BRICS AI Economics

Category: AI Engineering - Page 2

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Jul, 25 2026

Tokens per Parameter: The Real Data Ratio for Training LLMs

Emily Fies
9
Discover the optimal tokens per parameter ratio for training LLMs. Learn how scaling laws, the Chinchilla study, and data quality impact model efficiency and performance in 2026.
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Jul, 23 2026

Hybrid Search for RAG: Combining Semantic and Keyword Retrieval for LLMs

Emily Fies
0
Discover how hybrid search combines semantic and keyword retrieval to boost RAG accuracy. Learn about BM25, vector fusion, and implementation strategies for LLMs.
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Jul, 22 2026

How to Establish Coding Standards for Vibe-Coded Repositories in 2026

Emily Fies
0
Learn how to establish robust coding standards for vibe-coded repositories. Discover strategies for prompt engineering, context management with MCP, and automated safety layers to ensure maintainable AI-generated code.
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Jul, 19 2026

Parameter-Efficient Fine-Tuning: Mastering LoRA and Adapters for LLMs in 2026

Emily Fies
5
Learn how to fine-tune large language models efficiently using LoRA and Adapters. Discover the technical differences, implementation steps with Hugging Face PEFT, and 2026 trends like QLoRA and FlexLLM.
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Jul, 18 2026

Causal vs Bidirectional Attention: Tradeoffs in Modern LLMs

Emily Fies
7
Explore the critical tradeoffs between causal and bidirectional attention in modern LLMs. Learn how these mechanisms impact performance, speed, and suitability for different AI tasks.
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Jul, 16 2026

Data Augmentation for LLM Fine-Tuning: Synthetic and Human-in-the-Loop Approaches

Emily Fies
9
Learn how to boost LLM fine-tuning performance using synthetic data generation and human-in-the-loop strategies. Explore practical steps for data augmentation with LoRA and PEFT.
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Jul, 14 2026

Transformer Efficiency Tricks: Mastering KV Caching and Continuous Batching for LLM Serving

Emily Fies
9
Master LLM serving efficiency with KV caching and continuous batching. Learn how to reduce latency, optimize GPU memory, and boost throughput in 2026.
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Jul, 13 2026

Observability for LLM Inference: Token Metrics, Queues, and Tail Latency

Emily Fies
6
Master LLM inference observability by tracking token metrics, queue dynamics, and tail latency. Learn why RPS fails and how to optimize TTFT and throughput for production stability.
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Jul, 12 2026

Safety by Design in Generative AI: Embedding Protections into Product Architecture

Emily Fies
0
Discover how Safety by Design embeds protections into generative AI architecture. Learn about Thorn's framework, NIST standards, and the shift from reactive moderation to proactive engineering.
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Jul, 10 2026

ROI Modeling for Vibe Coding: Calculating Cost, Speed, and Quality Gains in 2026

Emily Fies
0
Calculate the true ROI of vibe coding in 2026. We break down cost savings, speed gains, and hidden technical debt risks to help you decide if AI-assisted development is right for your team.
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Jul, 8 2026

Cost-Quality Frontiers: Selecting the Best Large Language Model for ROI in 2026

Emily Fies
0
Discover how to maximize ROI in 2026 by navigating the cost-quality frontier. Compare value-tier LLMs like GPT-5 Mini and Grok 4 Fast, learn portfolio strategies, and avoid common pitfalls.
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Jul, 7 2026

Service Level Objectives for Maintainability: Indicators and Alerts

Emily Fies
10
Learn how to implement Service Level Objectives for maintainability. Discover key indicators like MTTR and deployment frequency, set realistic error budgets, and configure alerts that boost engineering velocity without sacrificing reliability.

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