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EduLab (TSE: 4427), Japan’s Leading EduTech Innovator in Adaptive e-Testing Powered by Artificial Intelligence to Profitability — H.E.R.O. Innovators Insights from CEO Junichi Takamura

Taking advantage of the character recognition technology cultivated through the development of AI technology and automatic scoring technology for handwritten tests, we will capture the demand for automation of increasing administrative work in the financial industry, insurance industry and healthcare industry,” comments Junichi Takamura, founder and CEO of EduLab (TSE: 4427).

Study Gear (49.3% of FY2018/09 sales, +25.1% yoy) provided by the Eiken Society and Educational Digital Solutions to support English learners including examinees for the Eiken exam in which more than 22,000 schools and cram schools participate and more than 400,000 people are continuously learning;(2) Providing test system (29.1%, +48.5% yoy) such as the Eiken-kai 4–5 class speaking system;(3) CASEC (11.7%, +3.7% yoy), an IRT (Item Response Theory) computer-aided test in joint development with the Eiken Society which can accurately measure the test examinee’s ability regardless of the difficulty of the test by automatically changing and analyzing test questions according to the individual’s abilities and is the world’s first test using adaptive technology;(4) Eiken Jr.

Contract (26% of sales): EduLab is entrusted with the creation, scoring, aggregation and system construction, management and operation of test questions from national and local governments that implement academic ability research projects, as well as public institutions, universities and other educational institutions, such as the Eiken Society, achievement survey (PISA), international adult competence survey (PIAAC), international mathematics and science education trend survey (TIMSS), Saitama prefecture academic ability survey utilizing IRT, etc.

There is an enhanced English learning demand for qualification and examination test in a paradigm shift in the education industry with the structural change of the external educational environment that include a new university admission common test from the fiscal year 2020 to include the qualification and examination test of the four English skills, adding ‘talk’ and ‘write’ to the two skills of ‘read’ and ‘listen’;

EduLab achieved a 15% yoy increase in sales and 63.9% yoy rise in operating profit in FY2018/09 with improving operating margin from 17% to 24.3% and ROE (= EBIT/ Equity) of 38.1% and ROA of 12.4%, propelling a 11.6% increase in market value since its listing on 21 Dec 2018 at the IPO price of 3,270 yen per share to US$273m.

Management expects FY2019/09 sales to rise 71.6% yoy to 6.81bn yen and operating profit to increase 46% to 1.4bn yen.NTT DoCoMo and Obunsha, a major educational publishing company founded in 1931 with its English textbook for college entrance examination achieving #1 in bookstore sales, are strategic shareholders with 5.06% and 6.34% respectively.

CEO Takamura comments thoughtfully that there is a paradigm shift and structural change in the educational environment in Japan that creates an enhanced English learning demand for qualification and testing: “As globalization accelerates and more practical communication skills in English is required, the course of English study has been revised for the first time in about 10 years recently, and a new university admission common test to include the qualification and examination test of the four English skills, adding ‘talk’ and ‘write’ to the two skills of ‘read’ and ‘listen’ so far.

There is an enhanced English learning demand for qualification and examination test in a paradigm shift in the education industry with the structural change of the external educational environment: (1) Under the development of the ICT environment at schools conducted under the 5 Year Plan 2018–2022 for the ICT conversion of education, it is expected that ICT will be actively utilized such as the introduction of digital textbooks, CBT of various tests at primary, middle and high school, including the English speaking CBT National Academic Achievement Survey conducted nationwide in 2019.(2) From the fiscal year 2020, it is expected that the ‘university admission common test’ will change greatly including the embodiment of the evaluation of the four skills of English (reading, listening, talking, writing).

We believe that future market movements will be a major business opportunity for EduLab who will become indispensable in the evaluation and measurement of learning progress in the knowledge-based society.” When asked about how he came about to start EduLab, the challenges he faced and overcame and the breakthroughs during his early entrepreneurial period, CEO Takamura shared briefly and reflectively the story of his early entrepreneurship period: “After completing an MBA at the University of Hartford, USA, in 1990 and an MS at the MIT Sloan School of Management in 1993, I was engaged in the high-speed scanner business at Scan-Optics LLC.

