Reasoning models can generate seven to 10 times as many tokens as necessary on simple tasks, creating unsustainable costs at scale. Amazon's vision for metacognitive AI could fundamentally shift how models allocate computational resources.
Amazon's competitive-agent architecture creates a continuous improvement cycle that develops security protections at machine speed, reducing what typically takes weeks down to hours.
A new approach to reducing carbon emissions reveals previously hidden emission “hotspots” within value chains, helping organizations make more detailed and dynamic decisions about their future carbon footprints.
How agentic systems work under the hood — and how AWS’s new AgentCore framework implements their essential components.
Customer-obsessed science
Research areas
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November 28, 20254 min readLarge language models are increasing the accuracy, reliability, and consistency of the product catalogue at scale. -
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Featured news
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
The collaboration will advance research in generative AI, robotics, natural language processing and cloud computing while fostering innovation in foundational and emerging technologies.
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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KDD 2022 Workshop on AI-enabled Cybersecurity Analytics and Deployable Defense , 2022 Conference on Applied Machine Learning for Information Security2022Data labels in the security field are frequently noisy, limited, or biased towards a subset of the population. As a result, commonplace evaluation methods such as accuracy, precision and recall metrics, or analysis of performance curves computed from labeled datasets do not provide sufficient confidence in the real-world performance of the model. In the industry today, we rely on domain expertise and lengthy
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ECCV 20222022Graph-based approaches have been becoming increasingly popular in road network extraction, in addition to segmentation-based methods. Road networks are represented as graph structures, being able to explicitly define the topology structures and avoid the ambiguity of segmentation masks, such as between a real junction area and multiple separate roads in different heights. In contrast to the bottom-up graph-based
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ACMMM 20222022Actor identification and localization in movies and TV series seasons can enable deeper engagement with the content. Manual actor identification and tagging at every time-instance in a video is error prone as it is a highly repetitive, decision intensive and time-consuming task. The goal of this paper is to accurately label as many faces as possible in the video with actor names. We solve this problem using
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AAAI 2022 Workshop on Dialog System Technology Challenge2022A lot of recent work in dialogue modeling has been on written conversations, partly because of available data sets. However, written dialogues are not sufficient to fully capture the nature of spoken conversations as well as the potential effect of speech recognition errors on practical spoken dialogue systems. This challenge track aims to provide a new benchmark on spoken task-oriented conversations. We
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IJCAI 2022 AI Safety Workshop2022Contextual bandits are widely used across the industry in many applications such as search engines, dialogue systems, recommendation systems, etc. In such applications, it is often necessary to update the policy regularly as the data distribution changes and new features are being on-boarded frequently. As any new policy deployment directly impacts the user experience, safety in model updates is an important
Collaborations
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.
