Category: Artificial Intelligence

Tess Rempel Jan, 16 2026 Artificial Intelligence

How to Calibrate Confidence in Non-English LLM Outputs

LLMs often overstate their confidence in non-English responses, creating dangerous blind spots. Learn why calibration fails across languages and how to protect yourself today.

Tess Rempel Jan, 15 2026 Artificial Intelligence

Flash Attention: How Memory Optimizations Speed Up Large Language Model Inference

Flash Attention slashes memory use and speeds up LLM inference by optimizing how attention computations move data in GPU memory. It enables 32K+ token contexts without accuracy loss, and is now standard in top models like Llama 3 and Claude 3.

Tess Rempel Jan, 14 2026 Artificial Intelligence

Fairness Testing for Generative AI: Metrics, Audits, and Remediation Plans

Fairness testing for generative AI ensures AI systems don't reinforce bias in text, images, and decisions. Learn key metrics, audit methods, and real-world remediation plans used by leading companies in 2026.

Tess Rempel Jan, 13 2026 Artificial Intelligence

How Large Language Models Learn: Self-Supervised Training at Internet Scale

Large language models learn by predicting the next word in trillions of internet text samples using self-supervised training. This method powers GPT-4, Claude 3, and Llama 3, but comes with trade-offs in accuracy, bias, and cost.

Tess Rempel Jan, 11 2026 Artificial Intelligence

Accessibility-Inclusive Vibe Coding: Build WCAG-Compliant Interfaces by Default

Accessibility-inclusive vibe coding combines AI-assisted development with WCAG 2.2 patterns to build accessible interfaces by default. Learn how to reduce fixes, avoid audits, and create truly inclusive digital products.

Tess Rempel Jan, 7 2026 Artificial Intelligence

Style Transfer Prompts in Generative AI: How to Control Tone, Voice, and Format

Learn how to use style transfer prompts in generative AI to control tone, voice, and format for consistent, high-performing content. Get practical methods, tool comparisons, and real-world fixes for common mistakes.

Tess Rempel Dec, 29 2025 Artificial Intelligence

Security Telemetry and Alerting for AI-Generated Applications: What You Need to Know

AI-generated apps need new security tools. Learn how security telemetry tracks AI behavior, detects prompt injection and model poisoning, and reduces response times by 52%. Essential for teams deploying AI in production.

Tess Rempel Dec, 25 2025 Artificial Intelligence

NLP Pipelines vs End-to-End LLMs: When to Use Composed Systems vs Prompt Engineering

NLP pipelines and end-to-end LLMs aren't rivals-they're teammates. Learn when to use each for speed, cost, and accuracy, and how to combine them into hybrid systems that outperform either alone.

Tess Rempel Dec, 22 2025 Artificial Intelligence

Quality Control for Multimodal Generative AI Outputs: Human Review and Checklists

Human review and structured checklists are essential for catching hidden errors in multimodal AI outputs. Learn how top industries like biopharma and manufacturing use verified workflows to ensure accuracy, compliance, and safety.

Tess Rempel Dec, 22 2025 Artificial Intelligence

HR Automation with Generative AI: Job Descriptions, Interview Guides, and Onboarding

Generative AI is transforming HR by automating job descriptions, interview guides, and onboarding-saving time, reducing bias, and improving candidate experience. Learn how to use it wisely without losing the human touch.

Tess Rempel Dec, 11 2025 Artificial Intelligence

Content Moderation for Generative AI Outputs: Safety Classifiers and Redaction Explained

Learn how safety classifiers and redaction systems protect users from harmful AI outputs, why current tools struggle with context and culture, and how to implement them without killing creativity. Real data, real cases, no fluff.

Tess Rempel Nov, 21 2025 Artificial Intelligence

Multi-Agent Systems with LLMs: How Specialized AI Agents Work Together to Solve Complex Problems

Multi-agent systems with LLMs use specialized AI agents that collaborate to solve complex tasks better than single models. Learn how role specialization, frameworks like MacNet and Chain-of-Agents, and latent communication are changing AI capabilities in 2025.