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Ai artificial intelligence in japan

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Data Artist, a Japanese company, specialized in AI services,
explains why and how artificial intelligence can be used to
to make Japan and the world a happier and better place than today.

Publicada em: Tecnologia
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Ai artificial intelligence in japan

  2. 2. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? “AI is software or systems that simulate the intelligence processes of humans”
  3. 3. OUR FRIEND AI HELPS US IN VARIOUS WAYS Predict tomorrow's sales Make taglines for ads Automatically create logos Create news articles Compose songs Detect abnormalities workings in machines Create art Predict TV program ratings Predict game outcomes Inform about crop growth Perceive the gender and age of customers Teach the contents of images and movies Find the magic moments from video and footage Forecast next year's or next season's trends Detect infrastructure deterioration Detect intractable disease from images Forecast temperatures for the coming winter Predict the efficacy of medicine Automatically separate garbage Automatically identify intruders
  4. 4. EVER-EVOLVING AI FINALLY TAKES OFF 1st AI BOOM 2nd AI BOOM DEEP LEARNING 1960's 1970's 1980's 1990's 2000's 2010's AI Winter AI AI promising but waay too young to be used for real life challenges! Many challenges remain. Fully dependent on AI experts. Troublesome/Expensive! As a result of rapid advances in AI technology and others AI finally takes off! AI Winter AI
  5. 5. 2012 GREAT ADVANCES IN DEEP LEARNING DEEP LEARNING - a machine learning method within the field of AI  YEAR
  6. 6. DEEP LEARNING - STEP 1 ”LEARN” FROM VAST AMOUNTS OF DATA Deep learning is a type of machine learning where the AI “learns” and automatically is able to identify data characteristics through processing massive amounts of data. (image, video, or sound data) One typical and easy-to-understand example is where the AI learns to identify cats from processing thousands and thousands of cat images.
  7. 7. DEEP LEARNING - STEP 2 VERIFY ACCURACY OF AI The next step is to verify the accuracy of the AI image recognition technology used. A major breakthrough took place in 2012 when deep learning techniques developed at Toronto University (using images of cats) and Google X lab (using video clips of cats) were able to recognize 85% of cat images/video, a much higher percentage than in the past. Since the breakthrough in 2012, the accuracy of AI image recognition technology has gradually improved year by year. I can say, with a high probability, that it is a cat! ?
  8. 8. GPU GPU GPU GPU THREE REASONS EXPLAINING THE RISE OF AI Deep Learning Improvements in computing power BIG DATA - Availability of large amounts of data from the web. AI tech progress and an ongoing AI research boom
  9. 9. AI ♥ GAMES - SOME RECENT VICTORIES 2010 2011 2012 2013 2014 2015 2016 2017 $5000 WATSON IBM Watson wins at Jeopardy! Shogi AI “Bonanza” beats a human Shogi master Shogi AI “Bonanza” beats a human master Igo AI “Alpha Go” beats a human Go master Poker AI beats a human Poker master AI conquers Ms. Pac Man
  10. 10. SOME BIG AI PLAYERS WORLDWIDE Apple IBM Google Facebook Samsung Baidu NVIDIA Salesforce Bosch Microsoft Alibaba Siemens General Electrics Tata Infosys Tencent
  11. 11. AI VENTURE COMPANIES SHOW STRONG GROWTH 2013 $1,039 $3,125$2,677 160 253 364 493 658 $6 億 $5,021 2012 2014 2015 2016 Ref: Deals $589 AI ANNUAL GLOBAL FINANCING HISTORY Disclosed Funding ($M)
  12. 12. JAPANESE AI INVESTMENT ALSO RAPIDLY INCREASING Rakuten Hitachi NTT Sony Panasonic Recruit Fujitsu Toyota Fanuc NEC Komatsu
  15. 15. AI EXCELS AT FINDING ABNORMALITIES MEDICAL CARE X-RAY SECURITY “Suspicious individual intruding” MANUFACTURING SALES AGRICULTURE INFRASTRUCTURE A I “Suspected tumor” “Product contamination” “Female/20s” “Extra Water and Pesticide Required” “Danger! Bridge crack”