In addition, we have long-term partnership with Obunsha in the educational contents related business, and NTT docomo in the ICT education related business.(3) intellectual capital such as knowledge and information gathering abilities in overseas EdTech markets.” “EduLab’s basic strategy of expanding the scale of its business and ensuring stable earnings is: (1) Product development to capture business opportunities by improving the skills of English exam;

(3) Implement various tests, expand the scope of infrastructure, cultivate customers, (4) Investment of EdTech to become the core of the next generation education solution.” When asked to elaborate on how EduLab’s AI technology DEEP READ came to be developed, its potential applications and expansion plan, CEO Takamura shares: “Various academic achievement surveys are shifting to a method of comprehensively evaluating ‘knowledge / skill’ and ‘critical thinking ability, judgment ability, expression power’ from the conventional method that mainly focuses on just ‘knowledge and skills’.

The reason behind the development of DEEP READ was the enormous amount of time and cost savings associated with grading of the answers that had been a long-standing problem.” “And the need for automatic scoring is increased by the rise in the number of descriptive papers from the 2020 college entrance examination exam.

EduLab has developed and launched on 18 Jan 2018 a highly accurate handwritten character recognition technology called ‘DEEP READ’ using AI technology based on deep learning from the viewpoint of improving grading efficiency of descriptive expression solutions in large-scale academic ability surveys and tests, shortening scoring man-hours and the scoring lead-time.

There are many companies that manage vast amounts of data on paper, such as the customer data and various application forms in insurance companies, financial firms and medical certificates in hospitals.” “In order to solve these problems and to increasing the efficiency of our educational content and scoring work, we have started to research and develop AI character recognition for about 2 years.

This point also gradually improved with the approach by AI, and now it is possible to read multiple characters with very high precision.” “Currently, the character recognition accuracy of DEEP READ is 94.5% (without borderlines which is closer to actual answer sheets) compared to the average of 83%, and 98.9% accuracy when reading specific-format handwritten forms.

Regardless of whether the answer is correct or incorrect, we will be able to drastically reduce the time of the grader who had to confirm all answers.” “From Aug 2018, we collaborated with Box to utilize DEEP READ handwritten recognition service utilizing AI to automate the digitization of handwritten characters and make search in the cloud possible, so that it can be used for more efficient document management.

DEEP READ enables digitization of handwritten characters with overwhelming superiority in accuracy of over 94.5%, which is the top level in the industry and 83% on average for others, and is widely used by companies such as the financial industry, medical institutions and school corporations.” “In addition, we believe that this character recognition technology is applicable not only to educational IT field but also in a wide range of industries processing enormous paper-based data, forms and applications such as banks, insurance companies, hospitals.

Because the technique and service development method utilizing deep learning is relatively easy to apply to other fields, EduLab has developed capabilities that utilize the AI cultivated through the development of handwritten character recognition technology to develop in other fields and enhance the competitiveness of the products and services of the entire Group.” “We are considering natural language processing and personal adaptive learning management system engine as the areas where EduLab is planning to utilize AI.

In addition, since we do not build the environment on the customer side, it is possible to reduce introduction and maintenance cost.” “EduLab was recognized for the first time in Japan in July 2017 as an artificial intelligence company in the education field for our handwritten character recognition based on deep learning technology in the NVIDIA Inception Program’ which aims to train start-up companies trying to revolutionize the industry with advances in AI and data science.” Curious about EduLab’s different services, we asked CEO Takamura to elaborate more and he shares patiently: “English Navigation · Study Gear is a practical English proficiency test to support English learners including those who take exams.

Through the measurement → diagnosis → learning cycle, it provides the best teaching materials for each individual, provides the latest information useful for English learning, supports educators and learners through data analysis, and also serves as a platform for online application for Eiken exam.” “In addition, we offer online study service ‘Study Gear for EIKEN’, the Eiken official online learning app for English learning.

