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Stellaria Sounds ☆.｡.:*The 2025 Starlight Solstice Collection
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Stellaria Sounds ☆.｡.:*An Artist-First Music Industry Powered by IoT Hardware 🎛️
IoT hardware can power a shift in music industry standards and create an artist-first model that rewards royalties in real-time and incentivizes originality./// Bridge Between WorldsHardware is the heart of digital. The foundation of computing systems. The connection between physical, virtual, and extended realities. Hardware innovation is the exponent that multiplies transformation./// Smart Connected DevicesSmart connected devices, or the internet of things (IoT), are physical objects that ...
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Stellaria Sounds ☆.｡.:*The 2025 Starlight Solstice Collection
We believe that luxury should feel like belonging — to yourself, your story, your rituals. That elegance should be unique and accessible from moments that shimmer under chandeliers to cozy sunrise salutations.
Stellaria Sounds ☆.｡.:*Our Story — Starlight by Stellaria☆.｡.:*
Limited edition couture collectibles curated by Stellaria ✨💫
Stellaria Sounds ☆.｡.:*An Artist-First Music Industry Powered by IoT Hardware 🎛️
IoT hardware can power a shift in music industry standards and create an artist-first model that rewards royalties in real-time and incentivizes originality./// Bridge Between WorldsHardware is the heart of digital. The foundation of computing systems. The connection between physical, virtual, and extended realities. Hardware innovation is the exponent that multiplies transformation./// Smart Connected DevicesSmart connected devices, or the internet of things (IoT), are physical objects that ...
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From the viewpoint of Albert Einstein, "It is important for the common good to foster individuality: for only the individual can produce the new ideas which the community needs for its continuous improvement and requirements.”
The principle of originality in AI-generated art opens up an exploration of how AI models are assembled today, and if the collective approach to data amalgamation in building large language models is a supportive design principle for creating original works of art.
AI art applications today, use large language models mostly derived from data gathered from a range of sources. This approach to LLM assembly reaches to achieve the goal of AI alignment under the assumption that a massive, diversified dataset results in a greater probability of aligning with human output expectations.
However, if an artist values originality and holds it as a core design principle, then creating art with an AI model that generates suggestions based on a dataset derived from other artists’ work philosophically produces a misaligned output.
The alternative to a collectively curated AI model is an artist curated AI model.
Re-envisioning the relationship between artists and AI by redesigning models can open up possibilities to create deeper expressions of original works.
An artist-curated AI model is built with data that the artist generates, like workflows and compositions. These inputs contribute to the growth of the AI model over time. The frequency of artist working sessions combined with the volume of work an artist produces refines the AI model. In addition to a model that is custom-built for originality, the artist-to-AI development process encourages artists to continue skill building as opposed to cognitive offloading the creation process to AI.
With AI recommendations and outputs adapted to an artist’s individuality, misaligned scenarios, or “dreaming/hallucinating”, are significantly mitigated under the assumption that a curated dataset eliminates potentially irrelevant data sources.
The beauty of an artist-curated AI model is that the artist and AI evolve together. This evolutionary process can even be hypothesized to extend beyond an artist’s lifespan. In this scenario, the AI might be able to continue creating original work on behalf of the artist.
An artist-curated AI model holds a number of benefits, including:
👁️🗨️ Preservation of individual creativity
👁️🗨️ Higher degrees of AI alignment
👁️🗨️ Incentivization to build artistry skills
👁️🗨️ Reduction of cognitive offloading
👁️🗨️ Mitigation of AI “dreaming/hallucinating”
👁️🗨️ Co-creative evolution between artist and AI
👁️🗨️ Continuation of original works post-artist lifespan
From the viewpoint of Albert Einstein, "It is important for the common good to foster individuality: for only the individual can produce the new ideas which the community needs for its continuous improvement and requirements.”
The principle of originality in AI-generated art opens up an exploration of how AI models are assembled today, and if the collective approach to data amalgamation in building large language models is a supportive design principle for creating original works of art.
AI art applications today, use large language models mostly derived from data gathered from a range of sources. This approach to LLM assembly reaches to achieve the goal of AI alignment under the assumption that a massive, diversified dataset results in a greater probability of aligning with human output expectations.
However, if an artist values originality and holds it as a core design principle, then creating art with an AI model that generates suggestions based on a dataset derived from other artists’ work philosophically produces a misaligned output.
The alternative to a collectively curated AI model is an artist curated AI model.
Re-envisioning the relationship between artists and AI by redesigning models can open up possibilities to create deeper expressions of original works.
An artist-curated AI model is built with data that the artist generates, like workflows and compositions. These inputs contribute to the growth of the AI model over time. The frequency of artist working sessions combined with the volume of work an artist produces refines the AI model. In addition to a model that is custom-built for originality, the artist-to-AI development process encourages artists to continue skill building as opposed to cognitive offloading the creation process to AI.
With AI recommendations and outputs adapted to an artist’s individuality, misaligned scenarios, or “dreaming/hallucinating”, are significantly mitigated under the assumption that a curated dataset eliminates potentially irrelevant data sources.
The beauty of an artist-curated AI model is that the artist and AI evolve together. This evolutionary process can even be hypothesized to extend beyond an artist’s lifespan. In this scenario, the AI might be able to continue creating original work on behalf of the artist.
An artist-curated AI model holds a number of benefits, including:
👁️🗨️ Preservation of individual creativity
👁️🗨️ Higher degrees of AI alignment
👁️🗨️ Incentivization to build artistry skills
👁️🗨️ Reduction of cognitive offloading
👁️🗨️ Mitigation of AI “dreaming/hallucinating”
👁️🗨️ Co-creative evolution between artist and AI
👁️🗨️ Continuation of original works post-artist lifespan
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