engblogs

Continuous AI enables a cross-team accessibility feedback workflow at GitHub, automating triage and routing feedback into tracked, prioritized issues to drive continuous, human-guided improvements.

An end-to-end guide to fine-tuning NVIDIA Parakeet TDT 0.6B V2 for domain-specific ASR on AWS, spanning synthetic data generation, distributed training with NeMo and DeepSpeed, and scalable EKS deployment with observability and API management.

A scalable, end-to-end blueprint for multimodal video search that combines Nova multimodal embeddings with OpenSearch to support text-to-video, video-to-video, and hybrid semantic-keyword search over massive video datasets.

Debunking the top data warehouse migration myths with a Databricks-driven, lakehouse-based blueprint for AI-ready modernization—combining automated conversion, rigorous validation, governance, and rapid ROI.

Examines how Databricks serverless compute redefines data engineering for Notebooks, Lakeflow Jobs, and Spark Declarative Pipelines by auto-optimizing infrastructure, enabling versionless upgrades, and delivering rapid startups with substantial cost savings.

A production-focused guide to the first generation of agentic commerce, detailing catalog ingestion, real-time inventory checks, Shared Payment Tokens, and Stripe-powered cross-agent payments with AI agents via the ACP.

A historical-technical look at how chess computers evolved from deceptive automata to powerful engines, explaining how search, rules, and heuristics allow machines and humans to compete and improve.

Cloudflare Account Abuse Protection delivers a multi-layer defense that blends leaked credentials checks, disposable-email and email-risk scoring, account-takeover detections, and Hashed User IDs to distinguish authentic users from bot- and human-driven abuse across account creation and login.

Examines how AI and the mathematical and physical sciences mutually propel each other, foregrounding a science of AI, centaur scientists, and coordinated research, talent, and community to guide the future of AI.

Operationalizing Agentic AI Part 1 explains how to convert agentic AI into an executable, governed operating model, defining concrete work, bounded autonomy, observable metrics, and safe fallbacks to bridge the execution gap from pilots to production.

Turning a model into an autonomous agent by provisioning the Responses API with a programmable computer environment.

Graph-based ontologies and open standards enable scalable, auditable, and interoperable knowledge management for nuclear plants, linking design, licensing, safety constraints, and operations to accelerate decision-making under evolving regulatory and technology landscapes.