[R] EMEA19 - Assets (new)

Implementing AI: From Exploration to Execution

Amazon Web Services Resources EMEA

Issue link: https://emea-resources.awscloud.com/i/1124971

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Lor alicimi nven- tecese nulparu ntiaspi duciam fugiaepudam re omnisqu aturiti simusant ullab idist, tempost utectem ea des eritatis rerferum aceria non porrunt, conet evellaute et omnit, simenda nissimus dolentur? Quibust, utem. Qui audipsam, vellam, ut eicimus sol- orum qui aut as accabor ectibus ius esti at eos eos eiusand itat- ur aniscil ibusdae reheni cum dolest, aliciis min et periatur? Pedigenia nos ad que seque volenim aut moluptas sam sedios millest eturiorae ventiis qui quae dent eum exces doloria sse- quis aliqui voleconsequiata volum quiaeru ntiisci to et eossum omnist laboreh C U S T O M R E S E A R C H R E P O R T 15 Putting Machine Learning in the Hands of Every Developer S P O N S O R ' S V I E W P O I N T Artifi cial intelligence is driving innovation and enabling business benefi ts across industries. In fact, IDC estimates that 40% of digital transformation initiatives will be supported by AI this year. For early adopters, AI has had a profound impact on how they transform their business for higher-value gains such as competitive advantage and faster innovation by improving their ability to make better decisions and open up new opportunities. Despite their enthusiasm for AI adoption, many decision makers don't know where to start. Should they begin with pilot projects or transformational initiatives? How do they select the use cases that are aligned to their business goals? What technology should they use to build AI applications? Last, are there industry best practices and sources of inspiration and education as they contemplate their AI journey? At Amazon, we've been investing heavily in AI for more than 20 years. Machine learning is used in virtually every aspect of our business — from Amazon.com's recommendations engine and path optimization in our fulfi llment centers to Echo powered by Alexa, our Prime Air drone initiative, and our new retail experience, Amazon Go. At AWS, our mission is to put machine learning in the hands of every developer so that everyone can benefi t from this powerful technology. We deliver this through a portfolio of AI/ML services that meets the needs of all developers. For expert practitioners, AWS takes an open and fl exible approach to all major machine learning and deep learning tools and frameworks, and provides the highest performing environment for running TensorFlow. For ML developers and data scientists, Amazon SageMaker offers an end-to-end solution to build, train, and deploy machine learning applications substantially faster than traditional methods. Finally, for application developers, AWS provides a broad set of AI/ML services to accomplish a wide variety of use cases across image and video analysis, speech, language analysis, document analysis, forecasting, personalization and recommendations, and chatbots. The AWS customers featured in this report — Liberty Mutual, Samsung SDS, and Zalando — are great examples of how businesses are leveraging AWS services to put AI to use in their organizations. AWS also offers unique learning tools to help customers get started quickly with AI: AWS DeepRacer, a fully autonomous 1 / 18-scale race car designed to help you learn about machine learning in a fun way; AWS DeepLens, the world's fi rst deep learning-enabled video camera for developers; Amazon ML Solutions Lab, which combines hands-on educational workshops with advisory professional services; and AWS Machine Learning Training and Certifi cation, which offers structured courses for machine learning based on the same material Amazon uses to train its developers. Learn more about machine learning on AWS. CUSTOM REP ORT — IMPLEMENTING AI: FROM EXPLORATION TO EXECUTION About Amazon Web Services AWS offers a broad and deep set of machine learn- ing and AI services for your business. On behalf of our customers, we are focused on solving some of the toughest challenges that hold back machine learning from being in the hands of every developer. You can choose from pretrained AI services for computer vision, language, recom- mendations, and forecast- ing, or Amazon SageMaker to quickly build, train, and deploy machine learning models at scale. Custom- ers can also build custom models with support for all the popular open- source frameworks. Our capabilities are built on the most comprehensive cloud platform, optimized for machine learning with high-performance com- pute and no compromises on security and analytics. Learn more at aws.ai. MIT SMR CONNECTIONS

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