How large language models actually work
A practical introduction to LLMs: what they learn, why they predict tokens and where they fail.
THE JOURNAL
The journal
Accessible AI education, research context and practical guidance.
12 articles · Source-linked educational writing
AI agents: beyond the chatbot interface
Learn how agents use tools and memory, why orchestration matters and where human approval belongs.
How to read an AI research paper critically
Avoid paper hype: inspect the question, baselines, evaluation setup and limitations before trusting a result.
Computer vision: from pixels to predictions
Understand the main computer-vision tasks, typical model families and how to evaluate real-world performance.
Text-to-image AI: what Midjourney illustrates
A practical look at image synthesis, creative iteration and the need to check usage rights.
AI in drug discovery: promise and boundaries
Explore target discovery, molecule screening and the scientific limits of AI-assisted pharmaceutical research.
Understanding text-to-video generation
A primer on video synthesis, temporal consistency and responsible media provenance.
AI copilots at work: a practical evaluation guide
How teams can evaluate coding and productivity copilots without relying on marketing claims.
RAG vs fine-tuning: choosing the right approach
When should an AI product retrieve documents, fine-tune a model, or simply improve its prompt?
AI infrastructure: GPUs, memory and inference cost
A practical overview of accelerators, bandwidth, batching and the trade-offs of AI infrastructure.
Building safer AI products: a developer checklist
Practical controls for applications using external models, user prompts and connected tools.
A realistic roadmap to start learning AI
Move from Python and linear algebra to practical ML, PyTorch and a credible portfolio.