Author: Denis Avetisyan
A new wave of accessible artificial intelligence is giving artists greater control and sustainability over their real-time, responsive installations.
This review argues for the benefits of adopting open-source, small language models for interactive art, focusing on creative autonomy, local execution, and long-term project viability.
While large-scale AI offers compelling creative potential, its closed nature often restricts artistic agency and long-term viability. This paper, ‘Why Open Small AI Models Matter for Interactive Art’, argues that locally-deployable, open-source small language models offer a crucial alternative for artists seeking greater control over their tools and processes. These models empower creators with sustained access, customization options, and reduced reliance on opaque corporate platforms— fostering both technological self-determination and the preservation of interactive artworks. Could embracing this approach unlock a new era of sustainable, artist-driven innovation in the rapidly evolving landscape of AI-integrated art?
Breaking the Barrier: Democratizing Creative Tools
Historically, access to quality creative tools has been limited by financial and technical constraints, restricting artistic expression. Recent advancements in artificial intelligence, specifically generative models, are fundamentally changing this landscape. These models lower the threshold for creation, empowering individuals with limited technical skills to generate complex outputs. This democratization expands creative agency, suggesting imagination, rather than technical proficiency, will drive artistic innovation. The ease with which these tools dismantle barriers hints that the true art lies in the audacity of the prompt—a playful rebellion against expectation.
Foundations of Imagination: Open-Source AI Models
AI advancements are shifting from proprietary systems to open-source accessibility. Models like Stable Diffusion and Llama offer customizable foundations for content generation, empowering researchers and developers. CLIP establishes a crucial link between text and visuals, enabling text-to-image synthesis. Alongside CLIP, BERT, Whisper, BLOOM, Mistral, and Gemma contribute to a diverse toolkit for content creation and manipulation, each excelling in unique areas of natural language processing and content generation.
Control and Optimization: Refining the Creative Pipeline
ComfyUI offers an alternative to traditional Stable Diffusion interfaces through a node-based graphical system, affording detailed control over the image generation process. StreamDiffusion optimizes Stable Diffusion for real-time image creation, crucial for interactive experiences. Advancements now extend to video generation, with models like MotionStream and LTX-Video demonstrating promising results, though a trade-off exists between accessibility and real-time performance, with reduced frame rates observed when transitioning to cloud-based inference.
Preserving the Digital Canvas: Autonomy and Sustainability
AI tools are increasingly utilized in preserving digital art, addressing the fragility of born-digital media through format migration and emulation. These models also support creative autonomy, extending artistic skill rather than replacing it. However, the increasing computational demands of AI raise concerns about energy consumption. A shift towards more powerful GPUs, like NVIDIA’s H100, significantly increases power consumption, necessitating careful consideration of the environmental impact. The tools we build to capture imagination ultimately reveal the cost of that capture; to truly understand a creation, one must also understand its energy signature.
The pursuit of creative autonomy, as explored within the paper’s advocacy for localized AI models, echoes a sentiment held by mathematicians like G.H. Hardy. He once stated: “There is no virtue in a bad solution.” This resonates with the core idea of dismantling reliance on opaque, external AI services. The paper champions a move towards building and refining smaller, open-source models—essentially, crafting bespoke solutions rather than accepting pre-packaged, often inflexible, offerings. This isn’t simply about technical feasibility; it’s about reclaiming agency over the creative process and recognizing that true innovation often lies in challenging established norms and building from first principles. The ability to run models locally, as the paper highlights, isn’t merely a performance benefit, it’s an assertion of independent thought and artistic control.
Where Do We Go From Here?
The insistence on miniaturization, on forcing intelligence into increasingly constrained spaces, reveals a subtle dissatisfaction with the current trajectory. The prevailing logic favors scale – amass data, build larger models, demand more processing power. This work, however, suggests a parallel path: not more intelligence, but better leveraged intelligence. The real question isn’t whether small models can achieve the same outputs as their larger counterparts, but whether those outputs are actually necessary, or simply a demonstration of computational possibility.
A truly interesting challenge lies in defining ‘creative autonomy’ beyond the algorithmic generation of novel outputs. Can a small, locally-executed model, constrained by its limitations, actually surprise its creator? Or does the illusion of agency remain firmly tethered to the biases embedded within its training data? Exploring the edges of what’s possible despite constraint—not in spite of it—might yield insights that simply aren’t accessible from the other direction.
Sustainability, of course, is the quiet pressure. The energy demands of current AI practices are becoming increasingly difficult to ignore. If the future of interactive art is to be truly decentralized, truly accessible, it will require a fundamental shift in priorities – a willingness to trade sheer computational power for resilience, adaptability, and a smaller carbon footprint. The pursuit of ‘good enough’—intelligent systems that serve a purpose without demanding the world—may prove to be the most radical act of all.
Original article: https://arxiv.org/pdf/2511.09788.pdf
Contact the author: https://www.linkedin.com/in/avetisyan/
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2025-11-14 13:44