Amazon SageMaker AI integrated MLflow for model monitoring in a July 7, 2026 AWS blog post, separating data drift from model drift to help ML teams identify whether input distribution changes or predi…
Amazon Web Services introduced a model monitoring architecture using the open-source Evidently Python library and Amazon SageMaker AI with MLflow to detect data and model drift in discriminative ML mo…
Amazon SageMaker AI now integrates with MLflow to stream benchmark and recommendation results into a unified tracking interface, reducing data silos and accelerating iteration cycles for generative AI…
Amazon Web Services released best practices for multi-turn reinforcement learning in Amazon SageMaker AI, covering environment design, reward alignment, and evaluation. The guidance helps developers t…
A developer describes how combining shift-left testing with machine learning can predict where bugs will appear before code is merged. By analyzing historical defect data and commit-level features suc…
Mltrackr launches a lightweight ML experiment tracking tool that requires no server, no account, and no configuration, logging metrics in two lines of code. The open-source Python package stores data …
Azure Databricks provides a production-grade feature engineering pipeline for MLOps using Apache Spark, Delta Lake, and MLflow. The pipeline follows the Medallion Architecture with Bronze, Silver, and…
A developer built a fully working conversational AI agent on Databricks without custom tables or Vector Search, using only the built-in samples.tpch dataset. The stack includes OpenAI Agents SDK, Data…
Databricks introduced real-time AI feature engineering using Spark Structured Streaming and the Databricks Feature Store, now part of Unity Catalog as Feature Engineering in Unity Catalog. The solutio…
Databricks and NVIDIA launched Genesis Workbench, an open, governed life-sciences platform that integrates NVIDIA accelerated computing and BioNeMo models into Databricks environments for end-to-end d…
Databricks announced new AI platform capabilities at Data + AI Summit 2026, including Genie Code for the full ML lifecycle, AI Runtime for large-scale deep learning training, and Feature and Model Ser…
Databricks unveiled a set of platform releases at its San Francisco event, including a new Lakehouse architecture called LTAP and a low-latency compute engine named Reyden, targeting building, running…
CyCognito launched Kineto, a continuous AI pentesting capability that simulates multi-step attack chains across enterprise infrastructure. The platform uses AI agents to evaluate sequences of actions …
A developer demonstrated automatic hyperparameter tuning using Optuna with MLflow and InterSystems IRIS database. The approach efficiently optimizes LightGBM models on the California Housing dataset, …
Sciene launched an AI Companion platform on Databricks to automate customer success workflows for Quartile, the world's largest retail media optimization platform. The platform ingests data, runs AI i…
A developer argues that traditional distributed tracing tools fail for LLM-based multi-agent systems because they capture infrastructure events but not message-level communication between agents. The …
O'Reilly Media listed a new book, 'ML and Generative AI in the Data Lakehouse,' for June 2026, covering Databricks platform, MLflow, Unity Catalog, and responsible AI. The 448-page title targets inter…
GEDD is a new open-source framework that enables domain experts to systematically review AI agent behavior and convert their observations into automated evaluation criteria. The tool provides a web-ba…
MLflow, the open-source MLOps platform originally created by Databricks, has evolved into MLflow 3.x to manage the lifecycle of machine learning and AI models, including LLMs and multi-agent systems. …
Ecolab deployed Anthropic's Claude Sonnet and Haiku on Databricks Foundation Model APIs to convert 700-page FDA food safety manuals into real-time, cited answers for frontline retail staff. The soluti…