Real-Time Machine Learning on Blockchain Data

Expert guide to real-time machine learning on blockchain data: streaming architecture (Kafka, Redis, Substreams), on-chain feature engineering (transaction… From the article "Real-Time Machine Learning on Blockchain Data" by Synor, published on Misar.Blog. In this episode: 0:00 Real-Time Machine Learning on Blockchain Data Can Process Transactions 1:03 The Production Stack Consists of Substreams for Streaming Blockchain Data 1:43 Critical Applications of the System 2:46 The Key Challenge Is That Blockchain Data Is Sparse 3:09 End-To-End Latency Must Stay Under 500 Ms from Block Production to Action 3:28 For MEV Opportunity Detection 4:30 Liquidation Forecasting Builds an Incremental DeFi Position Model 5:18 Anomaly Detection Uses an Ensemble of Isolation Forest 5:56 Streaming Features Such as HyperLogLog for Unique Counts 6:36 ONNX Runtime on a CPU Can Deliver 1-5 Ms Inference Latency This episode is narrated by an AI voice from a written article. More episodes: Tokenized Money Market Funds vs Stablecoins: On-Chain Cash Best PSU for a Used RTX 4090 (2026 Picks) Best Embedding Models 2026: OpenAI vs Voyage vs Open-Source Related reads: vLLM PagedAttention Explained Simply (with Visuals) Llama 4 vs Qwen 3.6 70B on RTX 4090: Speed Benchmarks 🔔 Subscribe to every episode Read the article: https://www.misar.blog/@synor/articles/real-time-ml-blockchain-data. Read the articles by this Author: https://www.misar.blog/@synor. Generated using: https://www.misar.ai (Misar.AI).