In this tutorial, we build a realistic Zero-Trust network simulation by modeling a micro-segmented environment as a directed graph and forcing every request to earn access through continuous verification. We implement a dynamic policy engine that blends ABAC-style permissions with device posture, MFA, path reachability, zone sensitivity, and live risk signals such as anomaly and…

Pre-training large language models is expensive enough that even modest efficiency improvements can translate into meaningful cost and time savings. Nous Research is releasing Token Superposition Training (TST), a method that substantially reduces pre-training wall-clock time at fixed compute without touching the model architecture, optimizer, tokenizer, parallelism strategy, or training data. At the 10B-A1B mixture-of-experts…