• WHERE
    Virtual

    WHEN
    Thursday to Friday
    Aug 19 to 20, 2021

Schedule

Event Schedule

Over 2 Days, the Rakuten Product Conference (Theme: Applied AI) brings together AI Evangelists, Innovation Heads and leading Data Scientists across domains such as Customer & Product Sciences, Advanced AI Research, Data Science Platforms and Business Analytics.

All timings in IST

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  • Day 1

    August 19,2021

  • In this talk, I will give an overview of AI/data strategy and execution in the Rakuten group. Rakuten is one of the largest internet conglomerates in Japan with more than 70 services and processes transaction data more than 15 trillion JPY or 3% of Japan GDP. With this unprecedented diverse and a large amount of data, Rakuten has the potential to understand customers’ lifestyles and well-being, and we set this as the key mission of AI/data. We also explain our moonshot projects in Rakuten institute of technology such as quantum computations, cure cancer and autonomous network. 
    Keynotes

  • The theoretical, practical, and application foundations of AI and Data Science have matured well now with a wide variety of learning paradigms, well understood data-to-decision process, cloud and edge-enabled infrastructures and platforms for training and inferencing, and applications across a wide variety of domains and data types. While we have mastered the art of building and deploying a “collection of models” well, the complex ecosystems of the future - Telecom, Retail, Manufacturing, Smart Cities, etc. - will require us to think systematically about a whole “Ecosystem of models” – where models are connected to each other.  In this talk, we will explore the eight (Ashtaang = eight parts) different types of AI capabilities needed to complete an end-to-end AI Stack. Components from such an AI stack form the building blocks of an “AI Architecture of the future” for such next generation complex ecosystem products.
    Keynotes

  • Natural Language Processing (NLP), as a field, has made dramatic progress over the last 10 years. In this talk, we will cover the underlying trends in data, compute and algorithms that are driving this progress. Diving into a bit more technical details, we will also look at some of the major deep-learning models that have resulted in fundamental advances in the field. Finally, we will wrap up with some applications of NLP to E-commerce at Rakuten.
    Advances in AI

  • A glimpse of what it takes to enable unparalleled convenience to Swiggy's customers and how AI powers decisions at each stage of the customer journey.
    Data Science Platforms & Analytics

  • Unravel Data is an AI-enabled product to simplify the observability of modern data platforms and is used today by the largest brand names in Fortune 500. This talk covers the hard lessons I learned over the years in developing dozens of Data+AI products from idea to production -- things that can go wrong across ML problem definition, dataset selection, data preparation, model design, training, and operationalization in production. I wrap up the talk with key patterns you can follow to build your AI/ML products successfully. 
    Customer & Product Sciences

  • Computer vision helps automating tasks at scale, by understanding relevant aspects of image or video content. In many cases scaling such tasks would be prohibitive, and they can now be carried at human-level accuracy. Applications include document processing for rapid user onboarding,  product image classification and tagging, image quality control, and banner generation. This talk will provide an overview of vision research projects at the Rakuten Institute of Technology that help enabling frictionless customer experiences.
    Advances in AI

  • Learn how the world's second-largest home improvement retailer helps customers love where they live. This talk will be focused on a couple of case studies where Lowe's has been able to improve customer engagement and, thereby, revenue through the use of ML and personalisation in the context of offline retail. This will also delve into challenges faced and the key learnings.
    Customer & Product Sciences

  • Most modern AI systems are entirely neural. It is believed that for most tasks, end-to-end data-driven learning of neural architectures is sufficient, without any need for additional background knowledge about the domain. In this talk, I discuss the importance of symbolic AI in the modern neural world. With various applications ranging from natural language processing, planning, and computer vision, I will show the value of symbolic features, constraints, and representations inside deep learning systems.
    Advances in AI

  • Explainable AI (XAI) tends to refer to the movement, initiatives, and efforts made in response to AI transparency and trust concerns, more than to a formal technical concept. Interpretable ML is one of the most talked-about topics in the AI domain, to convert the black-box algorithm into easy to comprehend solutions to improve adoption for real-life business problems. Interpretable ML is the degree to which a human can understand the cause of a decision. We plan to talk about some of the cutting edge algorithms in the world of Explainability. Interpretability/ during the conference, explaining the importance of this topic along with real business applications and examples.
    Data Science Platforms & Analytics

  • The recent advances in artificial intelligence are mainly attributed to deep learning models, which are intrinsically data-hungry and compute-hungry. Moreover, such deep learning models also suffer from black-box-ness, vulnerable understanding and reasoning ability, and intrinsic bias. All these factors limit its domain application. Explicit knowledge represented in knowledge graphs has a lot to offer. It could potentially drive the next surge in AI by addressing all of the above concerns. Let us brainstorm "Role of Knowledge Graphs in AI" with the education domain case study researched and developed at Embibe.
    Customer & Product Sciences

