BRICS AI Economics

Category: AI Engineering

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May, 9 2026

Risk Assessments and Impact Statements for Large Language Model Projects: A Practical Guide

Emily Fies
0
Learn how to conduct effective risk assessments and write impact statements for Large Language Model projects. This guide covers bias, privacy, hallucinations, and compliance with ISO/IEC 42001.
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May, 8 2026

LLM Training Failure Modes: Why Models Crash and How to Fix Them

Emily Fies
0
Explore common failure modes in LLM training, from synthetic data traps to infrastructure crashes. Learn practical fixes for hallucinations, bias, and hardware faults.
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May, 7 2026

Anonymization vs Pseudonymization in LLM Workflows: A Practical Guide

Emily Fies
3
Compare anonymization and pseudonymization for LLM workflows. Learn which method ensures GDPR compliance, protects against inference attacks, and maintains data utility for your AI applications.
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May, 6 2026

Accessibility Risks in AI-Generated Interfaces: WCAG and Real-World Failures

Emily Fies
4
Explore the hidden accessibility risks in AI-generated interfaces. Learn why WCAG compliance fails for dynamic AI content, the legal implications under ADA and EU AI Act, and practical steps to ensure inclusive design.
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May, 4 2026

Convergence of Generative AI with Blockchain and Cryptography: Security and Privacy Potential

Emily Fies
6
Explore how merging Generative AI with Blockchain and Cryptography solves trust issues. Learn about zero-knowledge proofs, homomorphic encryption, and real-world security benefits for data privacy.
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May, 3 2026

Privacy-Aware RAG: How to Stop Sensitive Data Leaks in AI (2026 Guide)

Emily Fies
0
Learn how Privacy-Aware RAG prevents sensitive data leaks in enterprise AI. Compare architectural approaches, understand accuracy trade-offs, and discover implementation strategies for GDPR and HIPAA compliance in 2026.
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May, 2 2026

Containerizing Large Language Models: A Practical Guide to CUDA, Drivers, and Image Optimization

Emily Fies
5
Learn how to containerize large language models effectively. This guide covers CUDA management, Docker image optimization, and strategies for reducing cold start times.
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May, 1 2026

How to Stop AI Hallucinations: Constraints, Quotes, and Extractive Answers

Emily Fies
10
Stop AI hallucinations with precise prompting strategies. Learn how to use constraints, quotes, and extractive answers to force large language models to deliver accurate, verifiable results instead of fabricated guesses.
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Apr, 30 2026

Abstention Policies for Generative AI: Stopping Model Hallucinations

Emily Fies
6
Learn how abstention policies prevent AI hallucinations by teaching models to say "I don't know" using uncertainty quantification and RAG.
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Apr, 27 2026

Balanced Training Data Curation for LLM Fairness: A Guide to Reducing Bias

Emily Fies
0
Learn how balanced training data curation reduces LLM bias and improves performance. Discover techniques like ClusterClip Sampling and high-fidelity labeling for fairer AI.
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Apr, 26 2026

Mastering Vibe Coding: Prompting Strategies for Rapid Development

Emily Fies
8
Learn the best prompting strategies for vibe coding to turn ideas into apps fast. Discover the six-step framework, user-action prompting, and how to avoid technical debt.
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Apr, 26 2026

Mastering Vibe Coding: Prompting Strategies for Rapid AI Development

Emily Fies
0
Learn the best prompting strategies for vibe coding to build software faster. Discover modular prompting, chained requests, and how to bridge the gap from prototype to production.

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