How AI & Deep Learning can help in Supply Chain Decision Making. By Krishna Khandelwal Chief Business Officer

Size: px
Start display at page:

Download "How AI & Deep Learning can help in Supply Chain Decision Making. By Krishna Khandelwal Chief Business Officer"

Transcription

1 How AI & Deep Learning can help in Supply Chain Decision Making By Krishna Khandelwal Chief Business Officer

2 2 2 WHAT IS ARTIFICIAL INTELLIGENCE Set of algorithms and techniques which can help machines in mimicking human behaviour. Recommendations

3 3 3 IT IS NOT NEW 7-8 Boom and Busts cycle Language translations, Intuition etc Failed in generalising solutions at scale Summer of 1956 at Dartmouth College in US where the foundation of Artificial Intelligence as a Discipline of computer science was first laid

4 4 4 IS THE BUZZ REAL THIS TIME? Commercially SCALE now

5 5 5 WHAT IS SO DIFFERENT THIS TIME? Structured Data Algorithms Compute Power Machine Learning Deep Learning

6 6 6 SUPPLY CHAIN AT THE CUSP OF DISRUPTION On an average around the world 180 Million Packages are delivered in a day. Certain problems are designed to be solved by Human Intuition Certain problems are designed to be solved by Algorithms

7 7 7 COMPONENTS OF ARTIFICIAL INTELLIGENCE Reasoning Knowledge Presentation Planning Natural Language Processing Perception Generalised Intelligence

8 8 THE JOURNEY A B 8 C

9 9 9 CHALLENGES AT EACH POINT A Customer placing an Order Free text address - High contextual component Unpredictable delivery timelines Customer and location properties

10 10 10 B Order Packed and Loaded CHALLENGES AT EACH POINT Multi model complex package movement Dynamism against static planning Resource planning Ever increasing storage cost Large Stock/Inventory/Warehouse management

11 11 11 CHALLENGES AT EACH POINT C Customer receives the Order Timely delivery of the package Lack of delivery proofs To deliver in first attempt Visibility to customer Cost vs Serviceability Finding the right location to deliver

12 12 WHAT DOES AI OFFER? A E C F D 12 B Magic at every point

13 13 13 WHAT DOES AI OFFER? Reasoning, Planning, Generalised Intelligence, Perception - Planning of orders done using AI Without AI With AI

14 14 14 WHAT DOES AI OFFER? Generalised Intelligence - Route planning can consider fuzzy human decisions

15 15 15 WHAT DOES AI OFFER? Natural Language Processing - Contextual understanding of address/text No universal format for writing Address PIN/ZIP codes have a very high error rate. Localities can be wrong too Delivered lat logs can be extremely wrong Landmarks are sometimes very local in nature Raw Address Abuse of free text address field Different language - Deciphering context is a challenge Different script Decipher the Address Information Content Local database may be unavailable Formatted Descriptive Co-ordinates Precision Type

16 16 16 WHAT DOES AI OFFER? Natural Language Processing - Contextual understanding of address/text Taufik Hidayat won his 1st gold medal in olympics on Aug 21st, 2004 Person Count Date Premise Locality Sub-locality [Shangri-La Hotel], [BNI, Kota], [Jl. Jend. Sudirman No.Kav 1], [Karet Tengsin], [Jakarta] [10220] Locality City Pin

17 17 16 WHAT DOES AI OFFER? Reasoning : Overlap of route clusters, routes choice (traffic - time vs distance) Knowledge Presentation : Road / Route constraints, # of docking bays, vehicle specific constraints etc Planning : Dynamic planning of load, inventory, fleet, resources etc Natural Language Processing : Contextual understanding of customer s comments, feedback, address etc Perception : Driver behaviour, location preference etc Generalised Intelligence : Intuitive load planning (Over-loading, SLA delays)

18 18 17 POTENTIAL IMPACT ARTIFICIAL INTELLIGENCE McKinsey estimates that firms will derive between $1.3trn and $2trn a year in economic value from using AI in supply chains and manufacturing

19 19 18 ARTIFICIAL INTELLIGENCE - AN AID Is it here to replace people? AI systems will interact with human beings in the real world only to make humans more efficient Google AlphaGo AI defeated Lee Sedol but Go players across the world are using this to improve their skills already

20 20 THANK YOU KRISHNA KHANDELWAL THANK YOU!

