I need a series of well-researched technical articles that dive deep into Artificial Intelligence from a software-development perspective. The audience is other developers, so code samples, architecture diagrams, and clear explanations of the underlying math are welcome and encouraged. You’ll receive a brief outline for each topic—think model-training workflows, optimisation strategies, edge deployment, or comparative benchmarks between TensorFlow, PyTorch, and JAX—and expand it into a polished narrative of roughly 1,200–1,800 words. All content must be original, technically accurate, and written with a practical, engineering-first mindset. Deliverables • Four AI development articles delivered in Google Docs or Markdown • Any custom diagrams or screenshots referenced in the text • Proper in-text citations with a short reference list • Final copy that passes a plagiarism check Acceptance criteria • Demonstrated technical depth and correctness • Clear, developer-friendly explanations and code snippets where useful • Alignment with the outline provided and adherence to word-count range A solid background in Python, CUDA, and mainstream deep-learning libraries will make this project straightforward. Please share at least two links to previously published technical pieces on AI or related software topics. First draft of Article 1 is expected within one week of kickoff, with the rest following on a weekly cadence.