Customer-obsessed science
-
September 30, 2024From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money.
-
September 19, 2024“Agentic workflows” that use multiple, fine-tuned smaller LLMs — rather than one large one — can improve efficiency.
-
September 16, 2024A position paper presented at ACL proposes a framework for more-accurate human evaluation of LLMs.
-
-
September 29 - October 4, 2024
-
October 21 - 25, 2024
-
September 25, 2024
Now open until November 6, Amazon Research Awards will be seeking proposals in the following research areas: AI for Information Security, Automated Reasoning, AWS AI, AWS Cryptography, and Sustainability.
-
NeurIPS 2022 Workshop on Interactive Learning for NLP2023While online shopping, customers often see a product that they have a preference for, but do not purchase it due to not liking a few aspects of the product (e.g., sleeve type or stripe colors on a shirt), and thus have to continue their search. Instead, if the customer were to select a preferred product and issue a modification query, and the system could find a similar product with the desired modification
-
EMNLP 20232023In the burgeoning field of natural-language processing, Neural Topic Models (NTMs) and Large Language Models (LLMs) have emerged as areas of significant research interest. Despite this, NTMs have predominantly leveraged contextual embeddings from LLMs, neglecting the potential benefits of harnessing the overall structure. Our study addresses this gap by introducing a novel framework named Diffusion-Enhanced
-
EMNLP 20232023Continual Federated Learning (CFL) combines Federated Learning (FL), the decentralized learning of a central model on a number of client devices that may not communicate their data, and Continual Learning (CL), the learning of a model from a continual stream of data without keeping the entire history. In CL, the main challenge is forgetting what was learned from past data. While replay-based algorithms
-
ACM 2023 Symposium on Operating Systems Principles (SOSP)2023Large deep learning models have recently garnered substantial attention from both academia and industry. Nonetheless, frequent failures are observed during large model training due to large-scale resources involved and extended training time. Existing solutions have significant failure recovery costs due to the severe restriction imposed by the bandwidth of remote storage in which they store checkpoints
-
EMNLP 20232023Large language models (LLMs) encode vast amounts of world knowledge. However, since these models are trained on large swaths of internet data, they are at risk of inordinately capturing information about dominant groups. This imbalance can propagate into generated language. In this work, we study and operationalise a form of geographical erasure, wherein language models underpredict certain countries. We
Resources
-
We look for talent from around the world for applied scientists, data scientists, economists, research scientists, scholars, academics, PhDs, and interns.
-
We collaborate with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly.
-
Learn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.