPT #Imagegen2 #Open #final #swing #Google
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21 thoughts on “OpenAI’s GPT-5.2 and Image-gen-2: A Last Challenge to Google’s Dominance?

  1. I'm noticing multiple mistakes on the output already. One of them says 2 teaspoons, yet on the illustration it shows a large wooden spoon. The other issue they have is the ROI damage of AI due to expensive RAM, expensive chips, multiple defects and expensive electricity.

  2. The amount of synthetic data used in pre-training used in Gemini 3 and GPT 5.2 is insane.. Likely spending equal amount of compute to generate/inference synthetic verifiable data structures as was spent on pertaining and rlsft. Curious if the performance improved because both are using geometric deep learning in their architectures.. Both using sparse MOE models. I think both of them are producing long run planning datasets for the next iteration allowing for greater reasoning forecasting depth.

  3. 2 giants of art theft fighting it out.. anyone really care?

    In other news if you want to use Gen AI in your show and run it at the Sydney Opera House you will need to prove you have rights to use all imagery/video/music etc.

    And that means, unless you use genuine public domain trained models , your show cant go ahead. It would be considered theft.

  4. I think we can be sure that at $22 input and wait for it $168 output per million – well no OpenAI are not 'Swinging at Google' they seem to be too busy doing crack or something – seriously what are they thinking? What dev can afford $168 per million tokens thats – crazy!

  5. GPT needs to stop trying to be the everything AI and competing with Google. They should niche down like Claude has. Google has cornered video and images. But if gpt had been more focused they could still be on top in document generation. Instead, I'm using Claude more and more because gpt 5.1 has fallen behind. I still use it for all brainstorming but when I'm ready to really start working on real drafts, I take my outlines and notes to Claude. I even increased my monthly payment with Claude to get more messages. I think OpenAI is too distracted on things like the Sora app that are just dumb novelties. They should leave stuff like that for developers who want to create apps and will pay for the API, not for their own developers to have to work on and maintain.

  6. Chai comes from a box. No?

    I’m stoked about 5.2. Was there any doubt? Also no. It’s the best… for so many reasons. 💥

    GPT 5.1 is slated for deprecation. Everything else stays in the legacy drop down. 👏 SVM and 4o is still the best combination but it’s nice to be poly-AI-amorous because nano banana pro in AI Studio is next level for a variety of reasons.

    Thanks Matt. Claude is very good… not lazy but lacks features. It’s has a determination to finish a task no matter what. Q

  7. I like how everybody's still impressed with this slow iterative advancement. For 5 months now I've had a 4-bit quantized 500 B model that I custom developed that literally beats every unsolved Benchmark in every domain. And it cost me $0 to operate essentially. The only reason that this seems impressive is because the industry blocks out all other development Pathways so that they can seem impressive when they release some iterative junk like this

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