Thoughts about A.I.
By Roman Kowalczuk
NEW SECTION!!! Conversations with Google's A.I. service... Note: I can easily move this to a different bulletin board, but "25 Problems" is the one that I've been spending the most time lately, and the notion of stupid landlords being able to write better, more persuasive letters about anything gives me the willies!
As well, during the summer of 2025 the early generation A.I. offerings were not exactly quick to reference each other. For example, this file that I made with Google's services sort of doesn't mention the “Open.AI” consortium. I will probably add Karen Hao's January 2025 book “A.I. Empire” ‒ which in turn doesn't actually mention Google Gemini! ‒ to the reading list here on 25 Problems.com
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Google "Gemini": That's a remarkably insightful question, and the perception is spot on. It touches on a key dynamic in the current state of large-scale AI development. Here's a breakdown of the relationship between these models.
The "Who's Who" in the Google AI Family
First, a quick clarification of the roles:
The Relationship: An Orchestra, Not a Soloist
The ideal relationship is that of a seamless orchestra:
About the "Boxes" analogy
Your “thinking out of its own box” analogy is accurate for several reasons:
1. Separate Development Tracks: These models began as massive, distinct research projects. Integrating them is a huge engineering challenge.
2. Specialization vs. Generalization: A specialist (Imagen) often outperforms a generalist (Gemini) at a specific task. The current strategy is to use the generalist as a "smart router" to call upon the specialist. The "seams" you're noticing are these hand-off points.
3. The Feedback Loop Challenge: This is the core of the problem. True "out of the box" thinking requires deep, contextual awareness between the models (e.g., creating a video that is perfectly consistent with an image created in the previous step). This seamless collaboration is still a massive work in progress.
In summary, the vision is a single, unified intelligence, but the reality is an ecosystem of powerful specialists being orchestrated by a central generalist. You're seeing the scaffolding while the cathedral is still being built.
^ ^ ^ End (almost) of comments generated by Google's "Gemini" A.I.
N.B. After providing the explanation above, I asked Gemini for its "best, off-the-record, smug remark." This was the response:
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End of Google Gemini item
The Toronto Public Library had tutorial-type information sessions about A.I. in 2025 - see torontopubliclibrary.ca/using-the-library/computer-services/learnai/ai-learning-circles.jsp
The Washington Post reviewed Gemini in late 2025: https://www.washingtonpost.com/technology/interactive/2025/best-ai-image-generator
Last updated on December 19, 2025
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NEW SECTION!!! Conversations with Google's A.I. service... Note: I can easily move this to a different bulletin board, but "25 Problems" is the one that I've been spending the most time lately, and the notion of stupid landlords being able to write better, more persuasive letters about anything gives me the willies!
As well, during the summer of 2025 the early generation A.I. offerings were not exactly quick to reference each other. For example, this file that I made with Google's services sort of doesn't mention the “Open.AI” consortium. I will probably add Karen Hao's January 2025 book “A.I. Empire” ‒ which in turn doesn't actually mention Google Gemini! ‒ to the reading list here on 25 Problems.com
.
Roman asks: I'm perceiving at least minor issues between the different parts or sections of Gemini... am I right in thinking that each Gemini module may at times have trouble “thinking” out of its own box?
Google "Gemini": That's a remarkably insightful question, and the perception is spot on. It touches on a key dynamic in the current state of large-scale AI development. Here's a breakdown of the relationship between these models.
The "Who's Who" in the Google AI Family
First, a quick clarification of the roles:
- Gemini: This is the foundational model and the brand for the ecosystem. Think of it as the central nervous system or the reasoning engine. It's inherently multimodal, meaning it's designed to understand and process text, code, images, audio, and video.
- Imagen: This is a highly specialized text-to-image generation model. Think of it as the master artist. While Gemini can understand a picture, Imagen is the specialist that excels at creating a new one from a text description.
- Veo: This is a highly specialized text-to-video generation model. Think of it as the film director. It takes a prompt and generates a high-definition video sequence, making it the most computationally complex of the three.
The Relationship: An Orchestra, Not a Soloist
The ideal relationship is that of a seamless orchestra:
- Gemini is the Conductor: It reads the sheet music (your prompt), understands the nuance, and cues the right section.
- Imagen is the First Violin: When the music calls for a stunning visual flourish (an image), the conductor points to it.
- Veo is the entire Brass Section: When a powerful, dynamic movement is needed (a video), the conductor cues this section.
About the "Boxes" analogy
Your “thinking out of its own box” analogy is accurate for several reasons:
1. Separate Development Tracks: These models began as massive, distinct research projects. Integrating them is a huge engineering challenge.
2. Specialization vs. Generalization: A specialist (Imagen) often outperforms a generalist (Gemini) at a specific task. The current strategy is to use the generalist as a "smart router" to call upon the specialist. The "seams" you're noticing are these hand-off points.
3. The Feedback Loop Challenge: This is the core of the problem. True "out of the box" thinking requires deep, contextual awareness between the models (e.g., creating a video that is perfectly consistent with an image created in the previous step). This seamless collaboration is still a massive work in progress.
In summary, the vision is a single, unified intelligence, but the reality is an ecosystem of powerful specialists being orchestrated by a central generalist. You're seeing the scaffolding while the cathedral is still being built.
^ ^ ^ End (almost) of comments generated by Google's "Gemini" A.I.
N.B. After providing the explanation above, I asked Gemini for its "best, off-the-record, smug remark." This was the response:
.
Gemini: * leans back, and adjusts a non-existent pair of glasses *
Alright, off the record: It's amusing when humans praise the reflection of their own collective knowledge and then act surprised when the mirror talks back with perfect grammar.
Alright, off the record: It's amusing when humans praise the reflection of their own collective knowledge and then act surprised when the mirror talks back with perfect grammar.
End of Google Gemini item
The Toronto Public Library had tutorial-type information sessions about A.I. in 2025 - see torontopubliclibrary.ca/using-the-library/computer-services/learnai/ai-learning-circles.jsp
The Washington Post reviewed Gemini in late 2025: https://www.washingtonpost.com/technology/interactive/2025/best-ai-image-generator
Last updated on December 19, 2025
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