BRICS AI Economics

Category: AI Engineering - Page 2

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May, 2 2026

Containerizing Large Language Models: A Practical Guide to CUDA, Drivers, and Image Optimization

Emily Fies
5
Learn how to containerize large language models effectively. This guide covers CUDA management, Docker image optimization, and strategies for reducing cold start times.
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May, 1 2026

How to Stop AI Hallucinations: Constraints, Quotes, and Extractive Answers

Emily Fies
10
Stop AI hallucinations with precise prompting strategies. Learn how to use constraints, quotes, and extractive answers to force large language models to deliver accurate, verifiable results instead of fabricated guesses.
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Apr, 30 2026

Abstention Policies for Generative AI: Stopping Model Hallucinations

Emily Fies
6
Learn how abstention policies prevent AI hallucinations by teaching models to say "I don't know" using uncertainty quantification and RAG.
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Apr, 27 2026

Balanced Training Data Curation for LLM Fairness: A Guide to Reducing Bias

Emily Fies
0
Learn how balanced training data curation reduces LLM bias and improves performance. Discover techniques like ClusterClip Sampling and high-fidelity labeling for fairer AI.
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Apr, 26 2026

Mastering Vibe Coding: Prompting Strategies for Rapid Development

Emily Fies
8
Learn the best prompting strategies for vibe coding to turn ideas into apps fast. Discover the six-step framework, user-action prompting, and how to avoid technical debt.
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Apr, 26 2026

Mastering Vibe Coding: Prompting Strategies for Rapid AI Development

Emily Fies
0
Learn the best prompting strategies for vibe coding to build software faster. Discover modular prompting, chained requests, and how to bridge the gap from prototype to production.
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Apr, 25 2026

AdamW vs Adafactor vs Lion: Choosing the Best LLM Optimizer

Emily Fies
8
Compare AdamW, Adafactor, and Lion optimizers for LLM training. Learn about memory overhead, convergence speed, and which one to choose for your training pipeline.
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Apr, 24 2026

Stochastic Depth and Regularization for Deep Transformer LLMs

Emily Fies
0
Explore how stochastic depth and advanced regularization techniques prevent overfitting and improve generalization in deep transformer-based LLMs.
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Apr, 22 2026

Product Design with Multimodal Generative AI: Rapid Prototypes and Iterations

Emily Fies
5
Learn how multimodal generative AI transforms product design, using text, images, and 3D data to create rapid prototypes and accelerate design iterations.
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Apr, 21 2026

How to Prevent OOM Errors in Large Language Model Inference

Emily Fies
7
Learn how to prevent OOM errors in LLM inference using memory planning, CAMELoT, and sparsification to run larger models on existing hardware.
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Apr, 16 2026

How to Optimize Cloud Costs for Generative AI: Scheduling, Autoscaling, and Spot Instances

Emily Fies
7
Learn how to slash your Generative AI cloud bills using intelligent scheduling, AI-specific autoscaling, and spot instances. Stop overprovisioning and start optimizing.
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Apr, 15 2026

Cross-Attention in Encoder-Decoder Transformers: How Conditioning Works

Emily Fies
8
Explore how cross-attention enables LLMs to condition outputs on encoder context, the core mechanism behind machine translation and multimodal transformers.

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