Advancing the Frontiers of AI
Aurora is a state-of-the-art large language model (LLM) that represents the pinnacle of Nexsys' research and development efforts. With over 1 trillion parameters, Aurora demonstrates unprecedented capabilities in natural language understanding, generation, and multi-modal reasoning.
We've curated a diverse dataset of over 1 petabyte of text, code, and multi-modal data from high-quality sources, ensuring broad knowledge coverage and reducing biases.
Aurora is trained on a custom-built supercomputer cluster with over 10,000 GPUs, utilizing our proprietary distributed training algorithms for efficient scaling.
We've developed a hybrid architecture that combines transformer layers with sparse mixture-of-experts (MoE) layers, allowing for increased model capacity without a proportional increase in computational requirements.
We use LoRA (Low-Rank Adaptation) and prefix-tuning methods to adapt Aurora to specific domains with minimal additional parameters.
Aurora excels at in-context learning, allowing it to perform new tasks with just a few examples.
We've implemented elastic weight consolidation (EWC) and experience replay techniques to allow Aurora to learn new tasks without forgetting previously learned information.
We employ advanced debiasing techniques during training and have developed a comprehensive framework for identifying and mitigating biases in model outputs.
Aurora incorporates multiple layers of content filtering and safety checks to ensure outputs are appropriate and non-harmful.
We're advancing the field of AI interpretability, developing tools to better understand and explain Aurora's decision-making processes.