yanpei_cao
@yanpei_cao
Past bets that played out
These are the clearest thesis calls with observable outcomes, linked back to the original videos.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
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Yanpei Cao @yanpei_cao Jul 22 We @tripoai won Best in Show at #SIGGRAPH2026 Real-Time Live! last night! 🏆 What a blas...
A private company (Tripo AI) won “Best in Show” at SIGGRAPH 2026 Real-Time Live. This is positive validation for real-time/AI-generated 3D content tooling, but it’s not directly tradable unless there are public comparables; impact on public tickers is second-order and low-confidence.
@alightinastorm @rms80 @tripoai Yes, improvements are in the works! We noticed this issue too (it impacts smart mesh ...
A social reply indicating TripoAI is working on improvements to an issue affecting “smart mesh,” with no concrete timeline. This is a minor, non-quantified product-update signal for AI-generated 3D/mesh workflows, not a market-moving catalyst by itself.
@alightinastorm @rms80 @tripoai Forget the old stereotypes about AI meshes!😉 Tripo (Smart Mesh) now generates clean, ...
Post claims Tripo (Smart Mesh) can generate clean, artist-friendly polygon meshes quickly (improved topology vs older AI meshes that produced very dense ~1M-face outputs). This suggests accelerating quality improvements in AI-assisted 3D asset creation pipelines.
Pinned Yanpei Cao @yanpei_cao Mar 6 Generative 3D has been stuck in a representational compromise. When you serialize...
The source is a technical comment about generative 3D models being constrained by current representations (serialization causing unidirectional bias), implying potential innovation/cycle shift toward better 3D-native architectures. It is conceptually relevant to AI/graphics compute and 3D content tools, but contains no concrete company/news catalyst, timing, or adoption signal—so near-term trading actionability is low.
Proof-backed call history
These are recent thesis calls tied to original source content where available.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
A research post announces “HoloPart,” an open‑source generative model that decomposes 3D shapes into complete parts (including occluded/hidden components), enabling easier 3D editing, animation rigging, and content creation. This is an enabling technology signal for faster 3D asset pipelines rather than a direct, near-term revenue catalyst for any single public company.
The source is a technical comment about generative 3D models being constrained by current representations (serialization causing unidirectional bias), implying potential innovation/cycle shift toward better 3D-native architectures. It is conceptually relevant to AI/graphics compute and 3D content tools, but contains no concrete company/news catalyst, timing, or adoption signal—so near-term trading actionability is low.
The source is a technical comment about generative 3D models being constrained by current representations (serialization causing unidirectional bias), implying potential innovation/cycle shift toward better 3D-native architectures. It is conceptually relevant to AI/graphics compute and 3D content tools, but contains no concrete company/news catalyst, timing, or adoption signal—so near-term trading actionability is low.
The source is a technical comment about generative 3D models being constrained by current representations (serialization causing unidirectional bias), implying potential innovation/cycle shift toward better 3D-native architectures. It is conceptually relevant to AI/graphics compute and 3D content tools, but contains no concrete company/news catalyst, timing, or adoption signal—so near-term trading actionability is low.
The source is a technical comment about generative 3D models being constrained by current representations (serialization causing unidirectional bias), implying potential innovation/cycle shift toward better 3D-native architectures. It is conceptually relevant to AI/graphics compute and 3D content tools, but contains no concrete company/news catalyst, timing, or adoption signal—so near-term trading actionability is low.
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@yanpei_cao
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