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.
Top eight university teams move on to head-to-head finals focused on AI security for code generation.
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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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2025Accurately classifying the relevance of Query-Product pairs is critical in online retail stores such as Amazon, as displaying irrelevant products can harm user experience and reduce engagement. While Large Language Models (LLMs) excel at this task due to their broad knowledge and strong reasoning abilities. However, their high computational demands constrain their practical deployment in real-world applications
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QIP 20252025A central challenge in quantum simulation is to prepare low-energy states of strongly interacting many-body systems. In this work, we study the problem of preparing a quantum state that optimizes a random all-to-all, sparse or dense, spin or fermionic k-local Hamiltonian. We prove that a simplified quantum Gibbs sampling algorithm achieves a Ω(1 k)-fraction approximation of the optimum, giving an exponential
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2025Given a small number of images of a subject, personalized image generation techniques can fine-tune large pre-trained text-to-image diffusion models to generate images of the subject in novel contexts, conditioned on text prompts. In doing so, a trade-off is made between prompt fidelity, subject fidelity and diversity. As the pre-trained model is fine-tuned, earlier checkpoints synthesize images with low
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2025Large-scale vision-language pre-trained (VLP) models (e.g., CLIP [46]) are renowned for their versatility, as they can be applied to diverse applications in a zero-shot setup. However, when these models are used in specific domains, their performance often falls short due to domain gaps or the under-representation of these domains in the training data. While fine-tuning VLP models on custom datasets with
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ICSPCN 20252025This paper introduces a new tri-lateration method that utilizes a unique cost function formulation to significantly enhance the performance of positioning systems. Fixed-position devices called locators or anchors, with predetermined coordinates, are used to determine and track the unknown location of a moving electronic tag. The optimization algorithm enhances accuracy by assigning greater importance to
Academia
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
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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.
