Using the Neuron Kernel Interface, a Reactor–AWS collaboration tackled the dynamic shapes, memory access patterns, and cache management that make real-time autoregressive diffusion hard—building techniques that generalize across models.
Three new papers from Amazon Bio Discovery address bottlenecks in AI-driven antibody engineering, from benchmarking binding predictors to experimentally validating de novo design.
New research indicates that AI agents learn compressible models of data, which don’t have enough space to enable memorization.
How the Verus "program verifier", which automatically checks code against a mathematical specification of its functionality, helps increase security assurance in software projects.
Ten years after we founded the Automated Reasoning Group, mathematical logic has moved from academic research into production services that secure millions of customer workloads — demonstrating that systems can be provably correct, not just probably correct.
Customer-obsessed science
Research areas
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October 12, 202614 min read“Priming” reuses pretrained Transformer weights to build models with more efficient architectures at less than 1% of the original training cost and with throughputs up to twice as high. -
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August 21, 20269 min read
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July 30, 20268 min read
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The collaboration will support research in robotics, industrial and systems engineering, and aerospace technology while fostering innovation in foundational and emerging technologies.
Submissions open October 1 and close on November 4, 2026
The Build on Trainium program is a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
The Antibody Developability Benchmark is powered by one of the most diverse antibody datasets in public literature, enabling transparent performance evaluation for AI-guided antibody design.
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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JCAI 2022 Workshop on Heuristic Search in Industry2022The increasing demand for same-day delivery and the commitment of e-commerce companies to this service raise a number of challenges in logistics. One of these challenges for fulfillment centers is to coordinate hundreds of mobile robots in their automated warehouses efficiently to allow for the retrieval and packing of thousands of ordered items within the promised delivery deadlines. We formulate this
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ACM SIGSPATIAL 20222022Understanding and representing real-world places (physical locations where drivers can deliver packages) is key to successfully and efficiently delivering packages to customer’s doorstep. Prerequisite to this is the task of capturing similarity and relatedness between places. Intuitively, places that belong to a same building should have similar characteristics in geospatial as well as textual space. However
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Transportation Science2022The 2021 Amazon Last Mile Routing Research Challenge, hosted by Amazon.com’s Last Mile Research team, and scientifically supported by the Massachusetts Institute of Technology’s Center for Transportation and Logistics, prompted participants to leverage real operational data to find new and better ways to solve a real-world routing problem. In this article, we describe the data set released for the research
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ColdGuess: A general and effective relational graph convolutional network to tackle cold start casesKDD 2022 Workshop on Mining and Learning with Graphs2022Low-quality listings and bad actor behavior in online retail websites threatens e-commerce business as these result in sub-optimal buying experience and erode customer trust. When a new listing is created, how to tell it has good quality? Is the method effective, fast, and scalable? Previous approaches often face three limitations/challenges: (1) unable to handle cold start problems where new sellers/listings
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RecSys 2022 Workshop on CONSEQUENCES – Causality, Counterfactuals and Sequential Decision-Making2022Adaptive experimental design methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N testing methods. This paper shares lessons learned regarding the challenges and pitfalls of naively using adaptive experimentation systems in industrial settings where non-stationarity is prevalent, while also providing perspectives
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.
