Global standards, audits, and certification.
Graph stores + vector search for RAG.
Comprehensive evals, incidents, and postmortems.
SLAM, grasping, and robust control.
Prompt injection defense, isolation, policy.
Large multimodal models in production.
Energy-aware architectures, carbon accounting.
Reg-tech, explainability, monitoring drift.
Safety cases, simulation, and validation.
Clinical ML, validation, post-market surveillance.
Kafka, Flink, Spark Structured Streaming.
Training, inference, safety, and eval.
VQE, QAOA, and tensor networks for ML.
DP, PETs, MPC, and federated learning.
CI/CD for ML, lineage, and auditability.
Low-latency apps, MLOps at the edge, 5G slicing.
Snowflake/BigQuery patterns, dbt, Kafka, and reliability.
Techniques for fairness, explainability, policy.
NLP systems: training, evaluation, bias & safety.
Kubernetes hardening, supply-chain security, policy as code.
Deep dive into consensus (Raft/Paxos), service meshes, SRE.
