Topic

Machine Learning Operations (MLOps)

All digests tagged Machine Learning Operations (MLOps)

The Unreasonable Effectiveness of Separating the Task from the Model — Maxime Rivest, DSPy

DSPy brings software engineering principles to AI programs by defining tasks via a 'Signature' (inputs/outputs). This separates the task contract from the model, allowing flexible optimization and scaling.

Read article

Latent Space

Poolside’s Model Factory, Laguna S, Open Models, and the Race to AGI — Eiso Kant, Poolside AI

Poolside’s Model Factory is an end-to-end system that treats model building as an industrialized process. It enables rapid iteration by streaming data directly into training, ensuring perfect reproducibility through immutable data layers.

Read article

Weights & Biases

CoreWeave ARIA: The autoresearch loop for continuous improvement

CoreWeave ARIA demonstrates an autonomous autoresearch loop, allowing AI agents to continuously improve models by forming hypotheses, running experiments, and analyzing results using Weights & Biases.

Read article