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koriweb d8a80f6272 chore(wiki): dangling 링크 canonical 정규화 (768파일/1200건)

이름만 다른(표기 변형) [[위키링크]]를 대상 문서의 canonical 제목으로 치환해
끊겼던 1,200개 링크를 연결. 제목/파일명 정규화 일치만 적용하고 별칭 매칭은
과병합 위험으로 제외(애매성 가드). 원본은 _link_reconcile_backup/ 에 백업.
도구: Datacollect/scripts/link_reconcile_apply.mjs

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

2026-06-08 12:24:15 +09:00

7.6 KiB

Raw Blame History

id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack

title

Arts (Human + AI Era)

📌 한 줄 통찰

"매 language 너머의 communication". 매 emotion / experience / idea 의 form / sound / color 의 translate. 매 modern: 매 AI generative 의 democratize 가, 매 authenticity / labor / copyright 의 new battleground. 매 Neo-Humanism 의 imperfection 의 가치.

📖 핵심

매 function

Catharsis: 매 emotion 의 release.
Communication: 매 timeless message.
Critical perspective: 매 society 의 mirror.
Beauty: 매 aesthetic.
Identity: 매 cultural / personal.

매 evolution

시대	Medium
고대	매 cave painting, 매 sculpture
중세	매 religious art
르네상스	매 perspective, 매 oil
19c	매 photography
20c	매 film, 매 abstract, 매 conceptual
21c	매 digital, 매 NFT
2022+	매 AI generative

매 AI generative tool

Midjourney: 매 stylized, 매 artistic.
Stable Diffusion (open): 매 customizable.
DALL-E 3 (OpenAI): 매 prompt 의 understanding.
Flux (Black Forest Labs): 매 photorealistic.
Sora / Runway: 매 video.
Suno / Udio: 매 music.
ElevenLabs: 매 voice.

매 controversy

Copyright

매 LAION-5B (training data) 의 unauthorized.
매 lawsuit (Getty vs Stability AI).
매 EU AI Act 의 disclosure.
매 Glaze / Nightshade (artist 의 anti-tool).

Labor

매 illustrator / VFX 의 displacement.
매 Hollywood writers strike (2023).
매 game industry layoff.

Authenticity

매 award withdrawn (Sony 2023, Adobe 등).
매 disclosure 의무.
매 C2PA standard.

Quality

매 AI 의 averaged style.
매 Slop (over-produced).
매 derivative.

매 Neo-Humanism 의 응답

매 imperfection 의 가치.
매 physical mark 의 evidence.
매 process documentation.
매 human-only category.
매 hand-made 의 premium.
매 live performance.

→ 매 differentiation 의 lever.

매 hybrid (collaboration)

매 AI 의 ideation → 매 human refinement.
매 human sketch → 매 AI extension.
매 AI 의 variation → 매 human selection.
매 controlled (ControlNet, ComfyUI).

매 modern artist 의 stance

Refuse AI: 매 Glaze 적용.
Embrace + transparent: 매 disclosure.
Hybrid: 매 tool 의 use.
AI-first: 매 prompt 의 art.

매 evaluation 의 새 axis

Concept (idea).
Execution (technique).
Process (story).
Provenance (chain).
Originality (vs derivative).

💻 패턴

Stable Diffusion (controlled)

from diffusers import StableDiffusionXLPipeline, ControlNetModel
from diffusers import StableDiffusionXLControlNetPipeline

controlnet = ControlNetModel.from_pretrained('diffusers/controlnet-canny-sdxl-1.0')
pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
    'stabilityai/stable-diffusion-xl-base-1.0',
    controlnet=controlnet,
).to('cuda')

# 매 user 의 sketch (canny edge) + prompt
import cv2
sketch = cv2.Canny(user_sketch, 100, 200)

image = pipe(
    prompt='a cat with a hat, oil painting, vivid color',
    image=sketch,
    controlnet_conditioning_scale=0.7,
    num_inference_steps=30,
).images[0]

Glaze (anti-AI training)

