Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...

Image Editing is worth a single LoRA! We present In-Context Edit, a novel approach that achieves state-of-the-art instruction-based editing using just 0.5% of the training data and 1% of the ...

Where, exactly, could quantum hardware reduce end-to-end training cost rather than merely improve asymptotic complexity on a whiteboard?

While Google disagrees, the company may have decided again that your data is its toy. Here's how to try to stop Gmail from training its AI on your email. There's no shortage of big tech companies that ...

In this advanced DeepSpeed tutorial, we provide a hands-on walkthrough of cutting-edge optimization techniques for training large language models efficiently. By combining ZeRO optimization, ...

Both GPUs and TPUs play crucial roles in accelerating the training of large transformer models, but their core architectures, performance profiles, and ecosystem compatibility lead to significant ...

Abstract: Transformer models have achieved state-of-the-art performance across a wide range of machine learning tasks. There is growing interest in training transformers on resource-constrained edge ...

State-of-the-art pretrained models for inference and training Transformers is a library of pretrained text, computer vision, audio, video, and multimodal models for inference and training. Use ...