BRICS AI Economics

BRICS AI Economics

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Feb, 3 2026

Version Control with AI: Managing AI-Generated Commits and Diffs

Emily Fies
2
As of 2026, managing AI-generated commits and diffs requires new workflows. Teams using AI without version control adjustments face higher errors, security risks, and technical debt. Learn how to audit, review, and track AI code properly with Git and modern tools.
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Feb, 2 2026

How Curriculum and Data Mixtures Speed Up Large Language Model Scaling

Emily Fies
0
Smart data ordering and mixtures can boost LLM performance by up to 15% without larger models. Learn how curriculum learning works, what mixtures to use, and whether it’s worth the effort for your team.
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Feb, 1 2026

Measuring Data Quality for LLM Training: Model-Based and Heuristic Filters

Emily Fies
3
Measuring data quality for LLM training requires a mix of fast heuristic filters and smarter model-based systems. Learn how teams use cascaded approaches to remove low-quality data while preserving valuable content-and why skipping this step can ruin your model.
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Jan, 31 2026

Self-Consistency Prompting in Generative AI: How Voting Strategies Boost Accuracy

Emily Fies
7
Self-consistency prompting boosts AI accuracy by generating multiple reasoning paths and selecting the most common answer. It works best on math, logic, and medical tasks - not creative writing. Learn how to use it effectively.
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Jan, 30 2026

Safety Policies for Legal Use of Generative AI: Lessons from Mata v. Avianca

Emily Fies
4
The Mata v. Avianca case exposed the dangers of using generative AI for legal citations. Learn how lawyers got sanctioned for fabricating cases with ChatGPT-and what safety policies now prevent this from happening again.
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Jan, 29 2026

Edge-Capable Multimodal Large Language Models: What They Can Do and Where They Fall Short

Emily Fies
6
Edge-capable multimodal LLMs like MiniCPM-V run AI on phones without the cloud, offering privacy and speed-but they still have limits in battery life, accuracy, and complexity. Here's what they can do now and where they fall short.
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Jan, 28 2026

Event-Driven Architectures with Vibe Coding: Patterns and Prompt Templates

Emily Fies
4
Learn how to use vibe coding with event-driven architecture to build scalable systems faster. Discover proven patterns, effective prompt templates, and how frameworks like Ecotone reduce AI errors and technical debt.
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Jan, 27 2026

Executive Education on Generative AI: What Boards and C-Suite Leaders Need to Know in 2026

Emily Fies
8
Executive education programs in generative AI are now essential for boards and C-suite leaders. Learn which programs deliver real strategy, not just theory, and how to choose one that drives actual business change in 2026.
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Jan, 26 2026

Infrastructure Requirements for Serving Large Language Models in Production

Emily Fies
7
Serving large language models in production requires specialized hardware, smart scaling, and cost-aware architecture. Learn the real GPU, storage, and network needs-and how to avoid common pitfalls.
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Jan, 23 2026

Why Transformers Power Modern Large Language Models: The Core Concepts You Need

Emily Fies
6
Transformers revolutionized AI by letting language models understand context instantly. Learn how self-attention, positional encoding, and multi-head attention power today’s top LLMs - and why they’re replacing older models.
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Jan, 23 2026

Why Transformers Power Modern Large Language Models: The Core Concepts You Need

Emily Fies
9
Transformers revolutionized AI by enabling large language models to understand context across long texts using self-attention. This article explains how they work, why they beat older models, and what’s changing in 2025.
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Jan, 22 2026

How Large Language Models Are Transforming Healthcare Documentation and Triage

Emily Fies
5
Large language models are cutting documentation time for doctors and improving triage accuracy in emergency rooms. But bias, integration costs, and regulatory gaps remain major hurdles. Here’s how they’re really being used in U.S. healthcare today.

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