Amazon vice president and distinguished engineer Marc Brooker explains how agentic systems work under the hood — and how AWS’s new AgentCore framework implements their essential components.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
In-context learning enables a model that can solve forecasting tasks with an arbitrary number of dimensions in a zero-shot manner.
New technologies are helping vulnerable communities produce maps that integrate topographical, infrastructural, seasonal, and real-time data — an essential tool for many humanitarian endeavors.
A new dataset with over 238,000 images challenges and advances the state of the art in visual defect detection for complex retail applications.
Customer-obsessed science
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September 26, 2025To transform scientific domains, foundation models will require physical-constraint satisfaction, uncertainty quantification, and specialized forecasting techniques that overcome data scarcity while maintaining scientific rigor. -
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The collaboration will advance research in generative AI, robotics, natural language processing and cloud computing while fostering innovation in foundational and emerging technologies.
Amazon Research Awards have opened their Fall call for proposals, which closes November 5, 2025.
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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Building and maintaining a rich and high-quality product schema helps customers of an e-commerce service find products based on the characteristics they desire. As the quantity of products sold on the service increases, so does the complexity of maintaining the schema. Expanding it requires finding gaps, designing new product attributes, and ensuring that they do not already exist in the schema. In this
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Customer service in e-commerce often relies on human agents to handle inquiries related to orders, returns, and product information. While this approach is effective, it can be expensive and difficult to scale during periods of high demand. Recent advances in intelligent chatbots, particularly those based on Retrieval Augmented Generation (RAG) models, have significantly improved customer service efficiency
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Accurate intent classification is critical for efficient routing in customer service, ensuring customers are connected with the most suitable agents while reducing handling times and operational costs. However, as companies expand their product lines, intent classification faces scalability challenges due to the increasing number of intents and variations in taxonomy across different verticals. In this
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KDD 2025 Workshop on Structured Knowledge for Large Language Models2025Despite advances in large language model (LLM)-based natural language interfaces for databases, scaling to enterprise-level data catalogs remains an under-explored challenge. Prior works addressing this challenge rely on domain-specific fine-tuning—complicating deployment—and fail to leverage important semantic context contained within database metadata. To address these limitations, we introduce a component-based
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Financial accounting systems rely heavily on subledgers to track detailed transaction records. However, modern systems often evolve into complex architectures where different components use inconsistent labeling conventions, making it difficult to understand and utilize important relationships within subledger data. This paper presents a novel framework LLM-STARS (LLM-Enhanced Standardization of Time-series
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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.
