CybAI news

In today's rapidly evolving digital landscape, artificial intelligence (AI) stands as a transformative force with the potential to revolutionize industries, spur innovation, and drive economic growth. However, unlocking the full potential of AI requires overcoming significant computational challenges. This is where AI accelerators come into play. AI accelerators, specialized hardware designed to optimize AI workloads, play a crucial role in accelerating AI adoption, powering economic growth, and fostering social development.Acceleration of AI adoptionAI accelerators serve as catalysts for the widespread adoption of AI technologies across various sectors. By enhancing the speed and efficiency of AI computations, these specialized hardware solutions…

Low-rank adaptation (LoRA) is a machine learning technique that modifies a pretrained model (for example, an LLM or vision transformer) to better suit a specific, often smaller, dataset by adjusting only a small, low-rank subset of the model's parameters. This approach is important because it allows for efficient finetuning of large models on task-specific data, significantly reducing the computational cost and time required for finetuning.Last week, researchers proposed DoRA: Weight-Decomposed Low-Rank Adaptation, a new alternative to LoRA, which may outperform LoRA by a large margin.To understand how these methods work, we will implement both LoRA and DoRA in PyTorch from scratch…