Real-time semiotic graph reduction via convolutional receptive-field sweeps and virtual CRISPR imprinting — watch the engine restructure symbolic knowledge topology live.
Semiotic nodes encode symbolic primitives (Σ, Λ, Φ, Ω…) across three type manifolds — symbolic, neural, and graph. A 7×7 convolutional kernel sweeps the embedding space imprinting activations. Reduction events collapse topologically equivalent subgraphs into super-nodes. CRISPR-inspired edge editing rewires semantic adjacency with surgical precision.
From raw silicon to product — spanning distributed infrastructure, intelligent systems, and the interfaces that bind them.
Fault-tolerant architectures scaling to billions of events per day. Consensus protocols, sharding strategies, and eventual consistency at the edge.
Productionizing neural networks from research prototype to low-latency inference. Graph neural networks, symbolic AI, and neuro-symbolic hybrids at the frontier.
Real-time data infrastructure with Kafka, Flink, and custom stateful processors. Sub-millisecond latency on complex event processing at massive scale.
Building the developer experience layer — internal platforms, CI/CD systems, and the tooling that multiplies team velocity by an order of magnitude.
Temporal knowledge graphs, GNN inference engines, and symbolic graph reduction networks. Turning connected data into actionable intelligence.
End-to-end product development — from WebGL-accelerated frontends to bare-metal systems programming in Rust and Go.
Products and systems across intelligence platforms, streaming infrastructure, and developer tooling.
Real-time AI-powered analytics platform processing millions of signals per second. Custom GNN inference engine with sub-5ms p99 latency. NSGR for live knowledge consolidation.
Distributed streaming graph computation over 1B+ edges with time-travel queries. Supports bi-temporal versioning, WASM UDFs, and graph-native SQL.
Federated learning orchestration framework enabling privacy-preserving training across 200+ nodes. Differential privacy with less than 3% accuracy trade-off.
Real-time anomaly detection at billion-event scale using streaming ML. Adaptive thresholding with causal graph inference. MTTD reduced from 45 min to under 90 s.
Available for ambitious projects, co-founding opportunities, and conversations about the frontier.
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