  16. 16. 今年の農作を予測・企業の業績を予測・学生の成績 予測・社員のパフォーマンスを予測・週末の売上を 測・秋のファッショントレンドを予測・医療コスト 予測・自動車の需要を予測・犯罪率を予測・外国為 市場の動向を予測・来年のファッショントレンドを 測・選挙結果を予測・地震発生をッ予測・機械故障 予測・航空券の需要を予測・失業率を予測・平均寿 を予測・テレビ番組の視聴率を予測・ヒット曲を予 GDP を予測・サッカー試合の結果を予測・週末の 気を予測・大気汚染を予測・脳梗塞の回復率を予測 返済率を予測・合格率を予測・競馬の結果を予測・ 雑状を予測・石油単価を予測・退職率を予測・ヒッ 曲を予測・心臓発作の回復率を予測、新社員のパフ ーマンスを予測・テレビ番組の視聴率を予測・四半 AI ENABLES QUICK AND ACCURATE PREDICTIONS % LOWEST PRICE Camel Air flycheap.com 40,000 BEST BUY: AUGUST Copyright © 2017 Data Artist Inc., All rights reserved. Weekly Stock Price Prediction 65% 35% 30% 70% Brand S 80% 20% Brand T 10% 90% Brand P 45% 55% Brand D Sales Breakdown ● Riceballs: 50 ● Lunch Boxes: 25 ● Bananas: 50 ● Tea Drinks: 125 ● Sweets: 250 ● Ice Creams: 85 Mon Tue Wed Thur Fri Sat ¥114,514 ● Instant Noodles: 70 ● Sausages: 75 ● Sallads: 85 ● Chips: 125 ● Chocolate: 215 ● Shampoo:      15 Sun SALES FORECAST (TOMORROW) DECEMBER
  17. 17. AI FOR NOTIFICATION, DIALOGUE AND EDUCATION♥ Our tiger is now near the fence! Time to feed the bunnies. Please come! Dear Suzuki-san Please return the book by Friday! Suzuki-san, we recommend this book especially for you! Do you like green robots? Zoo Chatbot English Conversation Robot Library Chatbot
  18. 18. AI USED FOR TRANSLATION/INTERPRETATION Voice Images/ Video Lip Reading I like orange juice! Hand writing I like orange juice! I LIKE ORANGE JUICE I LIKE ORANGE JUICE
  19. 19. AI HELPS US TO UNDERSTAND FOREIGN OBJECTS Surströmming is a type of fermented Baltic Sea herring. Extremely smelly. Caution required. Surströmming The Daruma doll, also known as a Dharma doll, is a hollow, round, Japanese traditional doll modeled after Bodhidharma, the founder of the Zen sect of Buddhism Daruma Doll ゲルは、主にモンゴル高原に 住む遊牧民が使用している、 伝統的な移動式住居のこと。 日本では、中国語の呼び名に 由来するパオ(包)という名前で 呼ばれることも多い。 ゲル ( 家屋 )
  20. 20. AI - GENERATING ART, MUSIC AND TEXT BA GEL SH OP AL W AYS FRE SH 2015EST. ♪Compose Songs Create art-like Images and Videos Create Logos Make Recipes Create text for taglines, product presentations, news articles and others “Fluorescent light x is a compact fluorescent lamp used for downlight of commercial facilities and hotels.”
  22. 22. SOME PEOPLE ARE CONCERNED ABOUT AI Will AI take over my JOB? Will AI ATTACK us? Will AI increase DISPARITIES in our society?
  25. 25. CHALLENGES: AN AGING POPULATION 95 2000 05 10年 A declining birthrate and the aging of society has worsened the economic burden on the working population year by year. This trend is likely to continue. 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Burden of supporting the population aged 65 and over by those aged 15 to 64 65 years and over 15~64 years 65 years and over 15~64 years 65 years and over 15~64 years Source: “Population Future of Japan”, National Institute of Population and Social Security Research (2012) (%) 1955 60 65 70 75 80 85 90 95 2000 05 10 0.0 2.0 4.0 6.0 8.0 10.0 Source: "Overview of 2013 FY National Health Care Expenses", Ministry of Health, Labor and Welfare (2013) Changes in the ratio of medical expenses to national income 40 Year 2013 200 Billion Yen Year 1954 9.8 8.6 4.8 2.3 Trillion Yen
  26. 26. CHALLENGES: OVERWORK Are Japanese People, in particular men, still working too much? The working hours of the Japanese people seem to be similar to the world average but some data suggests that, for male regular employees, the overtime worked is much higher than the world average. The data also suggests not only that the number of paid holidays are comparatively few but also that the rate of workers taking paid holidays is low. 100 90 80 70 60 50 40 30 20 10 0 (min) Source: "International Comparison of Living", Research Institute for Advancement of Living Standards (2009) Average overtime hours regular employee/day Females Males 0 5 10 15 20 25 30 30/30 days Japanese workers use only half of paid holiday 100% 83% 80% 78% 71% 53% 100% 100% 100% 100% 80% 50% 30/30 days 30/30 days 25/25 days 14/14 days 25/30 days 12/15 days 12/15 days 14/18 days 15/21 days 8/15 days 10/20 days Brazil France Spain Austria Hong Kong USItaly Mexico Singapore India Korea Japan Japan US France Korea Source: “Vacation Deprivation Study”, Expedia (2016)
