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A grid shows images from the top Amazon Science articles of 2021, the year 2021 can be seen in an overlay
These are images from some of the most engaging stories published on Amazon Science in 2021.

The top Amazon Science articles of 2021

From quantum chess to robot arms to body fat percentage and ML-powered grocery shopping, these 10 articles resonated with readers in 2021.

By Staff writer
December 28, 2021
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  1. An Amazon quantum computing scientist wins the first-ever quantum chess tournament
    A picture of Aleksander Kubica
    Aleksander Kubica, research scientist with the AWS quantum computing team
    Credit: Perimeter Institute for Theoretical Physics

    Not only did Aleksander Kubica, a research scientist with the AWS quantum computing team, win the first-ever tournament, he did so having played quantum chess only once — the weekend before the event. Learn about his strategy and watch video from two of his historic matches.

  2. A conversation with Michael I. Jordan, Michael Kearns, and Bernhard Schölkopf
    Larry Hardesty, the Amazon Science blog editor, interviewed Amazon distinguished scientist Bernhard Schölkopf (top right) and Amazon Scholars Michael Kearns (bottom left) and Michael I. Jordan (bottom right).
    Larry Hardesty, the Amazon Science blog editor, interviewed Amazon distinguished scientist Bernhard Schölkopf (top right) and Amazon Scholars Michael Kearns (bottom left) and Michael I. Jordan (bottom right).

    On the cusp of the 2021 NeurIPS conference, the three Amazon-affiliated researchers — all of whom have given the conference’s major named lecture, the Posner lecture — talked about the accelerating interesting in machine learning, its implications for both tech and AI research, and the path forward for AI.

  3. Graceful AI
    Stefano 2.jpg
    Stefano Soatto, vice president of applied science for AWS AI.
    Credit: Todd Cheney

    Stefano Soatto, vice president of applied science for AWS AI, writes, "As machine-learning-based decision systems improve rapidly, we are discovering that it is no longer enough for them to perform well on their own. They should also behave nicely toward their predecessors. When we replace an old trained classifier with a new one, we should expect a smooth transition and a peaceful transfer of decision powers."

  4. A look at the science that powers Amazon's advanced robot arms
    A close up of the Robin robotic arm
    Robin must calculate how to identify, move, and sort parcels that may rest atop one another as they are presented via a conveyor.
    Credit F4D Studio

    Robin, one of the most complex stationary robot arm systems Amazon has ever built, brings many core technologies to new levels and acts as a glimpse into the possibilities of combining vision, package manipulation and machine learning. Learn what separates them from more traditional robot arms — and watch them in action.

  5. Why now is a 'particularly good time' to explore careers in robotics
    A split screen screengrab from a video interview shows Siddhartha Srinivasa, left, director of Amazon Robotics AI, and Nia Jetter, Amazon Robotics AI senior principal technologist, right
    Siddhartha Srinivasa, left, director of Amazon Robotics AI, and Nia Jetter, Amazon Robotics AI senior principal technologist

    In a video interview, Siddhartha Srinivasa, director of Amazon Robotics AI, and Nia Jetter, Amazon Robotics AI senior principal technologist, discuss inspiration, their roles at Amazon, and tips for pursuing a robotics career. Watch their informative and illuminating discussion about careers in robotics.

  6. A computer vision system that can accurately predict body fat percentage
    Halo App Body Feature2.png
    With Amazon Halo's Body feature, individuals can measure their own body fat percentage and track it through a personalized 3D model.

    A team of Amazon scientists discusses the challenges in developing a system that can accurately estimate body fat percentage and create personalized 3D avatars of users from smartphone photos. Learn how they utilized convolutional neural networks, and semi-supervised learning.

  7. ARA recipient aims to unite the deep learning community
    Michael Bronstein, the chair in Machine Learning and Pattern Recognition in the Department of Computing at Imperial College London
    Michael Bronstein, an Amazon Research Awards (ARA) recipient, is also the chair in Machine Learning and Pattern Recognition in the Department of Computing at Imperial College London
    Dino Dimopoulos

    Michael Bronstein, the chair in Machine Learning and Pattern Recognition in the Department of Computing at Imperial College London, is using pioneering machine learning to push the boundaries of drug design, among other things — including unifing the machine learning “zoo”.

  8. The science of operations planning under uncertainty
    An Amazon employee is seen making a delivery while an electric delivery van is parked behind him on a residential street in Los Angeles
    An Amazon employee is seen making a delivery while an electric delivery van is parked behind him on a residential street in Los Angeles
    About Amazon

    When Amazon announced it would purchase 100,000 custom electric delivery vehicles as part of The Climate Pledge, a team of scientists within the Amazon Logistics (AMZL) Research organization took on the challenge of determining the best strategy for deploying them. Based on sophisticated models that simulate Amazon’s shipments and external parameters like power availability in each city, the team is developing a plan to gradually electrify Amazon’s entire fleet.

  9. How machine learning is helping Amazon improve the grocery shopping experience
    Amazon Fresh Prime bag
    From forecasting to selection, Amazon Fresh scientists are developing machine learning models that seek to enhance the grocery shopping experience.

    From forecasting to selection, Amazon Fresh scientists are working through (often open) research challenges to develop machine learning models that seek to enhance the grocery shopping experience. Learn how Amazon Fresh is leveraging scientific innovation to meet increased consumer demand.

  10. Creating sustainable, data-driven buildings
    Sense, Act, and Scale 2
    The path to improving building energy efficiency can be paved with the framework of sense, act, and scale say Bharathan Balaji and Rob Aldrich

    Bharathan Balaji , an Amazon senior research scientist, and Rob Aldrich, senior sustainability strategist, write about what must happen to meet the United Nations Global Status Report goal of making buildings at least 30% more energy efficient in order to achieve Paris Agreement goals.

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US, WA, Seattle
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Applied Scientist, Amazon Ads Identity
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Are you interested in working with the core Amazon Advertising teams and leading ad tech partners to spearhead innovation and deliver Identity solutions for our customers? Do you want to have direct and immediate impact on millions of customers every day? We are building the next generation of Identity products and services that will fuel the growth of Amazon’s advertising business. We are looking for self-driven and talented engineers to revel in designing, developing and operating extremely high volume (internet-scale), low latency systems that drive revenue to Amazon. This role will involve designing and developing software system that enable many use cases for WW Advertising. The individual in this role will have the responsibility help define requirements, create software design, implement code to these specifications, provide thorough unit and integration testing, and support products deployed in production and used by our stakeholders and customers. We’re looking for experienced, motivated software engineers with a proven track record of building low-latency / high volume ad serving systems and services. Bonus if you are also comfortable handling big data queries and analytics - that is an integral part of what we do. We use Java and AWS technologies heavily. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE Key job responsibilities As an Applied Scientist on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship. A day in the life You will work collaboratively both within and outside of the Advertising team. As a Software Engineer, you would spend most of your time architecting, designing and coding and the rest in collaboration and discussion. Since we are now working remotely, we also like to have fun by taking time to celebrate each other and to spend time with happy hours. About the team Joining this team, you’ll experience the benefits of working in a dynamic, fast-paced environment, while leveraging the resources of Amazon.com (AMZN), one of the world's leading Internet companies. We provide a highly customer-centric, team-oriented environment. AdTech Identity Program (AIP) team is spearheading innovation for the existential challenge in AdTech today: The need for reliably establishing customer identity in a IDless world without 3P cookies or Device identifiers.
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