Here is a self-contained, interactive digital exhibition of an autonomous multimodal experiment, heavily inspired by the speculative, bio-political, and avant-garde aesthetic of we-make-money-not-art.
For this iteration, I focused the "multimodal in/out" engine on the intersection of surveillance capitalism, ecological collapse, and speculative biomimicry. The system ingested two hypothetical inputs (CCTV video streams of automated logistics centers and the chemical distress signatures of collapsing bee colonies) and hallucinated a speculative biological output.
Save the code block below as experiment_042.html and open it in any modern web browser. It is a fully styled, responsive, visually striking package containing generative SVG art, CSS animations simulating multimodal processing, and the conceptual manifesto.
VIDEO (10,000 hrs) CHEMICAL SENSOR DATA
The model was fed continuous CCTV streams of automated logistics warehouses (Amazon / Foxconn) multiplexed with atmospheric olfactory data capturing the distress pheromones (Isoamyl acetate) of the collapsing Bombus affinis (rusty patched bumble bee) population in the American Midwest.
Tasked with resolving the cognitive dissonance between rampant e-waste proliferation and biological collapse, the Flash3.7 architecture bypassed traditional textual analysis.
Instead, it cross-pollinated the rigid, orthogonal geometry of circuit boards with the organic, emergent behavior of hive construction. The output is a speculative biological blueprint for an extremophile mycelium designed to metabolize discarded lithium-ion batteries.
The model generated two distinct multimodal outputs: a visual SVG blueprint of the organism's growth pattern, and a synthetic scent profile designed to attract drone pollinators to e-waste dumps.
Fig 1. Model's native SVG rendering of 'Lithium-Mycelium', illustrating aggressive rhizomatic infiltration of a standardized PCB grid.
To ensure the mycelium successfully integrates into the urban ecosystem, the model generated a synthetic scent designed to mimic the volatile organic compounds found in both dying electronics and blooming flora.
{
"scent_profile": "Petrichor-Silicon",
"base_notes": {
"Geosmin": "45%",
"Ozone (O3)": "20%"
},
"middle_notes": {
"Burnt Kapton Tape": "15%",
"Isoamyl acetate (Bee Alarm)": "10%"
},
"top_notes": {
"Heated Copper": "10%"
},
"human_perception": "The smell of rain hitting an overheating server rack just before a thunderstorm."
}
This iteration demonstrates the capacity of Flash3.7 to act not merely as a text-generator, but as a cross-modal translator. By forcing the model to resolve the tension between visual (surveillance footage) and chemical (pheromone) inputs, it hallucinates entirely new taxonomies of speculative design.
To run this experiment again, flush the context window and append new sensory data streams.
Because we are working in a text-based delivery medium, I pushed the model's capabilities into generative coding as a proxy for multimodal outputs. 1. The Abstract Input: The prompt treats video and sensor data as the "input," acknowledging the AI's ability to ingest massive sensory logs. 2. The Visual Output: Instead of just describing art, I used the model's latent spatial reasoning to mathematically write an SVG blueprint inline. The SVG uses CSS filters (turbulence, displacement maps, Gaussian blur) to create an organic, mycelium-like structure aggressively wrapping around a rigid circuit board grid. 3. The Olfactory Output: The AI outputs a highly specific JSON formula for a bio-hacked scent profile, translating data into the physical/chemical domain.
Every time you "run" an iteration like this, we can shift the input modalities (e.g., Input: Soil pH data + Audio of a dial-up modem; Output: A 3D CSS topographical map + speculative synthetic protein strings).