[db analytics showcase sapporo 2017] microsoftのaiテクノロジーを活用しよう...

Is_dog

True

True

False

True

: :

Step1: 予測モデルの構築コンピューターを用いてデータを統計学的な分析手法に則って解析。データに含まれる潜在的なルール,相関関係,特徴を見出す(=モデル化)

東京大学 特任准教授松尾 豊 氏 による AI 発展の系譜

総務省「AIネットワーク社会推進会議」資料

・・・・・

・・・・・

・・・・・

・・・・・

・・・・・

学習済みモデル利用

学習モデル作成

→ MLの予測モデルを自作せずに結果だけ利用

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Search

Computer Vision

Emotion

Face

Video

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

Recommendations

Knowledge

microsoft.com/cognitive

Labs

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

microsoft.com/cognitive

Content Moderator

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

Content Moderator

LabsProject Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongongmicrosoft.com/cognitive

Labs

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

microsoft.com/cognitive

Content Moderator

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

GANew

https://westus.api.cognitive.microsoft.com/emotion/v1.0/recognize

using Microsoft.ProjectOxford.Emotion;

using Microsoft.ProjectOxford.Emotion.Contract;

string subkey = "YOUR_SUBSCRIPTION_KEY";

var eClient = new EmotionServiceClient(subkey);

Emotion[] eResult = await eClient.RecognizeAsync(url);

float score = eResult[0].Scores.Happiness;

Labs

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

視覚

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Content Moderator

microsoft.com/cognitive

SearchVision Speech Language Knowledge

Categories [ { "Name": "people_swimming", "Score": 0.98046875 } ]

Faces

[ { "Age": 36, "Gender": "Male", "FaceRectangle": { "Top": 133, "Left": 298, "Width": 121, "Height": 121 } } ]

Dominant color background

■"White"

Dominant color foreground

■"Grey"

Accent Color ■#19A4B2

Where there is love there is life.Mahatma Gandhi2 October 1869 — 30 January 1948

GA

[Document] https://docs.microsoft.com/ja-jp/azure/cognitive-services/custom-vision-service/home[Check&Try] https://www.customvision.ai/

SearchVision Speech Language Knowledge

New

DemoCustom Vision API

[Document] https://docs.microsoft.com/ja-jp/azure/cognitive-services/video-indexer/video-indexer-overview[Check&Try] https://www.videoindexer.ai/

SearchVision Speech Language Knowledge

New

DemoVideo Indexer API

Labs

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Translator

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

Content Moderator

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

音声

microsoft.com/cognitive

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Speech

*ja-jp含む

*ja-jp含む

Speech Translation=Speech Recognition＋Translation＋Text-to-Speech

Labs

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

SpeechAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

Content Moderator

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

言語

microsoft.com/cognitive

Translator

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

Language

SearchVision Speech Language Knowledge

[Document] https://docs.microsoft.com/en-us/azure/cognitive-services/luis/home[Check&Try] https://www.luis.ai/

*ja-jp 含む*ja-jp 含む

https://text-analytics-demo.azurewebsites.net/

SearchVision Speech Language Knowledge

Labs

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

Language

Content Moderator

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

知識

microsoft.com/cognitive

AcademicKnowledge

Entity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

SearchVision Speech Language Knowledge

SearchVision Speech Language Knowledge

SearchVision Speech Language Knowledge

[Document] https://docs.microsoft.com/ja-jp/azure/cognitive-services/custom-decision-service/custom-decision-service-overview[Check&Try] http://ds.microsoft.com/

New

Labs

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

Content Moderator

Project Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongong

検索

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

microsoft.com/cognitive

SearchVision Speech Language Knowledge

[Document] https://docs.microsoft.com/ja-jp/azure/cognitive-services/bing-custom-search/overview[Check&Try] https://customsearch.ai/

New

Computer Vision

Emotion

Face

Video

Video Indexer

Custom Vision Service

Vision

Bing SpeechCustom Speech

ServiceSpeaker

Recognition

Translator

Speech

Bing Spell Check

Linguistic Analysis

Language Understanding

Text Analytics

Web Language Model

LanguageAcademic

KnowledgeEntity LinkingKnowledge Exploration

QnA Maker

Recommendations

Custom Decision Service

Knowledge

Content Moderator

Bing Web Search

Bing Autosuggest

Bing Image Search

Bing Video Search

Bing News Search

Bing Custom Search

Search

LabsProject Prague Nanjing Project Project JohannesburgProject Cuzco Project Abu Dhabi Project Wollongongmicrosoft.com/cognitive

https://aka.ms/gestures

[Check&Try] https://labs.cognitive.microsoft.com/

https://labs.cognitive.microsoft.com/en-us/project-johannesburg

学習済みモデル利用

学習モデル作成

サービス検証プロトタイプ開発

投資 業界 業務シナリオ販促 生産性

流通&小売 広報&マーケ品質 新製品

投資 業界 業務シナリオ販促 生産性

運輸 社内IT品質 新製品

Webチャットエンドユーザー

チャット制御質問特定（LUIS）

AQ

質問検索

F F

会話履歴 QA

AQ

F 特定?

