Cerebras Sets Record for Largest AI Models Ever Trained on Single Device - Cerebras

This post details the challenges and complexity of training large AI models (up to 20 billion parameters) on distributed GPU clusters, requiring months of engineering effort for hybrid parallelism (data, pipeline, and tensor model parallelism). It contrasts this with the Cerebras CS-2 system, which allows for the training of these large models on a single device with minutes of setup time, simplifying the process and making it accessible to a wider range of users. The post emphasizes that the primary challenge in training large models is often distributed computing, not the machine learning itself.