Dan Moore: Redefining Creativity with AI, Art, and Robotics

I am Dan Moore, an artist, technologist, and educator working with AI, robotics, and generative systems. I am also a Senior Technical Artist at NVIDIA, where my work sits between art, engineering, real-time graphics, generative AI, robotics, and creative production technology.

My journey has always moved between engineering and art. I have been interested in how systems behave, how machines respond, and how technology can become a material for expression rather than just a tool for production.

Early in my career, I became fascinated by tangible interaction and computational media. That led me to work on projects involving robot arms, large scale interactive installations, real-time graphics, and later generative AI. My practice has expanded from building tools and interfaces into making cultural works that question authorship, agency, and collaboration between humans and machines.

Today, I work across painting, fashion, robotics, time-based media, and generative performance. I’m focused on turning emerging technology into expressive systems and artworks.

I also teach at The New School, where I work with students to think critically and creatively about software, AI, and the social impact of technology.

My journey has been shaped by a desire to bridge worlds that are often treated separately: engineering and art, automation and craft, computation and emotion. I am most interested in what happens when machines become agents in the creative process and the line blurs between tool and collaborator.

I’m bored by technology that’s just functional. I don’t care about bank software or another SaaS product or the latest app. I’m drawn to the expressive, the strange, and the emotionally resonant. I’ve always been obsessed with systems that go off-script: a robot improvising a movement, an AI hallucinating an image, a game not being a game, or a shader spitting out forms that will never exist again.

Creative technology lets me smash engineering discipline into artistic curiosity. I’m not here to just "solve problems"; I’m here to build experiences and narratives. The most interesting moment is when a machine does something I didn’t predict. In most fields, that’s an error. In mine, it’s the point.

That discovery keeps me moving. Whether I’m at NVIDIA, in my studio, or in a classroom, I treat creative technology as a way for artists to hijack the future of tools and culture before they’re handed to us as finished products.

I’m proud of building a practice that refuses to sit still. I move between art, tech, and education because sticking to one medium feels like a limitation. Whether it’s AI, robotics, or painting, the core is always the same: questioning who or what is actually in control.

The Great American Pastime series is a highlight. It won the 2025 AI Creative Future Award for turning fictional baseball into an infinite, AI-generated radio broadcast. For the Yogi Berra Museum’s centennial, I used AI to pit legendary Yankees lineups across eras against each other. It wasn’t just a tech demo; it was a way to use machine intelligence to poke at sports, memory, and Americana. Can Babe Ruth hit a dinger off Whitey Ford? Now we know.

I also value my time as an educator. Teaching students that code and AI are raw, expressive materials is as vital to me as the work I hang on a gallery wall.

GLITCHWEAR. It’s a live generative system that knits one-of-one garments from a visual stream that never repeats. You don’t pick from a catalog; you capture a fleeting digital moment and turn it into something physical.

The project stands out because it rethinks fashion as a time-based medium. A garment is no longer just designed, selected, and reproduced. It is encountered. It comes from a specific moment in a system that will never repeat in the same way again.

GLITCHWEAR brings together generative art, real-time graphics, textile production, e-commerce, and physical craft. It also reflects a larger question in my work: how do we translate unstable computational experiences into objects that can live in the world? I think that tension between the fleeting digital moment and the permanent physical object is incredibly rich.

AI and real-time technologies are changing creative industries by shifting the role of the creator from someone who only makes final artifacts to someone who designs systems, behaviors, prompts, constraints, and relationships. The future of creative work will not just be about producing images, films, garments, or experiences faster. It will be about building living systems that can generate, respond, adapt, and evolve.

In my work as a Senior Technical Artist at NVIDIA, I see how real-time tools, simulation, and generative AI are already changing the way creative teams think about production. These technologies make creative work more immediate, iterative, and performative. AI adds another layer by introducing systems that can interpret, transform, and collaborate.

Together, they create a new kind of creative environment where production is no longer linear. The artist, designer, or director can work in dialogue with a system that changes as they interact with it.

This will affect film, fashion, games, architecture, advertising, education, and fine art. The most interesting work will come from people who understand both the technology and the cultural questions around it. AI will not replace creativity, but it will change where creativity happens.

Do not wait for permission to start making things. The best way to understand emerging technology is to use it, break it, misuse it, and push it into places it was not designed to go.

I would also tell aspiring innovators not to define themselves too narrowly. Some of the most interesting ideas happen between disciplines. Learn enough engineering to build your ideas, enough art to question them, and enough culture to understand why they matter.

It is easy to get distracted by novelty, especially with AI. But innovation is not just using the newest tool. It is asking a better question. What does this technology reveal? What does it hide? Who does it empower? What new forms of expression become possible?

Finally, protect your curiosity. A career in innovation is really a career in learning how to stay uncomfortable, keep experimenting, and remain open to surprise.

I am most excited by the convergence of AI, robotics, and real-time simulation. AI has already changed how we generate images, text, and sound, but the next major shift will happen when intelligent systems move more directly into physical space.

Robotics is especially exciting because it forces AI to deal with the material world. Movement, balance, force, timing, and failure all become part of the system. When you combine that with real-time simulation and generative models, you can begin to create machines that do not just execute instructions, but improvise behaviors.

This convergence is something I think about constantly in both my independent artwork and my professional work at NVIDIA. For me, it opens up incredible possibilities for performance, installation, manufacturing, fashion, and public art. I am interested in machines that can collaborate physically, not just computationally.

One challenge has been learning how to work in fields that do not always share the same language. Art, engineering, fashion, education, and technology all have different expectations, timelines, and definitions of success. Moving between those worlds can be difficult because you often have to translate not only the work, but the reason the work matters.

I overcame that by learning to treat translation as part of the practice. In my career, including my work as a Senior Technical Artist, I have had to become comfortable explaining technical ideas to artists, artistic ideas to engineers, and speculative ideas to institutions or audiences that may not have seen anything like them before.

That process taught me that innovation is not only about making something new. It is also about helping people understand why the new thing matters. Communication, framing, and storytelling are as important as the technical execution.