Muundo Algorithmic Flesh Usanifu Mwingiliano na Yalin Wang ni mshindi mashuhuri wa tuzo ya kifahari ya 2026 Tuzo ya Shaba ya A' Design Award katika Kategoria ya Mashindano ya Usanifu wa Uzalishaji, Algorithimu, Parametriki na Msaada wa AI.
ShabaUsanifu wa Uzalishaji· 2026
Algorithmic Flesh Usanifu Mwingiliano
na Yalin Wang
Mteja: Yalin Wang
Mshindi wa Tuzo ya Shaba ya A' Design Award katika Kategoria ya Usanifu wa Uzalishaji
Mshindi wa Tuzo Aliyethibitishwa
Thibitisha Hali ya Tuzo kwa #177508Muundo
Kuhusu Algorithmic Flesh Usanifu Mwingiliano
Algorithmic Flesh ni usanifu mwingiliano ulioundwa kwa ajili ya kuwasilisha urithi wa kitamaduni. Usanifu huu hufuatilia miondoko ya mwili wa mshiriki kwa wakati halisi na kutumia data ya miondoko hiyo kama ingizo kwa mfumo wa akili bandia jenereta. Mfumo huu umefunzwa kwa picha za michoro ya kuta ya Dunhuang na huzalisha mchezaji dansi wa kimbingu anayetembea kwenye onyesho kubwa la projekta. Pale mkao wa mshiriki unapolingana na mkao uliorekodiwa kutoka kwenye michoro ya kuta, kivuli cha mshiriki hubadilishwa kuwa mchezaji dansi huyo. Lengo ni kugeuza kumbukumbu tuli kuwa uzoefu wa pamoja na hai.
Utambuzi
Kuhusu Tuzo ya Shaba ya A' Design Award
Algorithmic Flesh Usanifu Mwingiliano ni mshindi wa Tuzo ya Shaba ya A' Design Award, utambuzi wenye heshima kubwa unaotolewa kwa miundo bora inayotofautishwa kwa ubunifu, ustadi na busara. Washindi wa Shaba ni kazi za ufundi mwingi na bunifu ya kushangaza zinazothibitisha uzoefu mpana, mawazo na ustadi wa wabunifu wao. Algorithmic Flesh Usanifu Mwingiliano inatarajiwa kuwa kitu kinachothaminiwa sana, kupendwa na kuenziwa, ambacho ni cha kitaalamu na bunifu kwa kiasi kikubwa. Muundo huu ulioshinda Tuzo ya Shaba ya A' Design Award unajumuisha mbinu bora katika sanaa, sayansi, usanifu na teknolojia, na ni bora kwa umakini wake kwa undani. Algorithmic Flesh Usanifu Mwingiliano hutosheleza mahitaji kwa uzuri, hugusa hamu, huvutia hisia na kuvutia udadisi.
Nyuma ya Muundo
Vifaa vya Habari
Mikopo, wanachama wa timu na maelezo ya kiufundi yaliyotolewa na mbuni.
- Sifa za Kipekee
- Algorithmic Flesh is an interactive installation redefining cultural heritage preservation as Generative Revitalization. It introduces Somatic Prompting: bypassing text interfaces, the system uses the participant's real-time physical movements as the generative seed. This somatic input drives a deeply trained AI to computationally hallucinate a dynamic, multi-limbed celestial dancer in real-time, using data from UNESCO Dunhuang murals. The audience becomes active co-creators of a living ritual.
- Vipimo na Ufungashaji
- As a digital installation, "Algorithmic Flesh" is highly scalable for gallery or museum contexts. The typical setup requires a projection area of at least 3m x 2m (supporting either 16:9 landscape or 9:16 portrait orientation, up to 4K resolution) and a participant interaction zone 3-4 meters from the screen.
- Lebo
- Generative AI, Embodied Interaction, Digital Ritual, Cultural Heritage, Human-AI Co-Interpretation, Somatic Prompting, Interactive Art Installation, Dunhuang Murals, Algorithmic Art, Cultural Computing, Choreography
- Teknolojia ya Uzalishaji
- Algorithmic Flesh uses a custom, closed-loop machine learning pipeline within ComfyUI. Real-time, markerless biomechanical tracking is achieved via OpenCV, MediaPipe, and YOLO26. Visual synthesis is driven by a FLUX LoRA model, fine-tuned on Tang Dynasty Dunhuang murals for absolute aesthetic fidelity. Temporal coherence is managed by Wan 2.2 Mixture-of-Experts video architecture, while the Google Veo 3 API provides cinematic spatiotemporal synthesis and native, physics-based audio generation.
- Changamoto ya Ubunifu
- The primary challenge was epistemological: How to reconstruct the dynamic, anti-gravitational flight of ancient murals in a virtual space without reducing them to lifeless 2D data? We emphasize not replacing the physical UNESCO Mogao Caves with a simulation, but speculating on new representation models. We challenge the passive museum dynamic, proposing an interactive framework where human flesh computationally hallucinates and sustains the continuous flow of a broken historical lineage.
- Utafiti
- This research addresses the loss of kinesthetic knowledge in static cultural heritage by introducing a Generative Revitalization framework. Pioneering somatic prompting, the project explores how a participant's body guides a generative AI without text. The machine, trained on Dunhuang mural archives, computationally generates lost transitional movements between ancient poses. This offers a new perspective on digital materiality, transforming a passive archive into an embodied, co-interpretive ritual.
- Msukumo
- How can we reawaken a dance frozen in stone for a millennium? Traditional digital preservation secures visual fidelity but flat-lines the dynamic essence of the Dunhuang Apsara murals into static maps—a Crisis of Stasis. Inspired by Heimkehren (returning home) and Buddhist philosophies of Anitya (Impermanence) and Pratityasamutpada (Interdependence), the design treats machine intelligence as a collaborator, celebrating the poetic instability of forms in transition as Digital Epiphanies.
- Muda wa Mradi
- The project was developed over a 10-month period from January to October 2025. The research and technical implementation were conducted in Beijing, China, in affiliation with the Central Academy of Fine Arts.
- Mtiririko wa Uendeshaji
- A participant stands before the projection. Instantly, a "Cosmic Telemetry" UI tracks their skeletal data in real-time. As they move, the system calculates their posture against a canonical Dunhuang dataset (e.g., "raised_leg_flying [0.96] Mogao Cave 285"). Upon a high-confidence match, this somatic prompt triggers the AI. The UI dissolves, and the user's silhouette morphs into a fluid, hyper-realistic celestial dancer, transforming the viewer into a co-creator of a living ritual.
- Hataza
- Copyrights belong to Yalin Wang, 2025. All algorithms and visual outputs are original research generated for academic and artistic purposes at CAFA.
- Haki za Picha
- Image #1: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #2: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #3: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #4: Creator Yalin Wang, Algorithmic Flesh, 2025.
Image #5: Creator Yalin Wang, Algorithmic Flesh, 2025.
Video Credits: Creator Yalin Wang, Algorithmic Flesh, 2025.
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