Andrei Behel AC-43И 1

Andrei Behel AC-43И 1 Andrei Behel AC-43И 1 History The game of Go originated in China more than 2,500 years ago. The rules of the game are simple: Players take turns to place black or white stones on a board, trying to capture

More information

SDS PODCAST EPISODE 110 ALPHAGO ZERO

SDS PODCAST EPISODE 110 ALPHAGO ZERO SDS PODCAST EPISODE 110 ALPHAGO ZERO Show Notes: http://www.superdatascience.com/110 1 Kirill: This is episode number 110, AlphaGo Zero. Welcome back ladies and gentlemen to the SuperDataSceince podcast.

More information

The Future of Artificial Intelligence

The Future of Artificial Intelligence The Future of Artificial Intelligence Murray Shanahan Dept. of Computing Imperial College London What Is Artificial Intelligence? Artificial intelligence (AI) is the construction of computers and robots

More information

Data-Starved Artificial Intelligence

Data-Starved Artificial Intelligence Data-Starved Artificial Intelligence Data-Starved Artificial Intelligence This material is based upon work supported by the Assistant Secretary of Defense for Research and Engineering under Air Force Contract

More information

Game Playing: Adversarial Search. Chapter 5

Game Playing: Adversarial Search. Chapter 5 Game Playing: Adversarial Search Chapter 5 Outline Games Perfect play minimax search α β pruning Resource limits and approximate evaluation Games of chance Games of imperfect information Games vs. Search

More information

Applied Applied Artificial Intelligence - a (short) Silicon Valley appetizer

Applied Applied Artificial Intelligence - a (short) Silicon Valley appetizer Applied Applied Artificial Intelligence - a (short) Silicon Valley appetizer ATV tech Talk, 4. May, 2018 Martin Broch Pedersen Innovation Center Denmark, Silicon Valley Carlsberg turns to AI to help develop

More information

KÜNSTLICHE INTELLIGENZ JOBKILLER VON MORGEN?

KÜNSTLICHE INTELLIGENZ JOBKILLER VON MORGEN? KÜNSTLICHE INTELLIGENZ JOBKILLER VON MORGEN? Marc Stampfli https://www.linkedin.com/in/marcstampfli/ https://twitter.com/marc_stampfli E-Mail: mstampfli@nvidia.com INTELLIGENT ROBOTS AND SMART MACHINES

More information

The Roller-Coaster History of Artificial Intelligence and its Impact on the Practice of Law

The Roller-Coaster History of Artificial Intelligence and its Impact on the Practice of Law The Roller-Coaster History of Artificial Intelligence and its Impact on the Practice of Law Uniersity of Richmond Law School February 23, 2018 Sharon D. Nelson, Esq. & John W. Simek snelson@senseient.com;

More information

AI for Autonomous Ships Challenges in Design and Validation

AI for Autonomous Ships Challenges in Design and Validation VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD AI for Autonomous Ships Challenges in Design and Validation ISSAV 2018 Eetu Heikkilä Autonomous ships - activities in VTT Autonomous ship systems Unmanned engine

More information

Google DeepMind s AlphaGo vs. world Go champion Lee Sedol

Google DeepMind s AlphaGo vs. world Go champion Lee Sedol Google DeepMind s AlphaGo vs. world Go champion Lee Sedol Review of Nature paper: Mastering the game of Go with Deep Neural Networks & Tree Search Tapani Raiko Thanks to Antti Tarvainen for some slides

More information

AI in Tabletop Games. Team 13 Josh Charnetsky Zachary Koch CSE Professor Anita Wasilewska

AI in Tabletop Games. Team 13 Josh Charnetsky Zachary Koch CSE Professor Anita Wasilewska AI in Tabletop Games Team 13 Josh Charnetsky Zachary Koch CSE 352 - Professor Anita Wasilewska Works Cited Kurenkov, Andrey. a-brief-history-of-game-ai.png. 18 Apr. 2016, www.andreykurenkov.com/writing/a-brief-history-of-game-ai/

More information

*Please see course page for full description and additional details.

