A decision framework for choosing between Amazon's Chronos-2 foundation model and custom XGBoost many-models pipelines for demand forecasting. Based on real patterns from SKU-level supply chain work.
Your DataZone environment works. AWS says SMUS is the future. Do you upgrade, go greenfield, or wait? Here is the coverage matrix, the 70–85 percent pipeline replacement reality, and the multi-account mesh architecture you actually need.
A discovery call with a global specialty chemicals company revealed that the real AI bottleneck isn't models — it's data. Here's what enterprise chemistry teams actually need versus what the hype promises.
Everything a cloud/AWS engineer needs to know about Python, the Hugging Face Transformers framework, SageMaker integration, quantization, CUDA, and AWS Inferentia — without being a data scientist.
A curated summary of the most important AWS announcements from February 2026 — from Bedrock AgentCore deep dives to new EC2 instances and the European Sovereign Cloud.
End-to-end guide: fine-tune Mistral models with LoRA using Hugging Face Transformers, then deploy at scale with vLLM on AWS — from training to production serving on SageMaker, ECS, or Bedrock.
Building a production forecasting application without the complexity of traditional ML model training and feature engineering.