AWS re:Invent 2018

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AIM404: Build & Deploy ML Models Quickly & Easily with Amazon SageMaker Dec 01, 2018

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Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker takes away the heavy lifting of machine learning, thus removing the typical barriers associated with machine learning. In this session, we'll dive deep into the technical details of each of the modules of Amazon SageMaker to showcase the capabilities of the platform. We also discuss the practical deployments of Amazon SageMaker through real-world customer examples.

AIM405: Better Analytics Through Natural Language Processing Dec 01, 2018

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Natural language processing holds the key to unlocking business value from unstructured data. Organizations that implement effective data analysis methods gain a competitive advantage through improved decision-making, risk reduction, or enhanced customer experience. In this session, learn how to easily process, analyze, and visualize data by pairing Amazon Comprehend with services like Amazon Relational Database Service (Amazon RDS), Amazon Elasticsearch Service, and Amazon Neptune. We also share real-world examples of how customers built text analytics solutions with Amazon Comprehend.

AIM406: Unlock the Potential of Your Media Assets, Fox Entertainment Group Dec 01, 2018

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Machine learning (ML) enables developers to build scalable solutions that maximizes the use of media assets through automatic metadata extraction. From automatic transcription and language translation to face detection and celebrity recognition, ML enables you to automate manual workflows and optimize the use of your video content. In this session, learn how to use services such as Amazon Rekognition, Amazon Translate, and Amazon Comprehend to build a searchable video library, automate the creation of highlight reels, and more. Complete Title: AWS re:Invent 2018: Unlock the Full Potential of Your Media Assets, ft. Fox Entertainment Group (AIM406)

AIM407: Build Learning Applications Using Apache MXNet Dec 01, 2018

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The Apache MXNet deep learning framework is used for developing, training, and deploying diverse AI applications, including computer vision, speech recognition, natural language processing, and more at scale. In this session, learn how to get started with Apache MXNet on the Amazon SageMaker machine learning platform. Chick-fil-A share how they got started with MXNet on Amazon SageMaker to measure waffle fry freshness and how they leverage AWS services to improve the Chick-fil-A guest experience. Complete Title: AWS re:Invent 2018: [REPEAT 1] Build Deep Learning Applications Using Apache MXNet - Featuring Chick-fil-A (AIM407-R1)

AIS301: Delivering on the Promise of AI Together Dec 01, 2018

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Rohit Prasad Amazon AI We are living in a golden age of artificial intelligence (AI). Machines have already surpassed humans in some specific tasks, including image and speech recognition, thanks to the power of cloud computing, the abundance of data required to train AI systems, and improvements in foundational AI algorithms. While some express fear about the potential for AI systems to increasingly overtake the role of humans, together we should influence how these systems can improve every aspect of our lives. Join Rohit Prasad as he explores the opportunities for AI systems to augment human intelligence in ways that will make it accessible to everyone, increasing the societal good today and into the future.

AIS302: The Future of Mixed-Autonomy Traffic Dec 01, 2018

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How will self-driving cars change urban mobility patterns? This talk examines scientific contributions in the field of reinforcement learning, presented in the context of enabling mixed-autonomy mobility-the gradual and complex integration of autonomous vehicles into existing traffic systems. We explore the potential impact of a small fraction of autonomous vehicles on low-level traffic flow dynamics, using novel techniques in model-free deep reinforcement learning. We share examples in the context of a new open-source computational platform and state-of-the-art microsimulation tools with deep-reinforcement libraries.

AIS303: Creating Movie Magic with Computational Simulations Dec 01, 2018

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Rapid improvements in computational simulation have driven advances in many industries that rely on modelling natural phenomena. In particular, visual effects engineers use AI algorithms to create stunning imagery for feature films like Star Wars, Harry Potter, and the Marvel Cinematic Universe. In this talk, Ronald Fedkiw will discuss his research to produce a new wave of simulation technology with more realistic facial animation to remove the 'uncanny valley,' more realistic and predictive cloth simulation, as well as the simulation of botanical trees.

AIS304: Unbiased Learning from Biased User Feedback Dec 01, 2018

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Logged user interactions are one of the most ubiquitous forms of data available because they can be recorded from a variety of systems (e.g., search engines, recommender systems, ad placement) at little cost. Naively using this data, however, is prone to failure. A key problem lies in biases that systems inject into the logs by influencing where we will receive feedback (e.g., more clicks at the top of the search ranking). This talk explores how counterfactual inference techniques can make learning algorithms robust against bias. This makes log data accessible to a broad range of learning algorithms, from ranking SVMs to deep networks.

AIS305: Intelligent Systems for Cancer Genomics Dec 01, 2018

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One of the most exciting frontiers in science is building automated systems that use existing biomedical data to understand and ultimately treat human disease. The key difficulty in the case of cancer is that it is a highly heterogeneous disease, making it challenging to uncover which molecular alterations in tumors are important for the disease and to predict how an individual will respond to treatment. This talk presents an overview of integrative computational methods for analyzing cancer genomes that leverage a diverse range of complementary data in order to extract biomedically relevant insights.

AIS306: Making Aerial Micro-Drones a Reality Dec 01, 2018

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The concept of insect-scale aerial drones has long been in the realm of science fiction rather than reality, especially since powering such small drones is fundamentally difficult. In this talk, Shyam Gollakota will share his work on robofly, the first honeybee-sized wireless drone to successfully lift off. He will also discuss an alternative biology-based solution that integrates sensing, computing, and communication functions onto live-flying bumblebees. Data generated from this mobile IoT platform can feed AI models that have the potential to generate valuable intelligence for applications ranging from precision irrigation to environmental sensing.

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