# 매 artist 의 work 의 protect
# 매 imperceptible perturbation 의 add
# 매 ML 의 learn 의 disrupt
def glaze_protect(image, target_style='unrelated_style', epsilon=0.05):
    # 매 PGD-like attack
    perturbed = image.clone().requires_grad_()
    optimizer = torch.optim.Adam([perturbed], lr=0.001)
    for _ in range(100):
        loss = -torch.norm(style_extractor(perturbed) - target_style)  # 매 push to wrong style
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()
        perturbed.data = torch.clamp(perturbed, image - epsilon, image + epsilon)
    return perturbed.detach()

C2PA disclosure (provenance)

{
  "claim_generator": "Adobe Photoshop 25.0",
  "assertions": [
    { "label": "c2pa.actions",
      "data": { "actions": [
        { "action": "c2pa.created",
          "softwareAgent": "Stable Diffusion XL 1.0",
          "parameters": { "prompt": "a cat with a hat" } },
        { "action": "c2pa.edited",
          "softwareAgent": "Adobe Photoshop",
          "parameters": { "name": "manual color correction" } }
      ]}}
  ]
}

Hybrid workflow (sketch → AI variation → human refine)

def hybrid_workflow(user_sketch, prompt, n_variations=4):
    # 1. AI 의 N 의 variation
    variations = generate_n(user_sketch, prompt, n=n_variations)
    
    # 2. Human selection
    chosen = human_pick(variations)
    
    # 3. AI 의 refine (img2img with low strength)
    refined = pipe(
        prompt=prompt + ', polished',
        image=chosen,
        strength=0.3,
    ).images[0]
    
    # 4. Human final touch (Photoshop)
    return chosen, refined

AI-art disclosure UI

function ArtworkCard({ artwork }: { artwork: Artwork }) {
  return (
    <article>
      <img src={artwork.url} />
      <h3>{artwork.title}</h3>
      <DisclosureBadge level={artwork.aiInvolvement} />
      {artwork.aiInvolvement !== 'none' && (
        <details>
          <summary>AI tools used</summary>
          <ul>
            {artwork.aiTools.map(t => <li>{t.name} (v{t.version})</li>)}
          </ul>
          <p>Prompts: {artwork.prompts}</p>
          <p>Human edits: {artwork.humanEdits}</p>
        </details>
      )}
    </article>
  );
}

🤔 결정 기준

상황	Approach
Commercial (deadline)	AI + human refine
Personal expression	Human-first
Conceptual	Mix (concept matters)
Photography	Human (regulate AI)
Illustration job	Disclose + 의뢰자 의 OK
Music	Hybrid (sample / collaborate)
Game asset	AI + license check
NFT	Provenance-tracked

기본값: 매 disclosure + 매 attribution + 매 hybrid (human + AI). 매 100% AI 의 explicit category.

🔗 Graph

부모: Aesthetic-Value · Creativity
변형: Generative-Art · AI-Art
응용: Stable-Diffusion · Midjourney · ControlNet · ComfyUI
Adjacent: Authenticity · C2PA · Copyright · AI Image Generation

🤖 LLM 활용

언제: 매 generative art workflow. 매 brand asset. 매 game art pipeline. 매 hybrid creative. 언제 X: 매 fine art individual expression (human-only). 매 traditional photography (AI 의 ban).

❌ 안티패턴

No disclosure: 매 fraud.
AI 의 derivative 의 commercial: 매 copyright risk.
All AI no concept: 매 slop.
Glaze 의 ignore: 매 artist 의 will violate.
Single tool monoculture: 매 same look.
Award fraud: 매 community trust 의 destroy.

🧪 검증 / 중복

Verified (C2PA spec, ongoing copyright cases, art community discourse).
신뢰도 B (rapidly evolving).
Related: AI Image Generation · Authenticity · C2PA · Copyright · Glaze.

🕓 Changelog

날짜	변경
2026-05-08	Phase 1
2026-05-10	Manual cleanup — generative tool + controversy + Neo-Humanism + 매 SD / Glaze / C2PA code

7.6 KiB Raw Blame History