The paper introduces LeWorldModel (LeWM), a stable Joint-Embedding Predictive Architecture (JEPA) that trains end-to-end directly from raw pixels. Unlike existing methods that rely on complex losses, pre-trained encoders, or auxiliary supervision to prevent representation collapse, LeWM uses only two loss terms: next-embedding prediction and Gaussian latent regularization. This approach significantly simplifies the training process by reducing tunable hyperparameters. The model is highly efficient, with approximately 15 million parameters capable of being trained on a single GPU within hours, and it offers planning speeds up to 48x faster than foundation-model-based world models while remaining competitive in 2D and 3D control tasks. Additionally, the latent space effectively encodes physical structures, allowing the model to detect physically implausible events through surprise evaluation.
This is an open, unconventional textbook covering mathematics, computing, and artificial intelligence from foundational principles. It's designed for practitioners seeking a deep understanding, moving beyond exam preparation and focusing on real-world application. The author, drawing from years of experience in AI/ML, has compiled notes that prioritize intuition, context, and clear explanations, avoiding dense notation and outdated material.
The compendium covers a broad range of topics, from vectors and matrices to machine learning, computer vision, and multimodal learning, with future chapters planned for areas like data structures and AI inference.
The compendium covers a broad range of topics, from vectors and matrices to machine learning, computer vision, and multimodal learning, with future chapters planned for areas like data structures and AI inference.
Sipeed’s MaixCAM2 is a powerful, open-source AI camera designed for makers, offering significant performance improvements over Raspberry Pi and OpenMV solutions. It features the Axera Tech AX630 AI SoC with up to 12.8 TOPS and supports training-free vision models and vision-language models.
Creativity and a Jetson Orin Nano Super can help hobbyists build accessible robots that can reason and interact with the world. The article discusses building a robot using accessible hardware like Arduino and Raspberry Pi, eventually upgrading to more capable hardware like the Jetson Orin Nano Super to run a large language model (LLM) onboard.
