BRICS AI Economics

BRICS AI Economics

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Nov, 5 2026

Generative AI in Education: Curriculum, Assessment & Tutoring

Emily Fies
0
Discover how Generative AI transforms education through dynamic curriculum design, adaptive assessment, and personalized tutoring. Learn practical strategies for implementing AI tools in classrooms.
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Nov, 4 2026

AI Code Is Guilty Until Proven Secure: A Policy Framework for Teams

Emily Fies
0
Discover why AI-generated code must be treated as 'guilty until proven secure.' Learn how to build a zero-trust policy framework, implement automated technical controls, and foster a culture of skepticism to protect your applications from emerging AI-related security risks.
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Nov, 3 2026

Prompt Engineering for LLMs: Core Principles and Proven Patterns

Emily Fies
3
Master prompt engineering for LLMs with core principles like specificity and context. Learn proven patterns including few-shot, chain-of-thought, and role assignment to boost AI accuracy.
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Nov, 2 2026

Domain-Specialized Generative AI: Why Vertical Excellence Beats General Purpose

Emily Fies
0
Discover why domain-specialized generative AI models outperform general-purpose LLMs in accuracy and compliance. Learn how vertical excellence drives enterprise ROI.
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Nov, 1 2026

Watermarking AI Content: Methods, Limits, and Detection

Emily Fies
4
Discover how AI watermarking works, from SynthID to C2PA, and learn why detection remains challenging despite new regulations.
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Oct, 31 2026

Mathematical Reasoning Benchmarks for Next-Gen LLMs: The Truth Behind the Scores

Emily Fies
0
Explore the reality behind LLM math scores. Discover why high benchmark results hide reasoning flaws and how hybrid architectures offer the future.
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Oct, 30 2026

Governance ROI for Generative AI: Cutting Incidents and Boosting Audit Readiness

Emily Fies
5
Discover how Governance ROI transforms Generative AI from a risky experiment into a reliable business asset. Learn how policy-as-code and automated evidence reduce incidents and ensure perpetual audit readiness.
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Oct, 29 2026

Mixed-Precision Training for LLMs: FP16, BF16, and FP8 Explained

Emily Fies
7
Discover how mixed-precision training with FP16, BF16, and FP8 slashes LLM training costs and time. Learn why BF16 is the new standard for stability and how to implement it in PyTorch.
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Oct, 28 2026

Vibe Coding Policies: A Practical Guide to Allow, Limit, and Prohibit AI Code

Emily Fies
6
Discover how to govern AI-assisted development with clear vibe coding policies. Learn what to allow, limit, and prohibit to prevent security flaws and maintain code quality.
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Oct, 27 2026

Handling Multilingual Data in Large Language Model Pretraining Pipelines

Emily Fies
6
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
7
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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