We plan to earn early monetization by acquiring personal and corporate users and advertisers of the platform through appropriate marketing strategies.” “From 2 April 2018, together with NTT docomo, we offered the learning app service ‘English 4Skills’ using smartphones, tablets, PCs and a test that can easily measure the skill of each student while students advance their learning at their own pace.

IRT accurately measures the ability of a test taker without being influenced by the difficulty of a uniform test item like a conventional test, and automatically analyzes the answers to the test items of the test examinee using the adaptive method.” “CASEC is Japan’s first adaptive English test developed since 2001 with 4 million answers and the number of examinees is over 2 million people and the number of candidates increases year by year.

In the modern Japanese society in which further expansion of English ability is an extremely important task, we take advantage of the academically supported measurement theory such as IRT (item response theory) and computer adaptive test to differentiate CASEC as a next generation English test that can also be taken 24 hours on the internet.

The adaptive test which automatically changes and analyzes test questions according to the individual’s ability makes it possible to compare the test results of examinees who took different tests based on the examinees’ answers and to qualify an optimal level of problem according to the examinee’s ability for each question, accurately measuring the examinee’s ability in a short time.

The new development in big data analysis and the latest technology that objectively grasps the academic ability and non-cognitive abilities of children puts forward a stone to pave the way of what the future education will be.” CEO Takamura also commented on EduLab’s overseas business expansion in China and India: “EduLab started a cram school project using ‘adaptive learning’ in China with a partner company in 2014 and started service in the summer of 2017.

It is a new blended learning concept in which the students prepare for new learning contents usually by watching short anime video lessons at home, and teachers do not give lectures in the classroom and provide guidance tailored to each student about the subject, and the students work in cooperation with other students.” “With adaptive learning using online tests, it becomes possible to accurately identify where each student stumbles in the contents of learning and where understanding is insufficient.

We operate a directly operated school in Wuxi, Jiangsu Province and Changsha in Hunan Province, and promoting business alliances in other regions areas such as concluding regional agency contracts.” “As of December 2018, the number of deployed cities throughout China is 47 cities, the number of classrooms we manage is 117, and the number of paid students registered is about 6,000.

As teachers play a major role in student’s learning progress management and motivation maintenance, it became possible to reduce work while offering high quality guidance to students.” “As future management tasks, we will promote further expansion of business including junior high school student business development, expansion of Shanghai teaching material development base and Wuxi system development base, strengthening internal management system, introduce adaptive engine with AI function to improve the accuracy of analysis of personal learning history data by installing the personal adaptive learning management system in the existing system.

Future management tasks include strengthening the test development base in Pune in India, converting Bangalore logistics base nationwide to a logistics center, deploying our proprietary item response theory (IRT) CBT test.” CEO Takamura went on to share about EduLab’s EduTech investments in CodeMonkey, SpeakingPal, Authess, Listenwise, Academic Merit (Finetune) and ELSA: “Over the past few years, EduLab has invested as a limited partner in three U.S.-based education technology venture funds: LearnLaunch, Fresco Capital and GSV Acceleration.

“Boston-based Authess utilized machine learning and big data analytical technology to provide next-generation practical capability measurement test for enterprises in human resource recruitment to reduce the risk of hiring mismatched staff and to hire ‘responsive’ employees who can produce results at the business site.” “Listenwise is an online listening service platform with strengths in non-fiction content actually broadcasted by National Public Radio (NPR) for use as learning material for schools.” “Academic Merit develops services such as Fine Tune that help teachers write English composition teaching methods.

Edusoft, a subsidiary of US ETS with TOEIC® and TOEFL® and the world’s largest assessment body, is the major shareholder.” “Looking ahead, we aim to differentiate itself from other EdTech venture investment funds by making maximum use of the management resources of the EduLab group, not only to pursue mere capital gain income, but also to secure profit by developing the products of our investee companies in other areas and markets, such as CodeMonkey sold in China.” CEO Takamura summed up by emphasizing EduLab’s inspiring philosophy and mission as a roadmap for their development and growth journey in the fourth-generation testing technology era: “Does this test really measure individual ability?

