Google's Journey to AI-First

Home , Ilya Sutskever, RankBrain

Google’s Journey to AI-First “Hey Google, What is AI First?”

Chanchal Chatterjee November 13-14, 2019 Slides © Google with many contributors. Not for redistribution.

Google Cloud Platform Copyright Google 2013-2017 1 Era of AI

Observations

General AI? Goal System Environment

Actions

Google Cloud Platform Copyright Google 2013-2017 2 Deep learning

Geoff Hinton’s work fascinated our team at Google X

We thought he was onto something with his ingenious simplifications and engineering of artificial neural networks

Google Cloud Platform Copyright Google 2013-2017 3 Is this a cat or a dog?

Google Cloud Platform Copyright Google 2013-2017 4 2015

Google Cloud Platform Copyright Google 2013-2017 5 2017

Google Cloud Platform Copyright Google 2013-2017 6 A B

From Google Blog. 2018

Google Cloud Platform Copyright Google 2013-2017 7 Areas of Dramatic Improvement

Vision Language Translatio Speech Events n

Google Cloud Platform Copyright Google 2013-2017 8 Agenda

● Artificial Intelligence at Google ● Advancing Techniques ● Industry Applications

Google Cloud Platform Confidential & Proprietary 9 YouTube | WatchNext

Over 70 percent of video watch time now driven by algorithmic recommendations

Aggregate watch time on home page 20 times larger over 3 years - The Verge

Google Cloud Platform Copyright Google 2013-2017 10 RankBrain (a deep neural network for search ranking) improved performance significantly #3 Search signal for Search ranking, out machine learning for search engines of hundreds* #1 improvement to ranking quality in 2+ years* *Google Internal Data

Google Cloud Platform Copyright Google 2013-2017 11 Self-driving cars

Confidential & Proprietary 40 percent reduction in cooling energy

Servers

Facilities Facilities

Typical datacenter Google datacenter electricity usage electricity usage

Google Cloud Platform Copyright Google 2013-2017 13 Google Differentiates with AI

Assistant Search YouTube Query understanding Query understanding Video recommendations Conversation Search ranking Better thumbnails

Cloud Home Translate Cloud ML APIs Speech recognition text and speech TPU Conversation translations

Clips Gmail Photos smart image capture Smart Reply Photos / video search Spam classification Auto- smile montage

Android Cardboard Drive Keyboard input Image stitching Quick Access (also in iOS)

Maps Ads Play Street View images Richer Text Ads App clustering Parsing Local Search Video summarization Music recommendations Advancing Techniques

Google Cloud Platform Confidential & Proprietary 15 Data is the Foundation for AI

TensorFlow

Open Hadoop HBASE Crunch Drill Source Beam

Map Flume Google GFS BigTable Dremel Spanner Millwheel Dataflow TensorFlow Papers Reduce Java

Google Cloud Products BigQuery Pub/Sub Dataflow Bigtable ML

2002 2004 2005 2006 2008 2010 2012 2014 2015 2016

Confidential & Proprietary Google Cloud Platform Copyright Google 2013-2017 16 The most common ML models at Google are models that operate on structured data

Type of network # of network layers # of weights % of deployed models

MLP0 5 20M 61% MLP1 4 5M

LSTM0 58 52M 29% LSTM1 56 34M

CNN0 16 8M 5% CNN1 89 100M https://cloud.google.com/blog/big-data/2017/05/an-in-depth-look-at-googles-first-tensor-processing-unit-tpu

Google Cloud Platform Confidential & Proprietary 17 TFX: TensorFlow-Based ML platform at Google

Integrated Frontend for Job Management, Monitoring, Debugging, Data/Model/Evaluation Visualization

Shared Configuration Framework and Job Orchestration

Tuner

Data Data Data Data Model Evaluation Trainer Serving Logging Ingestion Analysis Transformation Analysis and Validation

Shared Utilities for Garbage Collection, Data Access Controls

Pipeline Storage

Confidential & Proprietary 18 Embeddings: learn signals

0.1 0.5 Learned -0.4 Embedding 128-D ... Function

0.02 ● From input images to low dimensional feature vectors ● Images of the “same class” are close together in the embedding space. ● Works for many data types (e.g. images, words, electrophysiology, transcription profiles) Text comprehension Berlin - Germany + Russia = Moscow take - took + drew = draw

Spain Italy Madrid Rome Germany fallen Berlin fall Turkey drawn given Ankara draw give Russia fell Moscow taken Canada Ottawa drew take Japan Tokyo gave Vietnam Hanoi took China Beijing

Solve analogies with vector arithmetic!

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean.Distributed Representations of Words and Phrases and their Compositionality. NIPS, 2013. YouTube Recommendations - 2016

Source: Deep Neural Networks for YouTube Recommendations

Google Cloud Platform Confidential & Proprietary 21 AI does AI Systematic exploration of the model space, using the techniques finessed in AlphaGo, yields super-human performance in AI network design

Source: Google Blog.

Google Cloud Platform Confidential & Proprietary 23 AutoML: How it works

A technology that can automatically create a Machine Learning Model

Source: Why AutoML Is Set To Become The Future Of Artificial Intelligence, Janakiram MSV. Google Cloud Platform Confidential & Proprietary 25 Industry Applications

Google Cloud Platform Confidential & Proprietary 26 To win in the future you need speed, scale and obsessive user focus

Cloud AI Mobile

Confidential & Proprietary Google Cloud Platform Copyright Google 2013-2017 27 AI-First Online Grocery

● 80x faster analytics for business agility ● 4x faster response to customer service claims with cloud Natural Language Processing ● 15x precision in fraud prediction with cloud Deep Learning ● Cloud ML models for customer lifecycle ● Processing and distributed ML for warehouse robots Business

Pixel Based Automation CPA, SA Sophisticated Ad Targeting Comprehensive Analytics

Opportunity to Improve ● Blended modeling ● Automation ● Integration

Data Analysis (Slow, Labor Intensive) Three ways to deliver AI capabilities

Infrastructure AI Building Blocks AI Solutions

Machine Learning AutoML Dialogflow Cloud Google Sheets Engine Vision Enterprise Edition Speech Differentiation Time to Value

Realtime Big Data AI-First Digital

Business Impact

Maturity