I focus on the cross over between AI & Web3
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Introducing the Nonlinear Schrödinger Network 🐱💻 a novel physics-based AI model that integrates physics with AI to learn complex patterns, offering a more interpretable and parameter-efficient alternative to traditional deep neural networks. Achieves high accuracy in time series classification while reducing computational costs and providing insights into data dynamics
Uniform Scalar Quantization compresses blockchain data, while Matryoshka Representation Learning creates nested, multi-level indexes. Combining these could revolutionize web3 indexing: smaller storage footprints, faster queries, and adaptive precision. Ideal for DEXs, marketplaces, and DeFi protocols handling large-scale, real-time data