A small team built their own AI PR reviewer to tackle traceability and approval issues in Azure DevOps, then compared it to commercial tools.

New open-source protocol separates AI decision-making from action enforcement to prevent costly agent errors.

New custom silicon aims to drastically improve AI model efficiency, potentially outperforming current TPUs.

The AI industry often restarts its growth cycle by releasing new models to mask underdelivery, a pattern mirroring Gartner's Hype Cycle.

Build practical AI skills with a curated roadmap covering classical algorithms, deep learning, and LLM training.

A severe authentication bypass vulnerability in Palo Alto Networks' PAN-OS is now actively exploited by the Qilin ransomware gang for network intrusion.

While Black-founded startups saw strong Q1 2026 funding, large deals mask a persistent Series A gap. Experts outline strategies to bridge this divide.

Stop losing track of model versions and parameters. MLflow provides a robust framework for reproducible machine learning.

Teams are shifting from manual data lake management to automated control planes, driven by Apache Iceberg's near-universal adoption.

Two years after diagnosing software development's subjectivity, the author admits the proposed cure was wrong, but a new path to verifiable criteria has emerged.