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Dec 20, 2023 | 
amazon.science | Larry Hardesty |Changyou Chen |Raffay Hamid
Last month, at its annual re:Invent developers’ conference, Amazon Web Services (AWS) announced the release of two new additions to its Titan family of foundation models, both of which translate between text and images. With Amazon Titan Multimodal Embeddings, now available through Amazon Bedrock, customers can upload their own sets of images and then search them using text, related images, or both.
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Oct 6, 2023 | 
amazon.science | Gunnar Sigurdsson |Raffay Hamid |Changyou Chen
Remote-object grounding is the task of automatically determining where in the local environment to find an object specified in natural language.
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Oct 4, 2023 | 
amazon.science | Changyou Chen |Raffay Hamid |Yi Xie
Many recent advances in artificial intelligence are the result of representation learning: a machine learning model learns to represent data items as vectors in a multidimensional space, where geometric relationships between vectors correspond to semantic relationships between items.
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Aug 22, 2023 | 
amazon.science | Austin Xu |Arjun Seshadri |Raghudeep Gadde |Raffay Hamid
Machine learning (ML) models thrive on data, but gathering and labeling training data can be a resource-intensive process. A common way to address this challenge is with synthetic data, but even synthetic data usually requires laborious hand annotation by human analysts. At this year’s Computer Vision and Pattern Recognition conference (CVPR), we presented a method called HandsOff that eliminates the need to hand-annotate synthetic image data.
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Jun 30, 2023 | 
amazon.science | Aviv A. Rosenberg |Dmitry Sotnikov |Raffay Hamid |Tal Lancewick
Policy Optimization (PO) is one of the most popular methods in Reinforcement Learning (RL). Thus, theoretical guarantees for PO algorithms have become especially important to the RL community. In this paper, we study PO in adversarial MDPs with a challenge that arises in almost every real-world application – delayed bandit feedback. We give the first near-optimal regret bounds for PO in tabular MDPs, and may even surpass state-of-the-art (which uses less efficient methods).
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Jun 30, 2023 | 
amazon.science | Nikolaos Aletras |Arpit Mittal |Raffay Hamid
The AWS AI Labs team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists have developed the algorithms and models that power AWS computer vision services such as Amazon Rekognition and Amazon Textract. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops.
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Jun 30, 2023 | 
amazon.science | Raffay Hamid |Noam Touitou |Nissim Halabi
A locality-sensitive hash (or LSH) is a function that can efficiently map dataset points into a latent space while preserving pairwise distances. Such LSH functions have been used in approximate nearest-neighbor search (ANNS) in the following classic way, which we call classic hash clustering (CHC): first, the dataset points are hashed into a low-dimensional binary space using the LSH function; then, the points are clustered by these hash values.
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Jun 28, 2023 | 
amazon.science | Raffay Hamid |Suren Kumar
At this year’s Conference on Computer Vision and Pattern Recognition (CVPR), Prime Video presented four papers that indicate the broad range of cutting-edge problems we work on. In one paper, “Movies2Scenes: Using movie metadata to learn scene representation", we present a novel contrastive-learning approach that uses only commonly available movie metadata to learn a general-purpose scene representation.
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Jun 28, 2023 | 
amazon.science | Priyanka Sen |Emine Zeynep Yilmaz |Raffay Hamid
Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer’s doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! Amazon Transportation Services is seeking Applied (or Research) Scientists.
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Apr 14, 2023 | 
amazon.science | Xiaohan Nie |Shixing Chen |Raffay Hamid |Shima Nassiri
We propose a novel framework to register sports-fields as they appear in broadcast sports videos. Unlike previous approaches, we particularly address the challenge of field registration when: (a) there are not enough distinguishable features on the field, and (b) no prior knowledge is available about the camera.