*Please see course page for full description and additional details. Course Title: Blockchain, Machine Learning, the Internet of Things, and More: Meet the New Technologies Shaping Our World Course Code: CS 02 Instructor: Saleem Mohamed Course Summary: If you live in Silicon

More information

Foundations of Artificial Intelligence Introduction State of the Art Summary. classification: Board Games: Overview

Foundations of Artificial Intelligence Introduction State of the Art Summary. classification: Board Games: Overview Foundations of Artificial Intelligence May 14, 2018 40. Board Games: Introduction and State of the Art Foundations of Artificial Intelligence 40. Board Games: Introduction and State of the Art 40.1 Introduction

More information

Game Playing State-of-the-Art CSE 473: Artificial Intelligence Fall Deterministic Games. Zero-Sum Games 10/13/17. Adversarial Search

Game Playing State-of-the-Art CSE 473: Artificial Intelligence Fall Deterministic Games. Zero-Sum Games 10/13/17. Adversarial Search CSE 473: Artificial Intelligence Fall 2017 Adversarial Search Mini, pruning, Expecti Dieter Fox Based on slides adapted Luke Zettlemoyer, Dan Klein, Pieter Abbeel, Dan Weld, Stuart Russell or Andrew Moore

More information

ARGUING THE SAFETY OF MACHINE LEARNING FOR HIGHLY AUTOMATED DRIVING USING ASSURANCE CASES LYDIA GAUERHOF BOSCH CORPORATE RESEARCH

ARGUING THE SAFETY OF MACHINE LEARNING FOR HIGHLY AUTOMATED DRIVING USING ASSURANCE CASES LYDIA GAUERHOF BOSCH CORPORATE RESEARCH ARGUING THE SAFETY OF MACHINE LEARNING FOR HIGHLY AUTOMATED DRIVING USING ASSURANCE CASES 14.12.2017 LYDIA GAUERHOF BOSCH CORPORATE RESEARCH Arguing Safety of Machine Learning for Highly Automated Driving

More information

CS6700: The Emergence of Intelligent Machines. Prof. Carla Gomes Prof. Bart Selman Cornell University

CS6700: The Emergence of Intelligent Machines. Prof. Carla Gomes Prof. Bart Selman Cornell University EMERGENCE OF INTELLIGENT MACHINES: CHALLENGES AND OPPORTUNITIES CS6700: The Emergence of Intelligent Machines Prof. Carla Gomes Prof. Bart Selman Cornell University Artificial Intelligence After a distinguished

More information

Artificial intelligence: past, present and future

Artificial intelligence: past, present and future Artificial intelligence: past, present and future Thomas Bolander, Associate Professor, DTU Compute Danske Ideer, 15 March 2017 Thomas Bolander, Danske Ideer, 15 Mar 2017 p. 1/21 A bit about myself Thomas

More information

COMP219: Artificial Intelligence. Lecture 2: AI Problems and Applications

COMP219: Artificial Intelligence. Lecture 2: AI Problems and Applications COMP219: Artificial Intelligence Lecture 2: AI Problems and Applications 1 Introduction Last time General module information Characterisation of AI and what it is about Today Overview of some common AI

More information

CIP 2018 Project Outline

CIP 2018 Project Outline Outline Technology Research TR_SUM_1 Summer 1 Jun 2018 31 Aug 2018 Engineering Computer Science 4. Name: Development of Artificial Intelligence Applications To develop Artificial Intelligence based models

More information

March 10, Greenbelt Road, Suite 400, Greenbelt, MD Tel: (301) Fax: (301)

