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Announcing Serverless RL: Train agents without worrying about infra or GPUs

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Weights & Biases gets a new terminal UI
Dave Davies, Chander Matrubhutam
Nov 11
Articles, W&B Features, W&B Meta
SkyPilot + Weights & Biases: AI observability on any infra
Romil Bhardwaj
Nov 14
Articles, Tutorial
Introducing Serverless LoRA Inference
Nina Olding, Chander Matrubhutam
Nov 20
Articles, Inference, New W&B feature releases, Tutorial
Product newsletter: Updates and new features for November 2025
Justin Tenuto
Dec 01
Articles, New W&B feature releases
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Curriculum Learning in Nature Using the iNaturalist 2017 Dataset
Stacey Svetlichnaya
Feb 08
Intermediate, Computer Vision, Object Detection, Experiment, CNN, Plots, iNaturalist
Classify the Natural World with Weights & Biases
Stacey Svetlichnaya
Feb 08
Advanced, Computer Vision, Object Detection, Keras, Experiment, CNN, Plots, ImageNet, iNaturalist, Exemplary
fastText Nanobot for the Transformer Age
Stacey Svetlichnaya
Feb 07
Beginner, NLP, fasttext, Tutorial, Plots
Hyperparameters of a Simple CNN Trained on Fashion MNIST
Stacey Svetlichnaya
Feb 07
Intermediate, Computer Vision, Object Detection, Experiment, CNN, Slider, Sweeps
Compare Code Across Runs
Robert Mitson
Feb 06
Beginner
Semantic Segmentation: The View from the Driver's Seat
Stacey Svetlichnaya
Feb 06
Advanced, Computer Vision, 3D, Object Detection, Semantic Segmentation, fastai, Experiment, CNN, ResNet, U-Net, Github, Panels, Plots, Slider, Sweeps, Berkeley Deep Drive, Autonomous Vehicles, Exemplary
Reproducibility: Docker for Machine Learning
Robert Mitson
Feb 06
W&B Features
Six Ways to Debug a Machine Learning Model
Robert Mitson
Feb 05
Beginner
Intro to Pytorch with W&B
Lavanya Shukla
Feb 04
PyTorch
Harness the Sky: Aerial Segmentation Benchmark with DroneDeploy
Stacey Svetlichnaya
Feb 03
Computer Vision
Introduction to Hyperparameter Sweeps – A Model Battle Royale To Find The Best Model In 3 Steps
Lavanya Shukla
Feb 02
W&B Features
arXiv Search: Generating Tags from Paper Titles
Robert Mitson
Feb 01
NLP
Pytorch Lightning with Weights & Biases
Ayush Chaurasia
Feb 01
PyTorch
Exploring Deep Learning Hyperparameters with Random Forests
Lukas Biewald
Jan 31
W&B Features
Introduction to Convolutional Neural Networks with Weights & Biases
Lavanya Shukla
Jan 27
Beginner
Debugging Neural Networks with PyTorch and W&B Using Gradients and Visualizations
Ayush Thakur
Jan 26
PyTorch
Visualize Scikit-Learn Models with Weights & Biases
Lavanya Shukla
Jan 25
Beginner, Tabular, scikit-learn, Tutorial, W&B Meta, Plots
Exploring ResNets With W&B
Ayush Chaurasia
Jan 24
W&B Features
What Is Bayesian Hyperparameter Optimization? With Tutorial.
Robert Mitson
Jan 22
W&B Features
Introduction to Hyperparameter Sweeps – A Model Battle Royale To Find The Best Model In 3 Steps
Lavanya Shukla
Jan 15
W&B Features
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