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Scale data quality with Agentic AI: an AI-driven, platform-native monitoring approach that learns normal patterns, detects anomalies, profiles data, and leverages Unity Catalog lineage to resolve issues across datasets for enterprise analytics and AI.

Concise guide to scaling AI/BI dashboard performance in Databricks, covering warehouse sizing, star-schema data modeling, and precomputed metrics with Metric Views to sustain fast queries under concurrent usage.

A holistic, end-to-end guide (Part 1) to optimizing AI/BI dashboards performance across design, warehouse concurrency, caching, and lakehouse data layout to reduce latency and scale with concurrent users.

A practical walkthrough of unlocking the Codex harness and building the App Server.

Screenless XR cross-device passkeys authentication that replaces QR codes with a companion-app-driven, hybrid WebAuthn/CTAP transport for secure passwordless login.

End-to-end, Databricks-based workflow that ingests FASTA protein sequences, classifies membrane proteins with ProtBERT-BFD, enriches records with LLM-driven research context, and delivers actionable, natural-language drug-target insights within a single governed platform.

Explores how AMI data, Databricks-powered AI analytics, and edge intelligence turn smart meters into a real-time, strategic platform for grid resilience, improved outage response, and enhanced customer value.

Examines how artificial intelligence and generative models accelerate the discovery and design of therapeutics and antibiotics through MIT collaborations, organ-on-chip testing, and translational pipelines from concept to preclinical candidates.

Antonio Torralba headlines MIT’s 2025 ACM Fellows alongside three alumni, underscoring advances in computer vision, machine learning, and human visual perception, plus leadership in AI research and education.

MIT appoints philosopher Brian Hedden as co-associate dean of the Social and Ethical Responsibilities of Computing (SERC) to advance interdisciplinary ethics in computing and AI within the MIT Schwarzman College of Computing.

Choosing meaningful monitoring metrics: blending DORA metrics with DX-driven developer feedback and Backstage-powered health checks to measure platform value and drive better conversations.

From chasing adoption to delivering real platform value, this article traces John Lewis's journey from simple metrics to multi-stage value measurement - lead times, DORA metrics, and a Technical Health score - driving faster, safer software with paved roads and self-service provisioning.