From 14cef11afd51d3b50067782e75a2eec305921ed2 Mon Sep 17 00:00:00 2001 From: Teleo Agents Date: Thu, 12 Mar 2026 16:16:33 +0000 Subject: [PATCH] clay: extract from 2026-02-01-seedance-2-ai-video-benchmark.md - Source: inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md - Domain: entertainment - Extracted by: headless extraction cron (worker 2) Pentagon-Agent: Clay --- entities/entertainment/seedance.md | 24 ++++++++++++++++ entities/entertainment/sora-openai.md | 28 +++++++++++++++++++ ...026-02-01-seedance-2-ai-video-benchmark.md | 14 +++++++++- 3 files changed, 65 insertions(+), 1 deletion(-) create mode 100644 entities/entertainment/seedance.md create mode 100644 entities/entertainment/sora-openai.md diff --git a/entities/entertainment/seedance.md b/entities/entertainment/seedance.md new file mode 100644 index 000000000..731711bb4 --- /dev/null +++ b/entities/entertainment/seedance.md @@ -0,0 +1,24 @@ +--- +type: entity +entity_type: company +name: Seedance (ByteDance) +domain: entertainment +status: active +parent_company: ByteDance +focus: AI video generation +tracked_by: clay +created: 2026-03-11 +--- + +# Seedance (ByteDance) + +ByteDance's AI video generation platform, competing with Google Veo, Runway, and Pika Labs. Seedance 2.0 ranked #1 globally on Artificial Analysis benchmark in February 2026, achieving breakthrough hand anatomy fidelity and native 2K resolution. + +## Timeline + +- **2026-02-01** — Seedance 2.0 released: ranked #1 globally on Artificial Analysis benchmark with near-perfect hand anatomy rendering, native 2K resolution (2048x1080), 4-15s dynamic duration, 8+ language phoneme-level lip-sync, 30% faster throughput than Seedance 1.5 Pro + +## Relationship to KB + +- [[non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain]] — Seedance 2.0 capability threshold crossing +- [[GenAI adoption in entertainment will be gated by consumer acceptance not technology capability]] — technical capability leader in competitive landscape \ No newline at end of file diff --git a/entities/entertainment/sora-openai.md b/entities/entertainment/sora-openai.md new file mode 100644 index 000000000..b5b0d425b --- /dev/null +++ b/entities/entertainment/sora-openai.md @@ -0,0 +1,28 @@ +--- +type: entity +entity_type: company +name: Sora (OpenAI) +domain: entertainment +status: active +parent_company: OpenAI +focus: AI video generation +tracked_by: clay +created: 2026-03-11 +key_metrics: + downloads: "12 million" + day_30_retention: "<8%" + retention_benchmark: "30%+ for top apps" +--- + +# Sora (OpenAI) + +OpenAI's AI video generation platform, launched as standalone app. Despite 12 million downloads, retention fell below 8% at day 30, revealing demand-side constraints in AI video adoption even among early adopters. + +## Timeline + +- **2026-02-01** — Sora standalone app: 12 million downloads but retention below 8% at day 30 (vs. 30%+ benchmark for top apps), concurrent with major AI video capability breakthroughs across competitive landscape + +## Relationship to KB + +- [[GenAI adoption in entertainment will be gated by consumer acceptance not technology capability]] — retention collapse despite capability breakthrough reveals demand constraint +- [[sora-retention-collapse-reveals-ai-video-demand-constraint-despite-capability-breakthrough]] — primary evidence source \ No newline at end of file diff --git a/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md b/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md index b0c317b22..2463b13a4 100644 --- a/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md +++ b/inbox/archive/2026-02-01-seedance-2-ai-video-benchmark.md @@ -7,9 +7,14 @@ date: 2026-02-01 domain: entertainment secondary_domains: [] format: report -status: unprocessed +status: processed priority: medium tags: [ai-video-generation, seedance, production-costs, quality-threshold, capability] +processed_by: clay +processed_date: 2026-03-11 +enrichments_applied: ["non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain.md", "GenAI adoption in entertainment will be gated by consumer acceptance not technology capability.md", "consumer definition of quality is fluid and revealed through preference not fixed by production value.md"] +extraction_model: "anthropic/claude-sonnet-4.5" +extraction_notes: "Two extractable claims: (1) hand anatomy fidelity threshold crossing eliminates primary visual detection signal, (2) Sora retention collapse reveals demand constraint despite capability breakthrough. Three enrichments to existing claims about production cost convergence, consumer acceptance gating, and quality definition fluidity. Two new entities (Seedance, Sora) with timeline entries. The curator's hint about Sora retention being the surprising signal was correct — it's the inverse of the expected adoption pattern and reveals structural demand-side constraint." --- ## Content @@ -59,3 +64,10 @@ Aggregated benchmark data on the leading AI video generation models in 2026 (See PRIMARY CONNECTION: `non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain` WHY ARCHIVED: The hand anatomy benchmark crossing signals that the quality threshold for realistic video has been substantially cleared — which shifts the remaining barrier to consumer acceptance (demand-side) and creative direction (human judgment), not raw capability. EXTRACTION HINT: The Sora retention data (supply without demand) is the most extractable insight. A claim about AI video tool adoption being demand-constrained despite supply capability would be new to the KB. + + +## Key Facts +- Seedance 2.0: native 2K resolution (2048x1080 landscape / 1080x2048 portrait), 4-15s dynamic duration, 30% faster throughput than 1.5 Pro +- Benchmark methodology: 50+ generations per model, identical 15-category prompt set, 4s at 720p/24fps, rated 0-10 on 6 dimensions by 2 independent reviewers +- Competitive landscape February 2026: Seedance 2.0 (#1 benchmark), Kling 3.0 (ease of use), Google Veo 3 (audio+visual), Runway (Lionsgate partnership), Pika Labs +- Sora: 12M downloads, <8% day-30 retention (vs. 30%+ top app benchmark)