March 10, Greenbelt Road, Suite 400, Greenbelt, MD Tel: (301) Fax: (301) Detection of High Risk Intersections Using Synthetic Machine Vision John Alesse, john.alesse.ctr@dot.gov Brian O Donnell, brian.odonnell.ctr@dot.gov Stinger Ghaffarian Technologies, Inc. Cambridge, Massachusetts

More information

Agents and Introduction to AI

Agents and Introduction to AI Agents and Introduction to AI CITS3001 Algorithms, Agents and Artificial Intelligence Tim French School of Computer Science and Software Engineering The University of Western Australia 2017, Semester 2

More information

Monte Carlo Tree Search

Monte Carlo Tree Search Monte Carlo Tree Search 1 By the end, you will know Why we use Monte Carlo Search Trees The pros and cons of MCTS How it is applied to Super Mario Brothers and Alpha Go 2 Outline I. Pre-MCTS Algorithms

More information

CS 380: ARTIFICIAL INTELLIGENCE MONTE CARLO SEARCH. Santiago Ontañón

CS 380: ARTIFICIAL INTELLIGENCE MONTE CARLO SEARCH. Santiago Ontañón CS 380: ARTIFICIAL INTELLIGENCE MONTE CARLO SEARCH Santiago Ontañón so367@drexel.edu Recall: Adversarial Search Idea: When there is only one agent in the world, we can solve problems using DFS, BFS, ID,

More information

All about Go, the ancient game in which AI bested a master 10 March 2016, by Youkyung Lee

All about Go, the ancient game in which AI bested a master 10 March 2016, by Youkyung Lee All about Go, the ancient game in which AI bested a master 10 March 2016, by Youkyung Lee WHAT IS GO? In Go, also known as baduk in Korean and weiqi in Chinese, two players take turns putting black or

More information

CMSC 671 Project Report- Google AI Challenge: Planet Wars

CMSC 671 Project Report- Google AI Challenge: Planet Wars 1. Introduction Purpose The purpose of the project is to apply relevant AI techniques learned during the course with a view to develop an intelligent game playing bot for the game of Planet Wars. Planet

More information

Synergies Between Symbolic and Sub-symbolic Artificial Intelligence

Synergies Between Symbolic and Sub-symbolic Artificial Intelligence Synergies Between Symbolic and Sub-symbolic Artificial Intelligence Thomas Bolander, Associate Professor, DTU Compute Current Trends in AI, 23 November 2016 Thomas Bolander, Current Trends in AI, 23 November

More information

CS 188: Artificial Intelligence

CS 188: Artificial Intelligence CS 188: Artificial Intelligence Adversarial Search Prof. Scott Niekum The University of Texas at Austin [These slides are based on those of Dan Klein and Pieter Abbeel for CS188 Intro to AI at UC Berkeley.

More information

Transer Learning : Super Intelligence

Transer Learning : Super Intelligence Transer Learning : Super Intelligence GIS Group Dr Narayan Panigrahi, MA Rajesh, Shibumon Alampatta, Rakesh K P of Centre for AI and Robotics, Defence Research and Development Organization, C V Raman Nagar,

More information

TTIC 31230, Fundamentals of Deep Learning David McAllester, April AlphaZero

TTIC 31230, Fundamentals of Deep Learning David McAllester, April AlphaZero TTIC 31230, Fundamentals of Deep Learning David McAllester, April 2017 AlphaZero 1 AlphaGo Fan (October 2015) AlphaGo Defeats Fan Hui, European Go Champion. 2 AlphaGo Lee (March 2016) 3 AlphaGo Zero vs.

