Introduction Keynotes from the Swiss Generative AI Summit, Lausanne

Raphaël Briner, curator and organiser of Panoramai revealed a sophisticated creative laboratory where traditional acrylic paintings become starting points for AI exploration (and versa). One personal work—depicting his nine-year-old son in a tree structure they built together—demonstrates his methodology. Using Midjourney, he explored gender variations. On another static painting, he employed Luma AI to animate it randomly. « I was like, whoa, this is cute. I didn't think about (a hat turning into an umbrella). And that movement suddenly created a kind of motion around a true painting. So something static became alive. »

Briner's most compelling contribution lies in his systematic research into Midjourney's training data—a project born from curiosity about which artists remain accessible versus those who have opted out. His investigation reads like digital archaeology, mapping the platform's creative DNA through targeted searches.

Classical masters remain reliably present: Degas, Van Gogh, Renoir, Monet, Picasso. But contemporary artists present a patchwork landscape. Issey Miyake has withdrawn entirely, while Marc Newson remains accessible. Thomas Hirschhorn made a definitive exit, but Pipilotti Rist continues generating results.

The research revealed unexpected discoveries. Briner found his own AI-generated artwork appearing in search results for artists he'd never explicitly referenced, suggesting the platform recognizes stylistic connections embedded within its latent space. « As a creator, I'm using somewhere some influence » from artists like Agnes Martin and Sol LeWitt, he observed—the algorithm revealing creative influences even the artist hadn't consciously acknowledged.

Briner maintains a reference library of over 700 documented Midjourney styles, though he notes colleague Didier has catalogued « more like 7,000 styles » within the platform's parameter space. This systematic approach allows precise navigation through « 4 billions of parameters » to achieve specific aesthetic outcomes.

His creative process demonstrates sophisticated prompt engineering. For Panoramai's visual identity, he employed specific style reference codes (sref) to maintain consistency across generated imagery. This technical precision enables repeatability—crucial for professional creative work where aesthetic coherence matters.

Yet Briner maintains critical perspective on platform evolution. Midjourney's version 7 drew mixed reactions: while technically advanced, he characterized some outputs as « definitely too much »—comparing over-stylized results to « porn pictures. It's too much style, too much colors, too much everything. » This aesthetic judgment reveals the irreplaceable role of human creative direction in AI-assisted workflows.

His investigation into artist representation within training datasets reveals the complex ethical landscape AI creatives must navigate. The systematic opt-out by established artists creates both challenges and opportunities—while reducing available reference material, it opens space for emerging aesthetic directions that combine accessible influences with original vision.

Briner's exploration of Swiss wellness pioneer Arnold Hickli illustrates both AI's potential and its constraints (no nudes allowed on Midjourney). Attempting to recreate early 20th-century aesthetic styles, he encountered Midjourney's content restrictions, which forced creative workarounds leading to unexpected « funny structures. » These limitations sparked new creative directions rather than simple historical reproduction.

Elliot Vaucher: The Philosophy of Human-AI Collaboration

Elliot Vaucher embodied the interdisciplinary spirit Briner had promised—a practitioner whose journey from philosophy and French literature at Lausanne through contemporary arts at Kunst Bern to machine learning certification at EPFL reflects the emerging profile of AI-augmented creatives.

Vaucher, currently building his company Rizal (Research Institute in Technologies of the Self), brought philosophical depth to technical discussions. His mission centers on making « AI accessible for anyone and to make it simple »—a democratic vision that challenges assumptions about technical barriers in creative AI adoption.

His presentation traced algorithmic art's evolution from 1960s pioneers like Frieder Nake, who programmed machines to draw on plotters without graphical interfaces, to Michael Noll's prescient 1960 prediction: « Computers will become more readily accessible with the net result that many more people, including artists, will become computer oriented. » Vauchernoted the prophetic accuracy: « It's funny that he already envisioned this in the 1960s, but I think we maybe are here today where maybe art and code can merge. »

Vera Molnár's 1970s work provided Vaucher's philosophical anchor. Her quote resonated particularly: « You could say I am a computer gone wrong that turned into a woman... I can talk, walk, eat, drink. Computers don't do any of these things, they just work. » Vaucher interpreted this as fundamental: « I really think what makes human interesting is their limitations... All of us are limited in subjective way. So any of us have individuality that is not copyable... And this is what makes us interesting, not the fact that we are unlimited as computers are. »

The Interface Revolution: From Code to Conversation

Vaucher's core thesis challenged prevailing assumptions about AI learning curves. Despite his technical background, he argued against mastering diffusion model complexities: « What should an artist learn today? What should you learn about artificial intelligence? I think you shouldn't actually. I think generative AI is not something you need to learn to use. »

His framework positioned current AI as the third major computing interface evolution: from physical programming (ENIAC, 1950s) through graphical user interfaces (point-and-click) to natural language interaction. « Today the new interface is language really. And this makes computing much more accessible to anyone because anyone is able to speak. »

This accessibility revolution reframes creative AI adoption. Rather than technical training, Vaucher emphasized cultural expression: « For artists today, it's not about learning a new technical tool... It's about expressing your culture, your sensibility and your taste, really. » His philosophy suggests that artistic value emerges from human perspective rather than technical mastery.

The Aesthetic of Early Imperfection

Vaucher demonstrated nostalgic appreciation for early AI art's « awkwardness. » Showing 2021 DALL-E outputs and experimental work by artist friend Girosko using the Crayon tool, he observed: « I think it's so funny to see how ugly they were » but noted their disappeared charm as models improved.

This perspective reveals sophisticated aesthetic judgment—recognizing that technical perfection may diminish rather than enhance creative interest. His appreciation for early AI's limitations aligns with his broader philosophy celebrating human constraints as sources of individuality and artistic value.

Looking Forward: The Collaborative Creative Future

The spontaneous collaboration between Briner and Vaucher—arranged just Sunday evening before the conference—exemplifies the cross-pollination Panoramai enables. Briner noted: « I was thinking it was only in the coding space and sometimes you need an event to sync and create possible cross projects. »

Vaucher's democratic vision of AI accessibility, combined with Briner's systematic technical approach, suggests complementary strategies for creative AI adoption. While Briner demonstrates the power of technical mastery and systematic documentation, Vaucher advocates for lowering barriers through natural language interfaces and philosophical frameworks that celebrate human limitations as creative assets.

Their combined message resonates clearly: AI tools amplify rather than replace human creativity, but success requires either technical sophistication (Briner's approach) or clear philosophical grounding in human uniqueness (Vaucher's philosophy). In the Swiss creative community, this synthesis of technical capability and humanistic values may prove particularly powerful as Europe shapes its AI future.