BRICS AI Economics

Dec, 30 2025

How to Detect Implicit vs Explicit Bias in Large Language Models

Emily Fies

Large language models may seem fair on the surface, but hidden biases persist-even in the most advanced systems. Learn how to detect implicit bias that standard tests miss and why bigger models aren't necessarily fairer.

Dec, 29 2025

Human-in-the-Loop Operations for Generative AI: Review, Approval, and Exceptions

Emily Fies

Human-in-the-loop operations for generative AI ensure AI outputs are reviewed, approved, and corrected by humans before deployment - critical for compliance, safety, and trust in regulated industries.

Dec, 28 2025

Energy Efficiency in Generative AI Training: Sparsity, Pruning, and Low-Rank Methods

Emily Fies

Learn how sparsity, pruning, and low-rank methods cut generative AI training energy by 30-80% without sacrificing accuracy. Real-world data, implementation tips, and future trends.

Dec, 25 2025

Democratization of Software Development Through Vibe Coding: Who Can Build Now

Emily Fies

Vibe coding lets anyone build software by describing ideas in plain language. No coding experience needed. From students to small business owners, more people than ever can now create apps-with AI doing the heavy lifting.

Dec, 24 2025

Testing and Monitoring RAG Pipelines: Synthetic Queries and Real Traffic

Emily Fies

Testing RAG pipelines requires both synthetic queries for controlled evaluation and real traffic monitoring to catch real-world failures. Learn how to balance cost, accuracy, and speed to build reliable AI systems.

Nov, 19 2025

Supply Chain Optimization with Generative AI: Demand Forecast Narratives and Exceptions

Emily Fies

Generative AI is transforming supply chain demand forecasting by turning numbers into explainable narratives and helping teams handle exceptions before they become crises. Learn how it works, who’s using it, and what you need to get started.

Oct, 16 2025

Why Large Language Models Excel at Many Tasks: Transfer, Generalization, and Emergent Abilities

Emily Fies

Large language models excel because they learn from massive text data, then adapt to new tasks with minimal examples. Transfer learning, generalization, and emergent abilities make them powerful without needing custom training for every job.

Oct, 5 2025

Cost-Performance Tuning for Open-Source LLM Inference: How to Slash Costs Without Losing Quality

Emily Fies

Learn how to cut LLM inference costs by 70-90% using open-source tools like vLLM, quantization, and Multi-LoRA-without sacrificing performance. Real-world strategies for startups and enterprises.

Sep, 22 2025

Why Transformers Replaced RNNs in Modern Language Models

Emily Fies

Transformers replaced RNNs because they process language faster and understand long-range connections better. With self-attention, they handle entire sentences at once-making modern AI possible.

Sep, 15 2025

How Large Language Models Handle What They Don't Know: Communicating Uncertainty

Emily Fies

Large language models often answer confidently even when they're wrong. Learn how knowledge boundaries and uncertainty communication help them admit when they don't know, reducing hallucinations and building trust in real-world applications.

Sep, 14 2025

Disaster Recovery for Large Language Model Infrastructure: Backups and Failover

Emily Fies

Disaster recovery for large language models requires specialized backups and failover systems to protect massive model weights, training data, and inference APIs. Learn how to build a resilient AI infrastructure that survives outages.

Aug, 24 2025

Cursor, Replit, Lovable, and Copilot: Best AI Coding Tools for 2025

Emily Fies

Compare Cursor, Replit, Lovable, and GitHub Copilot in 2025 to find the best AI coding tool for your skill level and project. Learn which one saves time, improves code quality, and fits your workflow.

BRICS AI Economics - Page 4

How to Detect Implicit vs Explicit Bias in Large Language Models

Human-in-the-Loop Operations for Generative AI: Review, Approval, and Exceptions

Energy Efficiency in Generative AI Training: Sparsity, Pruning, and Low-Rank Methods

Democratization of Software Development Through Vibe Coding: Who Can Build Now

Testing and Monitoring RAG Pipelines: Synthetic Queries and Real Traffic

Supply Chain Optimization with Generative AI: Demand Forecast Narratives and Exceptions

Why Large Language Models Excel at Many Tasks: Transfer, Generalization, and Emergent Abilities

Cost-Performance Tuning for Open-Source LLM Inference: How to Slash Costs Without Losing Quality

Why Transformers Replaced RNNs in Modern Language Models

How Large Language Models Handle What They Don't Know: Communicating Uncertainty

Disaster Recovery for Large Language Model Infrastructure: Backups and Failover

Cursor, Replit, Lovable, and Copilot: Best AI Coding Tools for 2025

Categories

Latest Courses

Generative AI in Business Operations: High-Impact Use Cases and Implementation Patterns

Video Understanding with Generative AI: Captioning, Summaries, and Scene Analysis

Stepwise Prompting with Feedback Loops: A Practical Guide to Iterative Code Generation

Vibe Coding for Operations Teams: Automate Workflows and Build Internal Dashboards with AI

Liability Considerations for Generative AI: Vendor, User, and Platform Responsibilities

Popular Tags