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Created November 9, 2025 03:07
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10 Foundational AI Building Block Concepts for Testers and Developers on https://qualitywithmillan.github.io
# Building Block Concept Short Description Reference Link
1 Foundation Models Large AI neural networks trained on massive raw data, enabling broad understanding and generation tasks. NVIDIA Blog - Foundation Models
2 Machine Learning Basics Core ML concepts like supervised, unsupervised learning foundational to AI applications. Microsoft Learn AI Fundamentals
3 Natural Language Processing & LLMs Techniques for understanding and generating human language using models like GPT and LLaMA. NVIDIA Blog - Open Reasoning Models
4 AI Model Training & Evaluation Methods for training models, tuning hyperparameters, and measuring model accuracy and robustness. OpenAI & NVIDIA Open Models
5 AI Agents & Automation Building goal-oriented autonomous agents for tasks like software testing automation and decision making. Reddit AI Agents
6 Responsible AI & Ethics Principles ensuring AI fairness, bias mitigation, transparency, and accountability in AI systems. Microsoft AI Responsible Use
7 Data Infrastructure for AI Data collection, cleansing, and pipeline management fundamental for high-quality AI inputs. NVIDIA Blog - AI Systems Building Blocks
8 Generative AI Models capable of creating content such as text, images, and videos, powering creative applications. NVIDIA Blog - GPT and Generative AI
9 AI Development Ecosystems & Tools Platforms like Hugging Face, CUDA, and frameworks facilitating AI model development & deployment. Hugging Face Blog
10 Industry Collaboration & AI Research Trends Recent AI breakthroughs and collaborations driving innovation in hardware and software ecosystems. Perplexity AI Blog Deep Dive
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