Author: Dr. Pranay Jha
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EU AI Act Readiness and Responsible AI on watsonx (IBM Gen AI Series, Part 21)
The 2026 Digital Omnibus pushed high-risk deadlines to December 2027, but GPAI and transparency duties still bite this year. Here is how I classify a watsonx system and build the evidence pack before an auditor asks.
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watsonx Cost Governance and FinOps, from Resource Units to a Real Budget (IBM Gen AI Series, Part 20)
watsonx charges in Resource Units, capacity unit hours, and a flat instance fee. Here is how those meters add up, and the plan choice that keeps your generative AI bill honest.
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watsonx.governance Risk Monitoring and AI Factsheets (IBM Gen AI Series, Part 19)
How watsonx.governance tracks models, logs AI factsheets, monitors drift and bias in production, and maps controls to the EU AI Act. Part 19 of the IBM watsonx series.
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Docling and Multimodal Document Understanding on watsonx (IBM Gen AI Series, Part 18)
How IBM Docling and the Granite vision models turn PDFs, scans, and DOCX files into clean structured chunks for RAG on watsonx, and where a vision model is worth the cost.
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watsonx Model Evaluation and Benchmarking (IBM Gen AI Series, Part 17)
How to evaluate and benchmark models and prompts on IBM watsonx using watsonx.governance, Evaluation Studio, and the ibm-watsonx-gov SDK. Score faithfulness, answer relevance, and context relevance on your own golden set, not a public leaderboard.
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watsonx Assistant, Conversational Applications End to End (IBM Gen AI Series, Part 16)
How to build a conversational application on IBM watsonx Assistant, from a first action and built-in conversational search to routing hard requests to the agent from Part 15, with the channel and cost trade-offs an architect actually weighs.
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Building Agents on watsonx Orchestrate with the ADK (IBM Gen AI Series, Part 15)
How to build a native agent on watsonx Orchestrate with the ADK, wire its tools, collaborators, and knowledge, pick the right agent style, and keep multi-agent routing from wrecking your bill.
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watsonx.ai Training Infrastructure and Scaling on OpenShift (IBM Gen AI Series, Part 14)
Every watsonx tune is a Kubernetes job under the hood. Here is how GPU nodes, the NVIDIA operators, autoscaling to zero, MIG limits, and Kueue quotas fit together on Red Hat OpenShift.
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Data Prep and Synthetic Data on watsonx.data (IBM Gen AI Series, Part 13)
How to land, clean, and curate real data in the watsonx.data lakehouse, then use the Synthetic Data Generator on watsonx.ai to fill the gaps before a tune. With a worked cost example and a runnable cleaning script.
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InstructLab on watsonx, from Taxonomy to Aligned Model (IBM Gen AI Series, Part 12)
InstructLab teaches a Granite model new skills from a handful of hand written examples, using a taxonomy, synthetic data generation, and phased training. Here is how it works on watsonx.ai and when to reach for it.
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Prompt Tuning and Fine-Tuning Granite on watsonx (IBM Gen AI Series, Part 11)
watsonx.ai gives you prompt tuning, LoRA, and full fine tuning for Granite. Here is how each method works and how to pick the right one for the size of your data.
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Granite Guardian and Hallucination Detection on watsonx (IBM Gen AI Series, Part 10)
Granite Guardian is a judge model that scores watsonx answers for hallucination. Here is where it sits in a RAG pipeline, how groundedness detection works, and where to put your block threshold.
Architect’s Toolkit
PJ’s Tools
VMware Cloud Foundation
- VCF Documentation
- VCF 9 Planning & Preparation Workbook
- VCF Bill of Materials (BoM)
- VMware Compatibility Guide
- VMware Interoperability Matrix
- VMware Configuration Maximums
- VMware Ports & Protocols
- VMware Hands-on Labs
- RVTools Download
Nutanix
AI & Cloud-Native Platform
- NVIDIA Build (Model Catalog)
- NVIDIA AI Enterprise Reference Architecture
- NVIDIA NIM Performance Benchmarking
- NVIDIA NGC Catalog
- NeMo Microservices Helm Chart
- Helm Charts Repository
- Hugging Face Models
Architecture & Design
About the Author
Dr Pranay Jha
Dr. Pranay Jha is a Cloud and AI Consultant with 18+ years of experience in hybrid cloud, virtualization, and enterprise infrastructure transformation. He specializes in VMware technologies, multi-cloud strategy, and Generative AI solutions. He holds a PhD in Computer Applications with research focused on Cloud and AI, has published multiple research papers, and has been a VMware vExpert since 2016 and a VMUG Community Leader.
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