Generative AI

Deep learning models that generate high-quality content

Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on.

Articles

02 February 2026

Article

Protecting AI embedding vectors by using approximate distance preserving encryption for RAG applications

Protect embedding vectors from reverse-engineering attacks using distance-comparison-preserving symmetric encryption (DCPE). Learn to implement DCPE in Java with IronCore Labs Alloy SDK for secure RAG applications.

29 January 2026

Article

From prompt engineering to fine‑tuning: Transforming document validation

Learn how fine‑tuning a small language model (Mistral 7B) and using a Granite 3.3 8B orchestrator solves the consistency challenges of large‑scale business document evaluation.

27 January 2026

Article

Model Context Protocol architecture patterns for multi-agent AI systems

Learn how Model Context Protocol enables scalable multi agent AI systems through client, server, and hybrid architecture patterns, LLM placement strategies, reusable AI agents, dynamic orchestration, enterprise design trade offs, and real world implementation guidance.

25 November 2025

Article

Building and deploying prebuilt domain agents in watsonx Orchestrate

Discover the watsonx Orchestrate Agent Catalog, which includes hundreds of prebuilt agents and hundreds more prebuilt tools across numerous domains, including HR, Sales, Finance, IT, and more. Understand the steps you need to take to build and deploy the prebuilt domain agents - configuring secure connections, customizing the prebuilt agent as a template and deploying it, and then testing the agent.

14 November 2025

Article

Calculating vector embeddings for semantic search and retrieval augmented generation (RAG)

Get started with LangChain4j, a Java library designed to simplify the integration of large language models (LLMs), and learn how to leverage its features for vector embeddings, semantic search, and generative AI applications.

31 October 2025

Article

JSON prompting for LLMs

Discover universal JSON prompt templates for extraction, generation, and analysis, plus best‑practice automation and error‑handling techniques for production‑grade AI pipelines.

07 October 2025

Article

Agentic data scientists: Redefining the future of analytics

Discover the Agentic Data Scientist, a revolutionary tool that automates data science workflows using LangGraph and watsonx. Simply upload a CSV/Excel file, describe your analysis, and let the agent do the work. The AI-driven agent plans, codes, executes, reviews, and delivers results, streamlining your data science tasks with minimal human intervention.

03 October 2025

Article

The ultimate guide to Elasticsearch

Elasticsearch has transformed from a simple search engine into a powerful AI-powered platform capable of handling diverse search requirements. By mastering indexing, analyzers and hybrid search techniques, developers can build sophisticated search experiences that combine the precision of keyword search with the contextual understanding of semantic search.

03 October 2025

Article

SOC Agentic Governance Engine (SAGE): Reinventing audit evidence collection with Agentic AI

Automate SOC audits with SAGE using agentic AI, QRadar, and watsonx Orchestrate for faster evidence collection, compliance, and reduced analyst workload.

24 September 2025

Article

Evaluating generic phrases using Granite models

In this article, we demonstrate using different prompts with different contexts to analyze how LLMs behave when asked generic-related questions. We show how the Granite 3.3-2b model is good at identifying associated quantifiers in generic phrases and the model's responses are context-driven too.

04 September 2025

Article

Accelerate Mainframe application modernization with Generative AI and COBOL Java interoperability

Learn how to modernize mainframe applications with IBM watsonx Code Assistant for Z, generative AI, COBOL modernization, and Java interoperability.

14 August 2025

Article

What is InstructLab and why do developers need it?

InstructLab empowers developers to unleash the full potential of LLMs, offering a streamlined training process, cost-efficiency, community collaboration, and stability in model performance.

Items per page:

1–12 of 71 items

of 6 pages

Topics

Languages

Products

Open Source

Generative AI

Deep learning models that generate high-quality content

Articles

Protecting AI embedding vectors by using approximate distance preserving encryption for RAG applications

From prompt engineering to fine‑tuning: Transforming document validation

Model Context Protocol architecture patterns for multi-agent AI systems

Building and deploying prebuilt domain agents in watsonx Orchestrate

Calculating vector embeddings for semantic search and retrieval augmented generation (RAG)

JSON prompting for LLMs

Agentic data scientists: Redefining the future of analytics

The ultimate guide to Elasticsearch

SOC Agentic Governance Engine (SAGE): Reinventing audit evidence collection with Agentic AI

Evaluating generic phrases using Granite models

Accelerate Mainframe application modernization with Generative AI and COBOL Java interoperability

What is InstructLab and why do developers need it?