Language models inspired by specialized processing regions in the brain offer significant time and cost savings.
An ensemble of models, weighted according to their reluctance to flag anomalies, outperforms its predecessors.
Unique end-of-arm tools with three-dimensional force sensors and innovative control algorithms enable robotic arms to “pick” items from and “stow” items in fabric storage pods.
In 2017, IEEE Internet Computing identified a single paper from its publication history that had best withstood the test of time: a 2003 paper called “Amazon.com Recommendations: Item-to-Item Collaborative Filtering”
We present Amazon Nova Premier, our most capable multimodal foundation model and teacher for model distillation.
Customer-obsessed science
Research areas
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July 22, 2025Generating diverse synthetic prior distributions leads to a tabular foundation model that outperforms task-specific baselines.
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Created for students keen to build their career in machine learning, the fifth edition of the program is now open for all eligible students from recognized institutes in India.
University teams battle to harden and hack AI coding assistants in head-to-head tournament
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Led by David Luan and Pieter Abbeel, the lab will focus on developing new foundational capabilities for enabling useful AI agents.
The company's new state-of-the-art foundation models deliver frontier intelligence and industry-leading price performance.
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SIGMOD/PODS 20252025Graph neural networks (GNNs) are models specialized for graph data and widely used in applications. To train GNNs on large graphs that exceed CPU memory, several systems have been designed to store data on disk and conduct out-of-core processing. However, these systems suffer from either read amplification when conducting random reads for node features that are smaller than a disk page, or degraded model
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2025Large language models (LLM) have demonstrated the ability to understand human language by leveraging large amount of text data. Automatic speech recognition (ASR) systems are often limited by available transcribed speech data and benefit from a second pass rescoring using LLM. Recently multi-modal large language models, particularly speech and text foundational models have demonstrated strong spoken language
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2025The data on user behaviors is sparse given the vast array of user-item combinations. Attributes related to users (e.g., age), items (e.g., brand), and behaviors (e.g., co-purchase) serve as crucial input sources for item-item transitions of user’s behavior prediction. While recent Transformer-based sequential recommender systems learn the attention matrix for each attribute to update item representations
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2025We propose a low-shot image classification method called LIMO, which can train an accurate image classification model under conditions of acute data scarcity. LIMO uniquely assembles existing knowledge from a set of diverse models and builds a novel mixture of experts architecture for low-shot image classification. LIMO’s architecture introduces minimal number of new model parameters, such that the added
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2025Target Speech Extraction (TSE) traditionally relies on explicit clues about the speaker’s identity like enrollment audio, face images, or videos, which may not always be available. In this paper, we propose a text-guided TSE model StyleTSE that uses natural language descriptions of speaking style in addition to the audio clue to extract the desired speech from a given mixture. Our model integrates a speech
Academia
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Gretchen Ertl
The program offers unrestricted funds and other resources to support research at academic institutions and non-profit organizations in areas that align with our mission.
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and large language model coding security.
Credit: Wolfram Scheible
We partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest.
Courtesy of Pai-Ling Yin
We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
