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Nov 5

After go-live: what to monitor so quality doesn't silently decay

#ai #monitoring #mlops #automation

3 min read

Muhammad Umair Ashraf

Nov 5

Build a Fine-Tuned Model Training and Serving Pipeline on AWS

#aws #machinelearning #mlops #cloud

9 min read

Viswaretas Kotra

Nov 5

How do you train on AWS spot instances without losing work?

#aws #machinelearning #mlops #gpu

9 min read

Andrey Lesnikov

Nov 4

Reserve before you run: a budget guard for LLM inference on Kubernetes

#kubernetes #devops #ai #mlops

5 min read

Nov 4

Catching Input Drift Before Accuracy Falls: A PSI Walkthrough

#monitoring #mlops #python #statistics

5 min read

Nov 4

Surviving the Model Treadmill: Building AI That Outlives the Model It Launched On

#ai #aiengineering #mlops #aistrategy

7 min read

Nov 4

Why the ‘Astra Can Read and Write Weights to Improve Qwen’ Claim Is Misleading – A Practical Take for Engineers

#ai #mlops #opensource

4 min read

Nov 3

Astra’s Weight‑Space Programming: A Practical Guide to Tuning Qwen

#ai #mlops #devops

4 min read

Anish Rane

Oct 4

Choosing the Right Base Model for Fine-Tuning LLMs: Strategy Before Execution

#llm #ai #machinelearning #mlops

5 min read

Nov 2

Memdoor: How a Team of 5 Qwen‑3.8‑27B Models Beats Fable‑5 on LiveCodeBench Hard

#ai #llm #mlops

4 min read

Ines Mota

Nov 1

A checklist before you ship a notebook model

#machinelearning #python #mlops

1 min read

kohei matsunobu

Oct 31

Before You Burn GPU Hours, Smoke-Test One Task on a Cheap CPU Runtime

#python #testing #pytest #mlops

5 min read

Oct 30

Mistral Large 4 Weights Are Out – What It Means for Building LLM Infrastructures

#ai #llm #mlops

4 min read

George Ezejiofor

Oct 29

Canary Releases for an ML Model on KServe: Replayed Traffic, Sidecar Metrics and Automatic Rollback

#kubernetes #machinelearning #mlops #kserve

17 min read

Suresh Kumar Pallapothu

Oct 29

Day 29: Managing Technical Debt, Drift and Model Governance in Enterprise IT

#ai #mlops #governance #30dayaiseries

3 min read

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