Galileo vs GenAI Lab

The goal with Galileo is to explain with simple words, the complex yet beautiful physics that is inside everything in our world. Contents are presented in small articles, written with a simple language. The articles covers various topics from mechanics to nuclear physics. Articles includes images, animations, 3D models and sometimes a little equation. Get a better understanding of physics with Augmented Reality! Place experiments and animated 3D models on you table and explore them by moving around.

GenAI Lab is an offline, hands-on course for understanding and prototyping generative AI systems, one experiment at a time. Learn how modern AI actually works by exploring it visually and interactively, right on your iPhone. No internet, no account, no tracking. A GUIDED CURRICULUM The course spans 8 tracks and 52 short missions covering: - GenAI foundations - Transformers and LLMs - Prompt engineering - Retrieval-augmented generation (RAG) - Image generation - Fine-tuning - Evaluation and safety - Multimodal AI and agents Every mission combines a concept check, a matching activity, and a guided Python code fragment so you learn by doing, not just reading. TRANSFORMER ARCADE Six short visual games and six boss challenges bring the internals of transformers to life: - Tokenization - Embeddings - Attention - Multi-head attention - Transformer blocks - Next-token generation Arcade rounds are untimed, offline, replayable, and use deterministic simulations so you can inspect exactly what is happening. LEARN BY EXPERIMENT The built-in simulators use deliberately small, deterministic examples so you can inspect attention weights, prompts, retrieval, diffusion controls, and agent loops step by step. Code activities validate guided fragments to build your intuition; the app does not execute arbitrary code. PRIVATE BY DESIGN Your progress is stored only on your device. GenAI Lab has no account, no ads, no analytics SDK, and makes no network requests. Learn anywhere, even completely offline. WHO IT IS FOR - Students and self-learners exploring how generative AI works - Engineers who want a clear mental model of transformers, LLMs, RAG, and agents - Anyone curious about the ideas behind modern AI, in a focused, no-pressure environment Questions or feedback? Email kshravi86@gmail.com.