More information

LONDON S BEST BUSINESS MINDS TO COMPETE FOR PRESTIGIOUS CHESS TITLE

LONDON S BEST BUSINESS MINDS TO COMPETE FOR PRESTIGIOUS CHESS TITLE PRESS RELEASE LONDON S BEST BUSINESS MINDS TO COMPETE FOR PRESTIGIOUS CHESS TITLE - London s business elite to compete alongside world s best chess players in the London Chess Classic Pro-Biz Cup 2017

More information

What we are expecting from this presentation:

What we are expecting from this presentation: What we are expecting from this presentation: A We want to inform you on the most important highlights from this topic D We exhort you to share with us a constructive feedback for further improvements

More information

COMP219: Artificial Intelligence. Lecture 13: Game Playing

COMP219: Artificial Intelligence. Lecture 13: Game Playing CMP219: Artificial Intelligence Lecture 13: Game Playing 1 verview Last time Search with partial/no observations Belief states Incremental belief state search Determinism vs non-determinism Today We will

More information

The Principles Of A.I Alphago

The Principles Of A.I Alphago The Principles Of A.I Alphago YinChen Wu Dr. Hubert Bray Duke Summer Session 20 july 2017 Introduction Go, a traditional Chinese board game, is a remarkable work of art which has been invented for more

More information

CSC 550: Introduction to Artificial Intelligence. Fall 2004

CSC 550: Introduction to Artificial Intelligence. Fall 2004 CSC 550: Introduction to Artificial Intelligence Fall 2004 See online syllabus at: http://www.creighton.edu/~davereed/csc550 Course goals: survey the field of Artificial Intelligence, including major areas

More information

Game-playing: DeepBlue and AlphaGo

Game-playing: DeepBlue and AlphaGo Game-playing: DeepBlue and AlphaGo Brief history of gameplaying frontiers 1990s: Othello world champions refuse to play computers 1994: Chinook defeats Checkers world champion 1997: DeepBlue defeats world

More information

Industry 4.0 The Future of Innovation

Industry 4.0 The Future of Innovation Industry 4.0 The Future of Innovation Peter Merrill Chair; ASQ Innovation Think Tank www.petermerrill.com Why Innovation? Global Change Digitization Market Change Social Change Perfect Storm of Change

More information

LONDON S BEST BUSINESS MINDS TO COMPETE FOR PRESTIGIOUS CHESS TITLE

LONDON S BEST BUSINESS MINDS TO COMPETE FOR PRESTIGIOUS CHESS TITLE PRESS RELEASE LONDON S BEST BUSINESS MINDS TO COMPETE FOR PRESTIGIOUS CHESS TITLE - London s business elite to compete alongside world s best chess players in the London Chess Classic Pro-Biz Cup 2017

More information

My AI in Peace Machine

My AI in Peace Machine My AI in Peace Machine Timo Honkela University of Helsinki Finland MyData Conference Helsinki, FI, Aug 31, 2018 Personal timeline Born 1962 Mother died 1971 Quest for understanding MSc studies on human

More information

Recent developments in artificial intelligence: Deep learning & neural networks

Recent developments in artificial intelligence: Deep learning & neural networks 1 Recent developments in artificial intelligence: Deep learning & neural networks Lambert Schomaker Artificial Intelligence & Cognitive Engineering Institute Center for Data Science & Systems Complexity

More information

Adversarial Search Lecture 7

Adversarial Search Lecture 7 Lecture 7 How can we use search to plan ahead when other agents are planning against us? 1 Agenda Games: context, history Searching via Minimax Scaling α β pruning Depth-limiting Evaluation functions Handling

More information

Artificial Intelligence

Artificial Intelligence Artificial Intelligence One way to define Artificial Intelligence (AI) is as a branch of science trying to determine and formally describe, permitting a computer implementation the solutions for hard problems.

