Leap Nonprofit AI Hub - Page 2

How to Build Compute Budgets and Roadmaps for Scaling Large Language Model Programs

Learn how to build realistic compute budgets and roadmaps for scaling large language models without overspending. Discover cost-saving strategies, hardware choices, and why smaller models often outperform giants.

Sparse Mixture-of-Experts in Generative AI: How It Scales Without Breaking the Bank

Sparse Mixture-of-Experts lets AI models scale efficiently by activating only a few specialized subnetworks per input. Discover how Mixtral 8x7B matches 70B model performance at 13B cost, and why this is the future of generative AI.

Security Basics for Non-Technical Builders Using Vibe Coding Platforms

Non-technical builders using AI coding tools like Replit or GitHub Copilot must avoid hardcoded secrets, use HTTPS, sanitize inputs, and manage environment variables. These five simple rules prevent 90% of security breaches in vibe-coded apps.

Compression for Edge Deployment: Running LLMs on Limited Hardware

Learn how to run large language models on smartphones and IoT devices using model compression techniques like quantization, pruning, and knowledge distillation. Real-world results, hardware tips, and step-by-step deployment.

Third-Country Data Transfers for Generative AI: GDPR and Cross-Border Compliance in 2025

GDPR restricts personal data transfers to third countries unless strict safeguards are in place. With generative AI processing data globally, businesses face real compliance risks - and heavy fines. Learn what you must do in 2025 to stay legal.

Ethical Guidelines for Deploying Large Language Models in Regulated Domains

Ethical deployment of large language models in healthcare, finance, and justice requires more than good intentions. It demands continuous monitoring, cross-functional oversight, and domain-specific safeguards to prevent harm and ensure accountability.

Scaling for Reasoning: How Thinking Tokens Are Rewriting LLM Performance Rules

Thinking tokens are changing how AI reasons - not by making models bigger, but by letting them think longer at the right moments. Learn how this new approach boosts accuracy on math and logic tasks without retraining.

Model Lifecycle Management: Versioning, Deprecation, and Sunset Policies Explained

Learn how versioning, deprecation, and sunset policies form the backbone of responsible AI. Discover why enterprises use them to avoid compliance failures, reduce risk, and ensure model reliability.

When Vibe Coding Works Best: Project Types That Benefit from AI-Generated Code

AI-generated code works best for repetitive tasks like forms, APIs, tests, and UI components - not for security-critical or complex logic. Learn which projects benefit most from vibe coding.

Impact Assessments for Generative AI: DPIAs, AIA Requirements, and Templates

Generative AI requires strict impact assessments under GDPR and the EU AI Act. Learn what DPIAs and FRIAs are, when they're mandatory, which templates to use, and how to avoid costly fines.

California AI Transparency Act: What You Need to Know About Generative AI Detection Tools and Content Labels

California's AI Transparency Act (AB 853) requires major platforms to label AI-generated media and offer free detection tools. Learn how it works, what it covers, and why it matters for creators and users.

Vibe Coding for Knowledge Workers: Tools That Save Hours Every Week

Vibe coding lets knowledge workers build custom apps using plain language instead of code, saving 12-15 hours weekly. Tools like Knack and Memberstack turn natural prompts into working dashboards, automations, and tools - no programming needed.