Training infrastructure, benchmarks, responsible-AI methodology, and more.
David Chang/Getty Images/iStockphoto
The Amazon AGI SF Lab will focus on developing new foundational capabilities for enabling useful AI agents.
In a keynote address at the latest Amazon Machine Learning Conference, Amazon academic research consultant, Stanford professor, and recent Nobel laureate Guido Imbens offered insights on the estimation of causal effects in “panel data” settings.
Customer-obsessed science
Research areas
-
February 20, 2025Using large language models to generate training data and updating models through both fine tuning and reinforcement learning improves the success rate of code generation by 39%. -
-
-
December 24, 2024
Featured news
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.
Caltech professor and Amazon Scholar John Preskill wins Bell Prize for applying both classical and quantum computing to the problem of learning from quantum experiments.
-
As the demand for online A/B testing continues to rises for tech companies, the opportunity cost of conducting these experiments becomes increasingly significant. Consequently, there is a rising need for an efficient continuous monitoring system capable of early terminating experiments when necessary. Existing literature and tools primarily focuses on early terminating experiments with evidently significant
-
2025The instruction hierarchy, which establishes a priority order from system messages to user messages, conversation history, and tool outputs, is essential for ensuring consistent and safe behavior in language models (LMs). Despite its importance, this topic receives limited attention, and there is a lack of comprehensive benchmarks for evaluating models’ ability to follow the instruction hierarchy. We bridge
-
Tabular data is one of the most common data formats found in the web and used in domains like finance, banking, e-commerce and medical. Although deep neural networks (DNNs) have demonstrated outstanding performance on homogeneous data such as visual, audio, and textual data, tree ensemble methods such as Gradient Boosted Decision Trees (GBDTs) are often the go-to choice for supervised machine learning problems
-
2025Retrieval-Augmented Generation (RAG) systems have shown promise in enhancing the performance of Large Language Models (LLMs). However, these systems face challenges in effectively integrating external knowledge with the LLM’s internal knowledge, often leading to issues with misleading or unhelpful information. This work aims to provide a systematic study on knowledge checking in RAG systems. We conduct
-
ECIR 20252025Multi-vector dense retrieval with ColBERT has been shown to be effective in striking a good relevance and efficiency tradeoff for both in-domain and out-of-domain datasets through late interaction between queries and documents. However, the efficiency of ColBERT for a large-scale retrieval dataset is still constrained by its large memory footprint, as one embedding is stored per token; thus, previous work
Academia
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.
JORDAN STEAD/(JORDAN STEAD / Amazon)
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and LLM 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.