  • Visual metadata is a necessity to get videos discovered. The high cost of metadata makes it hard for the torso and tail to have good metadata - leading to a spiralling effect of the poor becoming poorer in the video domain. Our technology creates processes that make it extremely affordable to generate presentable metadata for an entire video library - almost automatically. A bottom-up video reasoning system automatically generates several structural artefacts, including poster art, trailers, cast information, promotions, brands, title credits, moods, and predict genre. All this is fed into a graph database with a global knowledge of TV, and from there on, curated by metadata professionals. We present an AI-assisted, metrics-driven process for creating and maintaining complete metadata and share experiences in taking this to industrial production.
    Advances in AI

  • Routing diagnostics show traffic is the biggest cause of ETA errors. To improve Routing, ETAs, and Navigation, we need to improve our Traffic prediction accuracy. In this session, we will talk about i) how does traffic work? ii) How is traffic used in Routing? iii) why does traffic matter?
    Data Science Platforms & Analytics

  • The ever-evolving economic scenarios, regulatory framework, changing consumer behaviour, data availability are additional factors besides the analytical consideration for a credit score. Therefore, a credit score using the robust analytical technique while addressing these factors is key for its adoption.
    Customer & Product Sciences

  • Day 2

    August 20, 2021

  • Join this session and learn how Rakuten's AI Product teams approach high impact AI solutions and products across 70+ businesses globally.
    Keynotes

  • Data is being leveraged by businesses to deep diving into customers' day-to-day life to understand their requirements and provide personalized solutions. Rakuten’s innovative frameworks combine big data with strategic business directions to create marketing solutions for brands which allows them to pinpoint their target users, as well as find the best possible ways to reach the target audience. Attend this session to explore how various dimensions of data science and analytics are being used to tackle real-life business problems in e-commerce, optimization of delivery logistics, and other interesting use cases.
    Keynotes

  • Science has fueled nearly every aspect of the world today, including healthcare, agriculture, transportation, entertainment, and the workplace. Judgement, as one of the core tenets of medicine, relies upon the integration of multi-layered data with nuanced decision making. I believe that we need to pay attention to it to make the best decisions at several crossroads of our lives. The thoughtful use of science can play a vital role in fixing the problems in society. At Rakuten, we attempt to treat cancer with light and develop AI algorithms to accelerate drug discovery, harness biomarkers to accurately match patients to clinical trials, and truly personalize cancer therapy using only patient's own data. In this talk, we present our approaches towards conquering cancer using AI.
    Advances in AI

  • Learn how retailers use AI-based product enrichment techniques and image recognition models to make products more searchable. Understand how using AI smart search and complementary product recommendations like “shop the look” can help eCommerce companies engage consumers and drive increased revenue.
    Customer & Product Sciences

  • Rakuten Data Platform provides Data and Analytics services to various services across Rakuten Group. It today collects, manages and serves data sets from 70+ services with 43+ integrated services, 20K+ managed datasets and 6500+ weekly Active Users. In this session we will briefly touch overall data landscape, Journey, the evolution of this platform over time, high-level architecture, the common challenges we are trying to address and the approach we have taken to address those challenges.  We will then drill down into the Data Discovery & Utilization part of the platform which is the key to the democratization of Data within Rakuten Group.  You will also have a sneak peek into New products & toolsets which we are building some of which are in alpha/beta stages today.
    Data Science Platforms & Analytics

  • Rakuten group operates more than 70 different services, such as e-commerce, fintech and mobile services, our data capture customer behaviours with various aspects. By fully utilising Rakuten data, we’re building customer models for understanding customers. In this talk,  we will introduce several research projects such as (1) customer attribute prediction, (2) customer relationship identification, (3) measuring customer credibility and (4) prospective user extraction.
    Customer & Product Sciences

  • Light-weight Convolutional Neural Networks (CNNs) are mobile-friendly models that can provide inference without the need for any specialised hardware. These models can be very effective in point-of-care settings, where the detection of disease has to be performed in real-time. The talk will highlight few developments of the Medical Imaging Group (MIG) at the Indian Institute of Science, especially towards COVID19 management and diagnosis. Deployment of these lightweight networks on embedded platforms to show highly versatility as well as prove optimal performance in terms of being accurate will also be highlighted. The developed models having latency in the same order as other lightweight networks without compromising the accuracy will also be shown.
    Advances in AI

  • This talk will touch upon the need for digital automation for behaviour analysis. Human behaviour analysis and activity analysis is an extremely complex subject. AI has been attempting to play a bigger role in the domain of human activity analysis. The need for human analysis allows better solutions to be built for 1.Media, 2. Sports, 3. Consumer Packaged Goods, 4. Manufacturing. Video is known to be the source of truth for capturing information. The challenge with video is: it's expensive to analyse the unstructured data inside videos and generate useful insights on what is happening across a sequence of frames( read activities). With this background, we would like to cover how the need for an end to end activity recognition platform has evolved and has been well received for use cases specific to the Consumer Packaged Goods industry. This platform is capable of enabling DIY Video AI for activity recognition. 1. A data annotation component with the ability to do automated annotation 2. A component to build models that can be deployed on-premise or in the cloud. 3. A component for inferencing, correction of inferences and feedback to model building and training. 4. An insights component that is capable of analysis of detections and generation of intuitive analytics insights. 5. How an integration between AI in the cloud and AI on edge has been implemented and pushed to production. We will also cover how all of the above are helping large multinational majors in the CPG segment apply their domain knowledge to generate new behaviour insights and apply activity recognition to analyse product use and measure the effectiveness of product redesign initiatives.
    Data Science Platforms & Analytics

