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9 articles
Learn to build a fair use classifier for AI training content that helps determine whether copyrighted material qualifies for fair use under US copyright law.
Learn what computer-use agents are, how they work, and why AI labs are investing heavily in Apple hardware to train them.
How Xiaomi's robot learned to move by watching humans, and why more data beats bigger models in AI.
This article explains how copyright law applies to AI training, using simple analogies to help readers understand the complex legal issues surrounding AI development and content creators' rights.
Learn how to build a model training pipeline that simulates the scenario of one AI organization training on another's models, similar to the Musk vs. OpenAI legal dispute.
Learn to build a basic video recording application using Python and OpenCV, demonstrating the technology behind AI training data collection systems like DoorDash's new Tasks app.
Learn to set up and use the UR AI Trainer for capturing robot training data, integrating force, motion, and visual sensors for imitation learning.
Learn how to build a basic emotion recognition system using Python that mimics how AI companies are training systems with improv actors' emotional skills.
This article explains how virtual simulation data is revolutionizing physical AI development by enabling efficient training of robotic agents that can perform real-world tasks. It covers the concepts of sim-to-real transfer, domain randomization, and the role of platforms like AI2 and MolmoBot.
