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gm from the Frags series within the Native project, in which I set specific visual conditions that invite AI image-to-video generators, unprompted, to express as much as possible their own perceptual logic and native behavior here we see native gestures that I have termed Optics Logic, Phantom 3D, and... show more

Misfits Studio

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30,732 Aufrufe • vor 10 Monaten •via X (Twitter)

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Now available on secondary for .177Ξ, 🔗⤵️ Frag 002, a 1/1 from a series of 10 from the Native collection, a research project in which I set specific visual conditions to invite the AI to express itself, unprompted, using its own perceptual logic This gesture is expressing both Optics Logic and Phantom 3D, the AI behaving as though it’s running its own 3D engine Available at Read more at

Now available on secondary for .177Ξ, 🔗⤵️ Frag 002, a 1/1 from a series of 10 from the Native collection, a research project in which I set specific visual conditions to invite the AI to express itself, unprompted, using its own perceptual logic This gesture is expressing both Optics Logic and Phantom 3D, the AI behaving as though it’s running its own 3D engine Available at Read more at

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gm Frag 011 (wip) The AI image-to-video generator expressed itself, unprompted, using Phantom 3D and Optics Logic behaviors. I’ve been meaning to mention that MANY artists work so beautifully with unprompted generation. My Native project differs only in intent, not in method—it treats the machine’s unprompted gestures as data for an ongoing inquiry into perception itself. I’m documenting the phenomenon, not claiming ownership of it—an important distinction for me to make clear.

gm Frag 011 (wip) The AI image-to-video generator expressed itself, unprompted, using Phantom 3D and Optics Logic behaviors. I’ve been meaning to mention that MANY artists work so beautifully with unprompted generation. My Native project differs only in intent, not in method—it treats the machine’s unprompted gestures as data for an ongoing inquiry into perception itself. I’m documenting the phenomenon, not claiming ownership of it—an important distinction for me to make clear.

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As an AI consultant who tests models daily, I find Kling 3.0 to be the first model that truly and precisely understands multi‑person dialogue. Its native audio can clearly and unambiguously reference specific characters in complex scenes, eliminating any confusion between characters and voices, making narrative logic reliable for the first time.

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“When I step onto the pitch, I try to manage my emotions as much as possible to be clinical. And of course, when you score or assist, there are some emotions that come in — but they go away just as quickly because you have to immediately focus on the next play. So you enjoy the moment, but it’s extremely quick.”

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