SCC Comets

Tess Rempel May, 18 2026 Artificial Intelligence

Understanding Bias in Large Language Models: Sources, Types, and Risks

Explore the sources, types, and real-world risks of bias in Large Language Models. Learn how data selection, architectural flaws, and deployment contexts create unfair outcomes in hiring, healthcare, and law, and discover proven mitigation strategies.

Tess Rempel May, 17 2026 Artificial Intelligence

Rapid Prototyping with APIs vs Production Hardening with Open-Source LLMs

Discover why most AI prototypes fail in production. Learn how to transition from costly GPT-4 APIs to efficient, self-hosted open-source LLMs using LoRA and hybrid routing strategies for scalable, private, and cost-effective AI applications.

Tess Rempel May, 16 2026 Software Architecture

Benchmarking LLM Serving Stacks: Realistic Loads and Production Patterns

Learn how to benchmark LLM serving stacks with realistic loads. We cover client vs server-side testing, key metrics like TTFT and QPS, and tools like vLLM and GenAI-Perf for production-ready AI infrastructure.

Tess Rempel May, 15 2026 Artificial Intelligence

Data Privacy in LLM Training Pipelines: PII Redaction and Governance Guide

Protect your AI projects from data leaks. Learn how to implement PII redaction, differential privacy, and governance in LLM training pipelines to meet GDPR and HIPAA standards.

Tess Rempel May, 14 2026 Artificial Intelligence

Privacy-Preserving Generative AI: Homomorphic Encryption and Secure Enclaves

Explore how homomorphic encryption and secure enclaves enable privacy-preserving generative AI. Learn about the shift from theoretical crypto to practical 2026 deployments in healthcare and finance.

Tess Rempel May, 13 2026 Artificial Intelligence

Schema-Constrained Prompts: Forcing JSON and Structured Outputs from LLMs

Learn how schema-constrained prompts force LLMs to produce valid JSON outputs. Explore constrained decoding, finite state machines, and practical tools for reliable structured data extraction in production.

Tess Rempel May, 12 2026 Artificial Intelligence

Implementing Generative AI Responsibly: Governance, Oversight, and Compliance Guide

A practical guide to implementing Generative AI governance, covering compliance with the EU AI Act, NIST frameworks, and strategies to overcome common implementation challenges.

Tess Rempel May, 11 2026 Artificial Intelligence

How to Build Human Feedback Loops for RAG Relevance

Learn how to build human feedback loops for RAG systems to boost accuracy by up to 7%. Explore the Pistis-RAG framework, implementation challenges, and tools like Label Studio for continuous improvement.

Tess Rempel May, 10 2026 Artificial Intelligence

Vibe Coding vs Traditional Programming: Key Differences for Developers and Teams

Explore the key differences between vibe coding and traditional programming. Learn when to use each approach for better software development outcomes.

Tess Rempel May, 9 2026 Artificial Intelligence

Benchmarking the NLP Renaissance: How Large Language Models Stack Up in 2026

Explore the 2026 LLM landscape: Gemini 2.5 Pro leads benchmarks, but open-source models like Llama 4 Scout redefine context limits. Discover how MoE architectures and efficiency shifts change AI deployment strategies.

Tess Rempel May, 8 2026 Artificial Intelligence

LLM Risk Management: Essential Controls and Escalation Paths for 2026

Explore essential strategies for managing Large Language Model risks. Learn about technical controls, continuous monitoring, and clear escalation paths to ensure safe AI deployment in 2026.

Tess Rempel May, 7 2026 Software Architecture

Architectural Innovations Powering Modern Generative AI Systems

Discover how architectural innovations like Mixture-of-Experts and verifiable reasoning are transforming generative AI. Learn why system-level intelligence beats monolithic models in speed, cost, and reliability for 2026 enterprises.