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The Multi-Modal Shift: Augmenting AI with Rich Data
Key Insights
- Multi-modal data significantly enhances AI capabilities by aligning text, image, audio, and video inputs.
- Large-scale datasets like InternVid and OpenHumanVid have notably improved AI model realism and accuracy.
- Collecting and curating massive multi-modal datasets remains challenging due to scale, cost, and ethical concerns.
- Grass leverages decentralized infrastructure, enabling efficient and extensive harvesting of multi-modal web data.
- Recent upgrades to the Grass network have substantially increased its capacity, reinforcing its role in future AI training.
Introduction
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Prior to joining Messari, Andrew was an equity trader at a proprietary trading firm. His primary interests are understanding market dynamics, riding trends, and finding the occasional onchain winner.
Mentioned Assets