  27. 27. CHALLENGES: WORK-LIFE BALANCE Japanese men have the lowest share in house chores and family care in the world. Relatively speaking, there are many spouses who are dissatisfied with the male share in house chores / family care. 43 41 40 40 39 38 38 38 37 37 37 36 35 35 35 34 33 33 32 32 32 32 31 31 31 30 30 30 30 26 25 25 18 0 5 10 15 20 25 30 35 40 45 Spousal house chore and family care share rate (for families with children) Source: Family and Changing Gender RolesIV , ISSP (2012) 0 10 20 30 40 0 10 20 30 40 Dissatisfaction level with house chore burden (wife) (Percentage of those who answered "rather dissatisfied" or "quite dissatisfied") Dissatisfaction level with the relationship between the partner and the child (wife) Source: “International comparison of living - couple survey of Japan, the United States, France, Korea”, Research Institute for Advancement of Living Standards (2009) Sweden Mexico Iceland Denmark Norway Venezuela France Ireland UK SouthAfrica Latvia Lithuania Poland Finland Slovakia Croatia US Spain Philippines Germany(West) Taiwan Russia Bulgaria Switzerland Australia SouthKorea Chile Slovenia Argentine CzechRepublic Israel Austria Japan KoreaFranceUSJapan KoreaFranceUSJapan (Percentage of those who answered "rather dissatisfied" or "quite dissatisfied") % %
  28. 28. CHALLENGE: LOW WORK SATISFACTION Several studies show that the work satisfaction level of Japanese employees is very low compared to other countries. (In comparison with 35 countries) Source: Indeed Job Happiness Index , Indeed (2016) 0 10 20 30 40 50 60 70 90 "Do you feel a sense of satisfaction in your current job?" The satisfaction level of regular Japanese employees are the lowest among 26 countries Source: LinkedIn Talent Report , LinkedIn (2014) Work Satisfaction Index 35rd India Malaysia Germany Indonesia UAE UK SouthAfrica Australia US Canada Norway Denmark NewZealand Netherlands Sweden Turkey China Singapore HongKong Italy Spain Finland Russia Brazil France Japan (Lowest Ranking)
  29. 29. CHALLENGES: LOW PRODUCTIVITY Work productivity refers to work efficiency in the creation of products or services. It is calculated by dividing the production amount by total labor. Among developed countries, Japan's productivity is relatively low which means that the remuneration per hour worked is comparatively low. Comparison of Work Productivity in G7 countries (GDP per hour) US France Germany UK Canada Japan Italy OECD Avg. $68.3 $67.5 $66.6 $53.6 $52.4 $51.1 $50.8 $45.5 Source: OECD (2015) Hourly Labor Productivity of OECD Countries After 2015 / GDP standard revision (out of 34 countries) Source: OECD (2015) 19th
  30. 30. JAPANʼs MAIN CHALLENGE: HAPPINESS? OECD Better Living Index (2016) 23 最下位 rd (of 38 countries) UN World Happiness Report (2016) 53rd (of 153 countries) Lowest Rank G7 OECD 6th (of 7 countries) G7 26th (of 35 countries) A survey on the "happiness level" of each nation is held annually by the OECD and the United Nations. These surveys show that the Japanese happiness level is relatively low compared with other developed countries. The survey data presented on previous pages may indicate some reasons for why the happiness level in Japan is comparatively low.
  31. 31. AI will contribute to solve many of the issues facing us today and tomorrow. SOLUTION?
  32. 32. More Time to Enjoy Life Higher standards of living can be obtained without need for excessive work. ※Using AI, Japan could more than triple its GDP by 2035, according to a study by Accenture. Men can afford more time with the family; helping with chores and care for the family. In a society without excessive overwork, females will be better able to balance work and family. Improved Standard of Living Improved Work Satisfaction Work-Life Balance Improved Productivity ▼ ▼ No More Boring & Tedious Work ▼ AI Humans will have jobs that are motivated by human pleasure; jobs that require creativity; caring for other humans, beautifying the environment and others.
  34. 34. We believe. We act. For our future. www.data-artist.com