The ability to establish a standard where a person of a certain ability can give correct answer to a certain question with a certain probability makes it possible to provide questions that adapt to the situation, similar to the approach used in eye tests, offering a slightly easier question if the examinee can’t answer a question, or offering slightly more challenging questions if the examinee correctly answers a question.

Artificial Intelligence (AI) Cars and Light Trucks Market Shares, Strategies, and Forecasts, Worldwide, 2019 to 2023

“” has added latest research report on “Artificial Intelligence (AI) Cars and Light Trucks Market”, this report helps to analyze top manufacturers, regions, revenue, price, and also covers Industry sales channel, distributors, traders, dealers, Research Findings and Conclusion, appendix and data source.

As automated process hits the auto industry as a disruptive force, it parallels the automated piloting of the airline industry that saw significant labor savings implementation.

Place Purchase Order@ Change is incremental, we do not have fully functioning Artificial Intelligence (AI) cars immediately, rather, steering, collision avoidance, parking, test driving, series of camera and radar based monitoring systems, lane assist, and adaptive cruise control are being implemented, presaging rapid adoption of Artificial Intelligence (AI) cars and light trucks as the various functions mature and work in the real world.

According to Susan Eustis, team leader for the preparation of the study, “The market for Artificial Intelligence (AI) car and light truck vehicles is anticipated to expand in parallel with the deployment of appropriate roadway controls funded by government programs.

The extension of this type of automated system to commercial fleet vehicles will be rapid after 2019” The Artificial Intelligence (AI) car designs amalgamate a group of features to represent an automated process solution.

Companies Profiled Market Leaders AMD Apple BMW Bosch Daimler AG / Mercedes-Benz Ford Fuji GM Google Hyundai IBM Intel / Mobileye Kairos Nissan NVIDIA NXP Qualcomm Samsung Softbank Tesla Group Texas Instruments (TI) Toyota Uber Volkswagen / Audi Market Participants Audi BAE Systems Boston Dynamics Bosch Group BMW Buick Group Chrysler / Dodge Daimler AG/Mercedes-Benz ECA Robotics Elbit Systems Evatran Group Ford / Lincoln Fuji Heavy Industries / Subaru General Dynamics Google Artificial Intelligence (AI) Car GM / Cadillac Kongsberg Jaguar Land Rover Lockheed Martin Mesa Robotics Mitsubishi Nissan Qualcomm Toyota / Lexus Vecna Technologies Volkswagen / Porsche Volvo Visteon WiTricity Key Topics Auto Artificial Intelligence Automotive Automated driving Automated vehicles Autonomous vehicles in-vehicle compute, Infiniti, Internet of things AI machine learning Mobileye Robot Cars and Trucks Robot steering Robot braking Robot automotive systems Autonomous functions for vehicles Collision avoidance Automated parking Robot Parking Robot test driving Car cameras Car LiDAR Car radar Truck follow me systems Radar based monitoring systems Lane assist Adaptive cruise control Table of Content: Artificial Intelligence (AI) Cars and Light Trucks Executive Summary 45 Artificial Intelligence (AI) Car and Light Truck Market Driving Forces 45 Artificial Intelligence (AI) Cars, Light Trucks, SUVs 48 Artificial Intelligence (AI) Cars / Connected Cars / Transportation 48 Artificial Intelligence (AI) Car and Light Truck Market Shares 52 Artificial Intelligence (AI) Software Market Share of Companies in The Computer and Auto Industries 54 Companies in The Tech Industries Building Auto Artificial Intelligence (AI) Processors 59 Artificial Intelligence (AI) Car and Light Truck Software, Component, and Vehicle Auto Market Forecasts 65 Artificial Intelligence Integrated Software Systems Auto Market 65 Artificial Intelligence (AI) Car and Light Truck Market Forecasts 67 Artificial Intelligence (AI) Car Forecasts 67 List of tables Figure 1.

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