engblogs

Practical guidance for building responsible, scalable AI programs through risk-based governance spanning data, models, lifecycle, and transparency to address bias, privacy, and compliance.

Cisco and OpenAI join forces to redefine enterprise engineering by deploying AI agents that streamline workflows and scale capabilities.

An in-depth look at the methods used to predict age from data, outlining our approach and key methodological considerations.

A practical guide to enabling multimodal retrieval in Amazon Bedrock Knowledge Bases, unifying text, images, video, and audio for Retrieval Augmented Generation using Nova Multimodal Embeddings.

Firestore's Enterprise edition adds an advanced query engine with pipeline operations that enable expressive, index-free queries, enhanced observability (query explain and query insights), customizable indexing, and predictable pricing on a scalable, serverless platform.

An executive guide to enterprise AI operating models, detailing CEO-aligned ownership of data and AI, comprehensive data inventories, broad definitions of data, governance of data assets, and a portfolio-based approach to delivering business outcomes across the organization.

A technical guide to integrating OpenAI with ServiceNow that enables actionable enterprise AI across workflows and systems.

Practical guide to deploying and managing ML workloads on Lambda Cloud with SkyPilot, covering installation, Lambda-specific configuration, a sample YAML-driven job, and automatic termination after idle time or job completion.

A technical guide to accessibility-driven language learning on Duolingo for hearing aid users, detailing configurable listening features, IPA-based phonetics, and the role of sign languages and subtitles in real-world practice.

A comprehensive guide to AI infrastructure, detailing the core computing, storage, networking, and software components and best practices for scalable, cost-effective AI workloads from training to deployment.

Production-grade AI agents across industries are explored—from fundamental agent types to multi-agent orchestration—grounded in enterprise data, governed for reliability, and designed for scalable, real-world deployment.

Practical framework-driven guide that defines core AI agent types (reflex, model-based, goal-, utility-, and learning-based) and explains how perception, autonomy, planning and governance shape reliable, production-ready agent systems.