June 2025

Using generative AI to do multimodal information retrieval With large datasets, directly generating data ID codes from query embeddings is much more efficient than performing pairwise comparisons between queries and candidate responses. Search and information retrieval Sungyeon Kim Xiaofan Lin June 25, 09:00 AM December 23, 03:48 PM For most of the past 10 years, machine learning (ML) relied heavily on the concept of embedding: an ML model would learn to convert input data into vectors (embeddings) such […]

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KV caches are one of the most critical techniques for efficient inference in LLMs in production. KV caches are an important component for compute-efficient LLM inference in production. This article explains how they work conceptually and in code with a from-scratch, human-readable implementation. It’s been a while since I shared a technical tutorial explaining fundamental LLM concepts. As I am currently recovering from an injury and working on a bigger LLM research-focused article, I thought I’d share a […]

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Scaling up image segmentation across data and tasks Novel architecture that fuses learnable queries and conditional queries improves a segmentation models ability to transfer across tasks. Computer vision Pei Wang Stefano Soatto June 12, 12:25 PM June 12, 12:25 PM The first draft of this blog post was generated by Amazon Nova Pro, based on detailed instructions from Amazon Science editors and multiple examples of prior posts. In a paper we’re presenting at the 2025 Conference on Computer […]

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Mixture-of-Experts (MoEs) architectures offer a promising solution by sparsely activating specific parts of the model, reducing the inference overhead. However, even with MoEs, the sheer number of parameters and experts makes deployment and serving costly. Pruning is an established method to reduce the number of parameters of a trained model while maintaining its task performance. Typically, we distinguish two kinds of approaches. Unstructured pruning removes individual weights, while structured pruning removes entire model components. Due to their clear […]

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75 Amazon Research Award recipients announced Awardees, who represent 46 universities in 10 countries, have access to Amazon public datasets, along with AWS AI/ML services and tools. Amazon Research Awards team June 03, 01:06 PM November 04, 03:38 PM Amazon Research Awards (ARA) provides unrestricted funds and AWS Promotional Credits to academic researchers investigating various research topics in multiple disciplines. This cycle, ARA received many excellent research proposals from across the world and today is publicly announcing 75 […]

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MemSAM MemSAM is a new video segmentation model designed for echocardiography, built on top of the SAM architecture. It is designed to address specific issues related to the application of SAM to echocardiography and video segmentation more broadly, versus image segmentation. A space-time memory module allows the model to prompt itself for all but the first frame in a video sequence, and its training framework allows it to be trained with fewer annotations in a semi-supervised manner. Using […]

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