  • Quantum computing has the potential to transform every domain, every business and every aspect of our lives, and the Quantum-AI combination is going to be a bonanza for business. Let’s understand how. Google’s quantum computer ‘Sycamore’ was been able to solve a complex mathematical calculation in just 3 minutes that a powerful supercomputer would have taken approximately 10,000 years. We call it ‘Quantum Supremacy’ in the world of ‘Qubits’ when a quantum computer outperforms a classic supercomputer. Now we can easily imagine, that with this enormous computational speed combined with the power of AI how it’s going to bring about a radical change in the way we perceive classic computing today. A quantum computer is expected to be at least hundred million times faster than a classic computer. But it will be completely wrong if we think quantum computing will just bring extra speed because it will also bring some other significant dimensions specifically while combined with Machine Learning. Scientists and experts have already forecasted that Qubit in Quantum and Artificial Neurons in AI are going to essentially rule the scientific and technological arena of the future. We need to also understand that quantum computing is not just a boon but essentially the need of today and tomorrow because the silicon revolution is slowly collapsing as it has almost reached its limit. The rise of quantum along with AI is going to manifest the whole spectrum of new possibilities in the field of science and technology. Quantum computers can solve the wide range complex optimisation problems in each domain which conventional computing struggles to perform on time. These optimisation challenges are intrinsic in the field of finance, aviation,  manufacturing, logistics, drug research and medicine, etc.
    Advances in AI

  • Most chatbot projects fail. In this session, we’ll first look at the standard approach that leads to the ‘typical’ chatbot you’ll encounter on many websites or mobile apps, and why it never works. Then, we’ll present the approach we use at Rakuten to ensure our chatbots provide real value to our businesses through natural, conversational experiences that empower customers to self-serve successfully. Finally, we’ll walk through a specific example of our Rakuten Mobile AI Assistant, show the steps we are taking to keep its performance high, improve its coverage over time, and measure its value to communicate back to the business.
    Data Science Platforms & Analytics

  • Product Matching In E-Commerce, Product Matching is one of the fundamental problems for various use cases like  (1) Competitive pricing of products,  (2) Deduplication of products in the catalog,  (3) Grouping items from various merchants  (4) Recommending products. The requirement is to match a product accurately against a catalog spread across tens of thousands of taxonomy nodes and millions of items. Product matching results must be accurate, and the margin for error is minimal to use Product Matching across use cases.  In this talk, we touch upon the “Six honest serving-men” by Rudyard Kipling –What, Why, How, Where, When, and Who of Product Matching. We share the overall approach, experience in designing and orchestrating Deep Learning models with a scalable architecture to achieve the required results. Here we have approached the problem at the grass-root level consisting of five stages  (1) Identifying attributes per taxonomy node  (2) Classification of Products  (3) Attribute Enrichment from NER (Text) and Image feature extraction  (4) Search against multiple indices and filter results for mandatory attributes  (5) Re-rank to improve the relevancy of shortlisted results.  We also address Product data quality, measured at every stage to improve the overall performance of Product Matching, towards meeting business needs.
    Customer & Product Sciences

  • Most of the entities in the world are connected via any kind of relationship such as social networks, mobile networks, financial networks, user-product relationships. A graph (or network) is a natural way to represent such representations. Recently graph neural networks are getting paid a lot of attention from industries and academia to perform representation learning on graphs with neural networks so that we can use learned embedding for downstream tasks such as community detection, recommender systems,  anomaly detection, and so forth. This talk covers an introduction to graph neural networks and their applications to various areas.
    Advances in AI

  • Scaling ML/AI has been a major challenge for medium to large organisations. Most organisations can productionize only 30% of their ML efforts. Join us for a deep dive into how we are confronting these challenges at Rakuten. With this session, you can learn about Rakuten’s Data Science Platform, Architecture and Modernize Feature Store capabilities that help in productionizing ML predictions faster at scale and enable collaboration across organizational boundaries to build value.
    Data Science Platforms & Analytics

  • With more than 70 different services in the Rakuten Group globally, our data science teams cover diverse initiatives in both the online and offline worlds. Offline Geodata and Geo Science applications are key to optimization and overall success in the fields of Logistics, Site Planning, Area Marketing and improving Customer Experience and many more.  In this talk, we will cover some of the Geo initiatives at Rakuten and discuss some interesting questions around the viability for online data to fully represent a user and how to potentially rectify that via offline data and data science.
    Customer & Product Sciences