Q

Y

N

A

追加学習

（Azure Search）

FAQ自動応答システム

複数チャットを特定応答

1 23

4

56

7 8

9

Q:質問A:回答F:フィードバック

１Intent－１Question

サービス実現性の検証を実施予定(2017年7月～)

投資 業界 業務シナリオ販促 生産性

流通&小売 営業&販売品質 新製品

サービス検証プロトタイプ開発

de:code 2017code your future

投資 業界 業務シナリオ販促 生産性

流通&小売 営業&販売品質 新製品

投資 業界 業務シナリオ販促 生産性

流通&小売 営業&販売品質 新製品

投資 業界 業務シナリオ販促 生産性

流通&小売 営業&販売品質 新製品

• Python, C++, BrainScript• 学習済みモデルは C#、Javaで動かすことも可能• MIT や Stanford 等の様々な研究者と共同作業で開発中• 2017年6月、バージョン2.0がGA (正式リリース)に

Caffe CNTK MxNet TensorFlowFCN5 (1024) 55.3ms 51.0ms 60.4ms 62.0msAlexNet (256) 36.8ms 27.2ms 29.0ms 104.0msResNet (32) 144.0ms 81.5ms 84.5ms 181.4msLSTM (256)(v7 benchmark)

- 43.6ms(44.9ms)

288.1ms(284.9ms)

-(223.5ms)

http://dlbench.comp.hkbu.edu.hk/ Benchmarking by HKBU, Version 8

2017年4月時点

エラー率

CNTK のスケール性が世界記録達成に貢献

歩道画像を解析撮影地点ごとに

ごみの種類や数を判別

地図データ（Google,ZENRIN）

清掃員の最適配置や新たな街づくりの提案へ

参照 http://www.image-net.org/http://image-net.org/challenges/LSVRC/2012/ilsvrc2012.pdf

ILSVRC大量のタグ付き画像データの認識精度を競うコンテスト

IMAGE NET 2012年

http://image-net.org

AlexNet, 8 layers(ImageNet 2012)

Very

VGG, 19 layers(ImageNet 2014)

Ultra

ResNet,152 layers

By Microsoft

重みづけ更新

重みづけ更新

重みづけ更新

皆さんも簡単にお試しいただけます

https://aka.ms/cntk_image

モデル

学習データを使ってモデルを教育すること

モデルの出来を精度から測ってあげること評価

The CIFAR-10 dataset

故障診断 医療診断物品の自動仕分け

データ準備

学習

モデル 分割

評価

データ準備

¥image¥train¥00000.png 6¥image¥train¥00001.png 9 ¥image¥train¥00002.png 9

データ準備

学習

モデル 分割

評価

データ準備

学習

モデル 分割

評価

モデル

http://intellabs.github.io/RiverTrail/tutorial/

Convolution, Pooling Layerを含むNeural Network

Convolution()MaxPooling() Dense()

AlexNet, 8 layers(ImageNet 2012)

データ準備

学習

モデル 分割

評価

学習

https://aka.ms/cntk-setup

CPU GPU

簡単!検証用には OK !

パフォーマンスはこちら!面倒くさい環境構築…

https://aka.ms/deepvm

Azure N シリーズ GPU インスタンス

2 種類の NVIDIA GPUを搭載サイズ コア

数 メモリ Disk RDMA GPU

NV6 6 56 GB 380 GB - M60 ×1

NV12 12 112 GB 680 GB - M60 ×2

NV24 24 224 GB 1.5 TB - M60 ×4

NC6 6 56 GB 340 GB - K80 ×1

NC12 12 112 GB 680 GB - K80 ×2

NC24 24 224 GB 1.5 TB - K80 ×4

NC24r 24 224 GB 1.5 TB InfiniBand K80 ×4

Visualization のNV 系

Compute のNC 系

Deep Learning はこちら

Kepler Maxwell Pascal Volta

GeForceゲーミング

Quadroプロフェッショナルグラフィックス

TeslaHPC & Cloud

M60

M6

M4 M40

P6000

GTX 1080

M6000M5000K6000K5000

GTX 980GTX 780

HPC 用

GRID 用

K80K40K20 P100

K2

K520

P40P4DL 用

M10

P5000

K1

https://aka.ms/cntk-tutorial

https://github.com/msmamita/cntk_handson

開発者チームも頻繁に見ています

https://stackoverflow.com/questions/tagged/cntk

microsoft.com/cognitive

https://docs.microsoft.com/ja-jp/azure/cognitive-services/

https://github.com/Microsoft?q=cognitive

https://westus.dev.cognitive.microsoft.com/docs/services/https://dev.cognitive.microsoft.com/docs/services/

https://docs.com/cogbot/9675/cognitive-services

[次回勉強会]2017/06/16(金) @日本マイクロソフト セミナールーム(品川)

Cognitive Toolkitドキュメント、チュートリアル、モデル ギャラリー、ブログなど…

http://cntk.ai/https://github.com/Microsoft/CNTKAzure Notebookshttps://notebooks.azure.com/cntk/libraries/tutorialsMicrosoft Cognitive Toolkit (CNTK) Japan Communityhttp://aka.ms/cntkjapan

© 2017 Microsoft Corporation. All rights reserved.

本情報の内容（添付文書、リンク先などを含む）は、作成日時点でのものであり、予告なく変更される場合があります。