BRICS AI Economics

Category: AI Engineering

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Oct, 17 2026

Stopping AI Hallucinations: Practical Mitigation Strategies for Generative Models

Emily Fies
0
Generative AI hallucinations occur when models produce plausible but false information. Learn practical mitigation strategies like RAG, RLHF, and prompt engineering to improve accuracy.
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Oct, 16 2026

Pair Reviewing with AI: Human + Model Code Review Workflows

Emily Fies
1
Stop waiting on slow code reviews. Learn how to integrate AI tools like GitHub Copilot and Greptile into your workflow to catch bugs faster while keeping humans focused on architecture.
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Oct, 14 2026

Scaling Laws in Practice: When to Stop Training Large Language Models

Emily Fies
0
Learn how to determine the optimal stopping point for LLM training. We compare Kaplan and Chinchilla scaling laws, explain why overtraining is common in production, and provide practical metrics for saving compute.
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Oct, 13 2026

Do Bigger LLMs Actually Pay Off? Benchmarking Scaling Returns

Emily Fies
0
Discover why bigger LLMs don't always mean better ROI. Learn to benchmark scaling outcomes using cost-efficiency and real-world utility instead of just parameter counts.
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Oct, 12 2026

Prompt Robustness: Handling Noisy Inputs in LLMs

Emily Fies
8
Learn how to build resilient LLM systems by mastering prompt robustness. Discover strategies like RoP and MOF to handle noisy inputs, typos, and user variations effectively.
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Oct, 8 2026

Benchmarking Vibe Coding Tool Output Quality Across Frameworks

Emily Fies
0
Discover how top AI models stack up in recent vibe coding benchmarks. Learn which tools deliver the highest accuracy, where they fail, and how to choose the right framework for your workflow.
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Oct, 7 2026

Curriculum and Blending: How to Mix Datasets for Better Large Language Models

Emily Fies
9
Discover how curriculum learning and dataset blending optimize LLM training. Learn strategies for ordering data, measuring difficulty, and improving performance without extra compute.
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Oct, 5 2026

Mastering Self-Ask and Decomposition Prompts for Complex LLM Questions

Emily Fies
0
Learn how Self-Ask and decomposition prompting enhance LLM accuracy on complex questions. Discover implementation steps, compare techniques, and avoid common pitfalls.
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Oct, 4 2026

Self-Attention in Transformers: How LLMs Understand Context

Emily Fies
5
Discover how self-attention powers Large Language Models. Learn the QKV framework, multi-head mechanics, and why this 2017 innovation revolutionized AI understanding.
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Oct, 2 2026

Flash Attention: Speeding Up LLM Inference and Training

Emily Fies
5
Discover how Flash Attention revolutionizes LLM performance by cutting memory usage and boosting speed. Learn the tech behind it, real-world gains, and how to implement it.
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Oct, 1 2026

Context Windows in LLMs: Limits, Trade-Offs & Best Practices

Emily Fies
0
Explore how LLM context windows work, from token limits to hardware constraints. Learn why bigger isn't always better and discover best practices for managing long conversations and documents efficiently.
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Sep, 30 2026

Privacy Notices and Cookie Banners in Vibe-Coded Frontends

Emily Fies
8
Vibe-coded frontends often overlook privacy compliance. Learn how to implement GDPR-compliant cookie banners and privacy notices without sacrificing user experience or development speed.

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