Experience: The Notebook LM as a Visual Hermeneutist
With the latest expansion, Notebook LM now accepts images as sources, opening up entirely new possibilities for analysis. For this experiment, I used AI images created in Midjourney 7 that I originally created as illustrations of my subjects on the Medium platform.
The aim was to test whether two very different images – one symbolic, the other satirical – could prompt notebook LMs to create mind maps as an unexpected form of interpretation. After the AI ​​uploads the images, Notebook LM immediately analyzes them and creates mind maps. This revealed interesting differences in how the algorithm approaches different types of visual content.
First Image: Realistic Book Earthscape
This image shows a huge open book drawn like a geographical landscape. Little people walk across its pages while a massive cloud with a geometric symbol rises above. Hot air balloons float through the scene, and lush trees frame the composition.
Notebook LM created a mind map with the following structure: Main landscape elements → massive clouds or small figures on book → surrounding figures → hot air balloons → trees and roots.
Second Image: Monkey Programmers
A satirical representation of five monkeys in cybernetic suits working on an apple laptop. The central figure leads the group while the others have mechanical attachments. The scene is full of cables, red details and high-tech aesthetics.
Notebook LM created a completely different mind map: Subjects (five monkeys, anthropomorphic style, sitting at a table) → clothing and style (main monkey in central monkey, side monkey, black robotic dress) → equipment and environment (Apple laptop, computer work, cable mess) → theme and environment (cyborg/cybernetic style, NFT/digital art aesthetics).
Mind Map Analysis: How Notebook LM Interprets Different AI Images
By analyzing the mind maps created, we can clearly see how Notebook LM has fundamentally applied different explanatory methods. Two AI images:
Structural differences in mind maps
Symbolic Image Mind Map:
- Uses organic, spatial terms (“landscape elements,” “roots,” “environment”).
- Organizes hierarchy around spatial dominance and natural relationships
- Focus on poetic connections between elements
- Creates categories based on physical positioning in space
Humorous Image Mind Map:
- Technical, cultural terms (“cybernetic style,” “NFT aesthetic,” “anthropomorphic”)
- Organizes hierarchies around functional roles and cultural categories
- Focus on object classification and style recognition
- Creates categories based on cultural and technological markers
Terminology revealed through maps
A mind map analysis shows this Notebook LM does not use a uniform analytical vocabulary but adapts its descriptive language to the nature of the content.
- For figurative imagery: “central elements,” “massive clouds,” “surrounding figures”—language suggests depth, organic, natural processes.
- For satirical image: “cybernetic style,” “digital art aesthetics,” “anthropomorphic style”—recognizing language as cultural categories, style markers, technological identities.
How brain maps reveal interpretive adaptation
A mind map comparison shows that Notebook LM can switch between different hermeneutical strategies.
For symbolic image, the algorithm is applied Spatial hermeneutics – Understanding how elements function in relation to geographies of meaning. A mind map reflects this through categories organized around physical and metaphorical positioning.
As for the satirical image, it changed Categorical classification – Understanding how elements relate to different cultural groups. A mind map shows this through a systematic categorization of subjects, styles, devices, and cultural references.
Cultural recognition through mind map analysis
One of the most impressive findings from analyzing brain maps is the cultural literacy of notebook LMs. “NFT/Digital Art Aesthetics” is included as a category in the satirical image mind map – not just a visual recognition but a cultural positioning. The algorithm understands that monkeys in a technical context refer to specific digital movements (bored monkeys yacht clubs and similar collections).
This cultural awareness is completely absent in symbolic image mind maps, which focus on universal, archetypal categories rather than contemporary cultural contexts.
Revealed in ironic motifs as interpretive challenges
Brain map analysis shows that notebook LM structurally recognizes irony. through categories such as “anthropomorphic style” and “monkey programmers”, but does not clearly define satirical work. Maps provide an analytical infrastructure for critical reading, leaving clear assessments to human interpreters.
Practical implications for creators
A mind map analysis suggests that Notebook LM can function as:
Adaptive Structural Analyzer – Changes organization rules based on content type
Cultural Pattern Detector – Identifies contemporary aesthetic movements and references
Terminology mirror – Reflects appropriate analytical language for different visual genres
Interpretive scaffolding – Provides a structured framework for human critical analysis
Hybrid interpretive processes
The most important takeaway from this mind map experiment That is, Notebook LM does not replace human interpretation, but rather creates sophisticated analytical frameworks that augment our interpretive capabilities. Mind maps serve as structural foundations upon which deep human analysis can be built.
Call for experience
This mind-mapping experiment reveals just the tip of the iceberg of Notebook LM’s visual analytics capabilities. I invite you to experience:
- Historical Artifacts – Check out how Notebook LM creates mind maps for classic paintings
- Photographic documentation – Analyze brain map structure for social document images
- Infographics – Explore how Notebook LM maps complex information concepts
- Mixed media – Combine different visual types and compare the resulting brain map structure
- Personal creations – Use your own tasks to test the limits of algorithmic classification
The future of visual analytics lies in understanding how AI creates interpretive frameworks through mind mapping. Notebook LM’s mind maps aren’t just organizational tools—they’re windows into how artificial intelligence “thinks” about visual content, revealing interpretive strategies from which we can learn and build upon.
Experiment with brain maps, analyze, and share results – each new test reveals something new about the intersection of human creativity and machine interpretation.