multimodal AI
The human brain seamlessly integrates sight, sound, and touch. Replicating this took a decade of AI research and seven critical innovations that now power today's video and image generation systems.
AI Architecture
From Transformers to GANs, these five foundational architectures form the backbone of AI video generation, deepfake creation, and synthetic media systems that every engineer should understand.
transformers
Deep technical comparison of transformer and mixture of experts architectures, exploring how MoE models achieve computational efficiency while maintaining performance in modern AI systems including video generation.
GPT
A detailed technical walkthrough of training transformer-based language models on consumer hardware, covering tokenization, architecture implementation, training optimization, and resource management on Apple Silicon.
transformers
Learn to implement transformer components and mini-GPT models from the ground up using Tinygrad. This technical deep dive covers attention mechanisms, layer normalization, and neural network fundamentals to understand how modern AI systems work.
Generative AI
A technical deep dive into the major families of generative AI models—from GANs and VAEs to diffusion models and transformers—that power today's synthetic media, deepfakes, and AI video generation tools.
transformers
Understanding the attention mechanism is essential for grasping how modern AI generates video, text, and synthetic media. This technical guide breaks down the architecture that powers everything from GPT to deepfake generators.
LLM Architecture
Deep dive into the technical progression of large language model architectures, from the foundational Transformer through Mixture of Experts to cutting-edge Mixture of Routers, examining how each innovation addresses scaling and efficiency challenges.