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Anaconda’s State of Data Science Report Report Reveals Surge in AI Upskilling Among Data and IT Professionals - insideBIGDATA

Anaconda Inc., provider of the popular platform for data science and modern AI development, released its sixth annual State of Data Science report, surfacing insights into today’s vibrant data science community and the growth and usage of AI and open-source software.

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Abhishek Persad - Amazon Science

Manager, Applied Science

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Sahil Verma - Amazon Science

Applied Scientist

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P Aditya Sreekar - Amazon Science

Applied Scientist

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Unveiling the power of self-attention for shipping cost prediction: The rate card transformer - Amazon Science

Amazon ships billions of packages to its customers annually within the United States. Shipping cost of these packages are used on the day of shipping (day 0) to estimate profitability of sales. Downstream systems utilize these days 0 profitability estimates to make financial decisions, such as…

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Kostas Bekris - Amazon Science

Amazon Scholar

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Charles Swan - Amazon Science

Sr. Mgr, Software Development

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Nicolas Hudson - Amazon Science

Principal, Applied Scientist

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Azarakhsh Keipour - Amazon Science

Applied Scientist

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Shuai Li - Amazon Science

Applied Scientist

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Pick planning strategies for large-scale package manipulation - Amazon Science

Automating warehouse operations can reduce logistics overhead costs, ultimately driving down the final price for consumers, increasing the speed of delivery, and enhancing the resiliency to market fluctuations. This extended abstract showcases a large-scale package manipulation from unstructured…

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“Above the Trend Line” – Your Industry Rumor Central for 9/29/2023 - insideBIGDATA

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

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Yizhou Sun - Amazon Science

Amazon Scholar

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Xian Li - Amazon Science

Principal, Applied Scientist

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Yan Liang - Amazon Science

Applied Scientist

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Jingbo Shang - Amazon Science

Amazon Visiting Academic

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Chenwei Zhang - Amazon Science

Applied Scientist

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Daheng Wang - Amazon Science

Applied Scientist

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Concept2Box: Joint geometric embeddings for learning two-view knowledge graphs - Amazon Science

Knowledge graph embeddings (KGE) have been extensively studied to embed large-scale relational data for many real-world applications. Existing methods have long ignored the fact many KGs contain two fundamentally different views: high-level ontology-view concepts and fine-grained instance-view…

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Yogesh Virkar - Amazon Science

Applied Scientist

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Improving isochronous machine translation with target factors and auxiliary counters - Amazon Science

To translate speech for automatic dubbing, machine translation needs to be isochronous, i.e. translated speech needs to be aligned with the source in terms of speech durations. We introduce target factors in a transformer model to predict durations jointly with target language phoneme sequences. We…

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DistTGL: Distributed memory-based temporal graph neural network training - Amazon Science

Memory-based Temporal Graph Neural Networks are powerful tools in dynamic graph representation learning and have demonstrated superior performance in many real-world applications. However, their node memory favors smaller batch sizes to capture more dependencies in graph events and needs to be…

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Ke Fan - Amazon Science

Applied Scientist

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Rethinking amodal video segmentation from learning supervised signals with object-centric representation - Amazon Science

Video amodal segmentation is a particularly challenging task in computer vision, which requires to deduce the full shape of an object from the visible parts of it. Recently, some studies have achieved promising performance by using motion flow to integrate information across frames under a…

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Coarse-to-fine amodal segmentation with shape prior - Amazon Science

Amodal object segmentation is a challenging task that involves segmenting both visible and occluded parts of an object. In this paper, we propose a novel approach, called Coarse-to-Fine Segmentation (C2F-Seg), that addresses this problem by progressively modeling the amodal segmentation. C2F-Seg…

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