© 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Yoshitaka Haribara Associate Solutions Architect Amazon Web Services Japan K.K. Overview and AWS customer stories of AI/ML startups in Japan Talk & Share: AI/ML Startups Stories @_hariby Apr. 12, 2019 CoderSchool, Ho Chi Minh City, Vietnam

© 2019, Amazon Web Services, Inc. or its Affiliates. About me - Yoshitaka Haribara - @_hariby - GitHub: hariby - Associate Solutions Architect @ AWS - Mostly work with Startup x AI/ML customers - Favorite AWS Service: Amazon SageMaker - Background - Ph.D. (Mathematical Informatics) - Keywords: Neural Networks, Graph Cut, Optical Computing

© 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Our mission at AWS Put machine learning in the hands of every developer

© 2019, Amazon Web Services, Inc. or its Affiliates. Table of contents • Startup space in AWS Japan • AWS customer stories for AI/ML startups • How to start your own AI/ML project?

© 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Startup space in AWS Japan

© 2019, Amazon Web Services, Inc. or its Affiliates. The place you shape your challenge

© 2019, Amazon Web Services, Inc. or its Affiliates. ML@Loft: an event for machine learning developers at AWS Loft

© 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. AWS customer stories for AI/ML startups

© 2019, Amazon Web Services, Inc. or its Affiliates. • Dely is running Japan's best cooking video service, Kurashiru. It strives every day to make culinary services that impact the world. Kurashiru helps many people per day, where it introduces a variety of tasty food recipes that color the dining table with cooking videos. Tens of millions of people watch and listen to the monthly recipe service in Japan. “We exceeded 15 million downloads of our mobile app, in 2.5 years since we launched the popular Kurashiru service. We believe it is critical to deliver the right content to our users at the right time using advanced technologies such as machine learning. To achieve this, we used Amazon SageMaker that helped us build and deploy the machine learning models in production in 90 days. We also improved the Click-Through Rate by 15% with content personalization”. - Masato Otake, CTO, Dely, Inc.

© 2019, Amazon Web Services, Inc. or its Affiliates. SmartNews • SmartNews is the largest news app in Japan delivering quality information to more than 11 million monthly active users in the world. With machine learning technologies, SmartNews helps users with the most relevant and interesting news stories. The machine learning algorithms at SmartNews evaluate millions of articles, social signals, and human interactions to deliver the top 0.01% of stories, that matter most, right now. "Our mission to discover and deliver quality stories to the world is powered by AWS and particularly Amazon SageMaker, which has helped us accelerate the development cycle to serve our customers. Using Amazon SageMaker has helped us immensely in our news curation methods including article classification using deep learning, predicting Life Time Value, and composite modeling for text and image. We look forward to achieving greater heights with Amazon SageMaker and other AI solutions from AWS.” - Kaisei Hamamoto, Co-Founder and Co-CEO, SmartNews, Inc.

© 2019, Amazon Web Services, Inc. or its Affiliates. • SIGNATE offers solutions for outsourcing, hiring, and consulting services, using AI. SIGNATE is also known as a data science community with more than 16,000 members where they compete each other to produce best models in the competitions. The company also offers a service using Amazon SageMaker that helps its clients deploy the models obtained through competitions into production applications. “We are leveraging Amazon SageMaker as our principal tool to build our machine learning models and this has made our model management system called “Aldebaran” more scalable. SageMaker has enabled seamless integration into our workflows including building, training, and deploying ML models simultaneously. Previously, it used to take us 3 to 6 months to deploy models into production. With SageMaker, we can deploy a model into production in 1 to 4 weeks, saving time and increasing productivity. SageMaker is our standard ML platform of choice for all our ML models”. - Shigeru Saito, President, CEO/CDO, SIGNATE Inc.

© 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. How to start your own project?

© 2019, Amazon Web Services, Inc. or its Affiliates. AWS DeepLens (available in U.S.) or Raspberry Pi 16 AWS IoT Greengrass Lambda function Machine Learning Model Video streaming

© 2019, Amazon Web Services, Inc. or its Affiliates. At first, we start with PR/FAQ • PR/FAQ • Press Release + Frequently Asked Questions • Define the value of your service • Example. (PR/FAQ for Amazon GuardDuty) • Title of the release • Date • Narratives

© 2019, Amazon Web Services, Inc. or its Affiliates. Simple Location Finder (Architecture) SAs DeviceService bucket with objects Lambda function Amazon Rekognition RecognitionService Amazon API Gateway DataService Frontend Amazon DynamoDB Office/17F/West Amazon DynamoDB Data lake Web Hosting Vue.js Amazon Cognito SAs Office/17F/North SAs Office/17F/East

© 2019, Amazon Web Services, Inc. or its Affiliates. Display AWS Cloud Face rekognition reception (Architecture) Edge Device NG OK Staff User Name image result Lambda function Amazon DynamoDB Amazon Rekognition Amazon CloudWatch AWS CloudTrail Picture + Name S3 Bucket S3 Bucket API log Archive AWS Cloud USB Camera Temporary security credential FaceID

© 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Thank You! Time for Q&A and discussions.