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Issue #31: Refuel.ai. LLMs can label data better than humans. Autolabel.
Back with some news! We started a company called Refuel.ai - helping teams create clean, labeled datasets at the speed of thought.
 • 
Rishabh Bhargava
 and 
Nihit Desai
March 2022
January 2022
Issue #30: ML Platforms. On Deck Data Science. Explainability in Healthcare. Re:Invent. ML for Content Moderation.
Happy New Year and welcome to the 30th issue of the MLOps newsletter. We have been on a bit of a hiatus from the newsletter (sorry that we can’t share…
 • 
Rishabh Bhargava
 and 
Nihit Desai
October 2021
Issue #29: State of AI. Kaggle ML Survey. ML Deployment at Reddit. Inferentia.
Welcome to the 29th issue of the MLOps newsletter. This one is going to be fairly image-rich - hope you enjoy it! 🖼️ In this issue, we briefly cover…
 • 
Rishabh Bhargava
 and 
Nihit Desai
Issue #28: MAD Landscape. Covid-19 Border Testing. Blocking Spam@Slack. Applying ML. Scikit-learn 1.0.
Welcome to the 28th issue of the MLOps newsletter. We really enjoyed writing this one, hope you enjoy it too! In this issue, we briefly cover Nihit’s…
 • 
Rishabh Bhargava
 and 
Nihit Desai
September 2021
Issue #27: Medical Imaging Challenges. Machine Unlearning. Managing Supply and Demand. AI Sandbox.
Welcome to the 27th issue of the MLOps newsletter. It is officially one year since we started writing this newsletter, and we are incredibly grateful…
 • 
Rishabh Bhargava
 and 
Nihit Desai
Issue #26: Concept Drift. Anomaly Detection with Self-Supervision. NLP in Legal Applications. Models Per Customer?
Welcome to the 26th issue of the MLOps newsletter. In this issue, we deep-dive into inferring concept drift, share a paper on outlier detection using…
 • 
Rishabh Bhargava
 and 
Nihit Desai
August 2021
Issue #25: Tesla AI Day. Feature Stores. NIST on AI bias. Model monitoring tips. AI and COVID.
Welcome to the 25th issue of the MLOps newsletter. In this issue, we cover Tesla AI Day, a short paper about gaps in feature stores, updates about the…
 • 
Nihit Desai
 and 
Rishabh Bhargava
Issue #24: AI at Porsche. Efficient Inference. Bootstrapping Labels. Nearest-Neighbor Benchmarks.
Welcome to the 24th issue of the MLOps newsletter. In this issue, we cover an interesting approach to autonomous vehicles at Porsche, discuss strategies…
 • 
Rishabh Bhargava
 and 
Nihit Desai
July 2021
Issue #23: AI Regulations. Efficient Active Learning. Model Health Assurance. Vertex Matching Engine.
Welcome to the 23rd edition of the MLOps newsletter. In this issue, we cover updates on AI regulations and frameworks in the EU and the US, a recent…
 • 
Rishabh Bhargava
 and 
Nihit Desai
Issue #22: Github Copilot. CI/CD for ML at Scale. Concept Drift in Healthcare. Behavioral Testing.
Welcome to the 22nd issue of the MLOps newsletter. In this issue, we cover OpenAI’s paper introducing Codex (their fine-tuned GPT language model for…
 • 
Nihit Desai
 and 
Rishabh Bhargava
June 2021
Issue #21: Selecting MLOps Capabilities. Continuous Delivery For ML. Static Language Modelling. Sharing Data with AWS.
Welcome to the 21st issue of the MLOps newsletter. In this issue, we cover some tips from Google Cloud on choosing the right MLOps capabilities, share…
 • 
Nihit Desai
 and 
Rishabh Bhargava
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