BRICS AI Economics

BRICS AI Economics

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Oct, 27 2026

Handling Multilingual Data in Large Language Model Pretraining Pipelines

Emily Fies
0
Discover how to break the curse of multilinguality in LLM pretraining. Learn why token allocation matters more than language count, how English acts as a pivot, and why model-based filtering beats rule-based heuristics.
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Oct, 26 2026

Vibe Coding Security: What Buyers Must Assess Before Adoption

Emily Fies
2
Discover the hidden security risks of vibe coding platforms. Learn why static analysis fails, compare major tools like GitHub Copilot and Cursor, and get a buyer's checklist to secure your AI-assisted development workflow.
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Oct, 25 2026

Chinchilla Scaling Laws: The Compute-Optimal Ratio for LLM Training

Emily Fies
0
Discover how Chinchilla scaling laws optimize LLM training by balancing model size and data volume. Learn the 20:1 ratio, its limits, and practical application.
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Oct, 24 2026

Risk Management for Large Language Models: Controls and Escalation Paths

Emily Fies
0
Discover how to manage LLM risks effectively. Learn about dynamic controls, escalation paths, and governance strategies for generative AI.
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Oct, 23 2026

Privacy by Design Prompts: How to Instruct AI to Limit Data Collection

Emily Fies
3
Learn how to apply Privacy by Design principles to AI by crafting prompts that limit data collection. Discover strategies for data minimization, dynamic consent, and regulatory compliance in LLMs.
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Oct, 22 2026

Layered Architecture in Vibe-Coded Apps: Enforcing Separation of Concerns

Emily Fies
0
Discover how vibe coding impacts layered architecture and learn strategies to enforce separation of concerns in AI-generated codebases.
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Oct, 21 2026

The Hidden Price Tag: Change Management Costs in Generative AI Programs

Emily Fies
7
Discover the true cost of generative AI adoption. Learn why change management, training, and process redesign consume 15-25% of budgets and how strategic spending boosts ROI.
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Oct, 20 2026

Output Filtering: Blocking Sensitive and Harmful LLM Responses

Emily Fies
0
Discover how output filtering protects AI applications by blocking harmful or sensitive LLM responses. Learn about layered defense strategies, PII detection, and tools like AWS Bedrock and Cloudflare.
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Oct, 19 2026

Generative AI ROI: Real Case Studies and Lessons from Early Adopters

Emily Fies
0
Discover the real ROI of generative AI through case studies from Coca-Cola, Klarna, and healthcare. Learn why 95% of pilots fail and how successful adopters measure value beyond cost savings.
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Oct, 18 2026

Cutting LLM Costs: Prompt Length, Batching, and Caching Strategies

Emily Fies
6
Discover how to cut LLM costs by up to 80% using prompt trimming, batch processing, and semantic caching. Learn practical strategies to optimize AI spending without sacrificing quality.
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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
8
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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