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
-
November 28, 20254 min readLarge language models are increasing the accuracy, reliability, and consistency of the product catalogue at scale. -
November 20, 20254 min read -
October 20, 20254 min read
-
October 14, 20257 min read
-
October 2, 20253 min read
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
David Chang/Getty Images/iStockphoto
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.
-
KDD 20222022Revenue forecasting for large business organizations is a challenging but important problem. As a multinational business organization, Bosch has an estimated 2,000,000+ time series capturing monthly financial key figures at multiple organizational and product hierarchies, which are forecasted every month into the future 12 month horizon to inform financial and resource planning. To address this challenge
-
arXiv2022In this work, we demonstrate that multilingual large-scale sequence-to-sequence (seq2seq) models, pre-trained on a mixture of denoising and Causal Language Modeling (CLM) tasks, are more efficient few-shot learners than decoder-only models on various tasks. In particular, we train a 20 billion parameter multilingual seq2seq model called Alexa Teacher Model (AlexaTM 20B) and show that it achieves state-of-the-art
-
RecSys 20222022Numerous problems of practical significance such as clickthrough rate (CTR) prediction, forecasting, tagging and so on, involve complex interaction of various user, item and context features. Manual feature engineering has been used in the past to model these combinatorial features but it requires domain expertise and becomes prohibitively expensive as the number of features increases. Feedforward neural
-
ECCV 20222022In this paper, we study the challenging instance-wise vision-language tasks, where the free-form language is required to align with the objects instead of the whole image. To address these tasks, we propose X-DETR, whose architecture has three major components: an object detector, a language encoder, and vision-language alignment. The vision and language streams are independent until the end and they are
-
GCPR 20222022Generation of photo-realistic images, semantic editing and representation learning are only a few of many applications of high- resolution generative models. Recent progress in GANs have established them as an excellent choice for such tasks. However, since they do not provide an inference model, downstream tasks such as classification cannot be easily applied on real images using the GAN latent space.
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
View all
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.