More information

CS 380: ARTIFICIAL INTELLIGENCE

CS 380: ARTIFICIAL INTELLIGENCE CS 380: ARTIFICIAL INTELLIGENCE ADVERSARIAL SEARCH 10/23/2013 Santiago Ontañón santi@cs.drexel.edu https://www.cs.drexel.edu/~santi/teaching/2013/cs380/intro.html Recall: Problem Solving Idea: represent

More information

Artificial Intelligence

Artificial Intelligence Artificial Intelligence Lecture 01 - Introduction Edirlei Soares de Lima What is Artificial Intelligence? Artificial intelligence is about making computers able to perform the

More information

AlphaGo and Artificial Intelligence GUEST LECTURE IN THE GAME OF GO AND SOCIETY

AlphaGo and Artificial Intelligence GUEST LECTURE IN THE GAME OF GO AND SOCIETY AlphaGo and Artificial Intelligence HUCK BENNET T (NORTHWESTERN UNIVERSITY) GUEST LECTURE IN THE GAME OF GO AND SOCIETY AT OCCIDENTAL COLLEGE, 10/29/2018 The Game of Go A game for aliens, presidents, and

More information

Human-like Computing: Call for feasibility studies

Human-like Computing: Call for feasibility studies Human-like Computing: Call for feasibility studies Call type: Invitation for proposals Closing date: 16 June 2017 Funding Available: 2 million is available to fund approximately 6 feasibility studies of

More information

Machine Learning has been used in the real estate industry much longer than headlines and pitch decks suggest

Machine Learning has been used in the real estate industry much longer than headlines and pitch decks suggest REGRESSION MODELING & MACHINE LEARNING: SEPARATING FACT FROM HYPE EXECUTIVE SUMMARY Machine Learning has been used in the real estate industry much longer than headlines and pitch decks suggest The McKinsey

More information

The Evolution of Artificial Intelligence in Workplaces

The Evolution of Artificial Intelligence in Workplaces The Evolution of Artificial Intelligence in Workplaces Cognitive Hubs for Future Workplaces In the last decade, workplaces have started to evolve towards digitalization. In the future, people will work

More information

Artificial Intelligence Adversarial Search

Artificial Intelligence Adversarial Search Artificial Intelligence Adversarial Search Adversarial Search Adversarial search problems games They occur in multiagent competitive environments There is an opponent we can t control planning again us!

More information

CSC321 Lecture 23: Go

CSC321 Lecture 23: Go CSC321 Lecture 23: Go Roger Grosse Roger Grosse CSC321 Lecture 23: Go 1 / 21 Final Exam Friday, April 20, 9am-noon Last names A Y: Clara Benson Building (BN) 2N Last names Z: Clara Benson Building (BN)

More information

ADAS Development using Advanced Real-Time All-in-the-Loop Simulators. Roberto De Vecchi VI-grade Enrico Busto - AddFor

ADAS Development using Advanced Real-Time All-in-the-Loop Simulators. Roberto De Vecchi VI-grade Enrico Busto - AddFor ADAS Development using Advanced Real-Time All-in-the-Loop Simulators Roberto De Vecchi VI-grade Enrico Busto - AddFor The Scenario The introduction of ADAS and AV has created completely new challenges

More information

The Intelligent Computer. Winston, Chapter 1

The Intelligent Computer. Winston, Chapter 1 The Intelligent Computer Winston, Chapter 1 Michael Eisenberg and Gerhard Fischer TA: Ann Eisenberg AI Course, Fall 1997 Eisenberg/Fischer 1 AI Course, Fall97 Artificial Intelligence engineering goal:

More information

Technology trends in the digitalization era. ANSYS Innovation Conference Bologna, Italy June 13, 2018 Michele Frascaroli Technical Director, CRIT Srl

Technology trends in the digitalization era. ANSYS Innovation Conference Bologna, Italy June 13, 2018 Michele Frascaroli Technical Director, CRIT Srl Technology trends in the digitalization era ANSYS Innovation Conference Bologna, Italy June 13, 2018 Michele Frascaroli Technical Director, CRIT Srl Summary About CRIT Top Trends for Emerging Technologies

More information

CS 380: ARTIFICIAL INTELLIGENCE ADVERSARIAL SEARCH. Santiago Ontañón

CS 380: ARTIFICIAL INTELLIGENCE ADVERSARIAL SEARCH. Santiago Ontañón CS 380: ARTIFICIAL INTELLIGENCE ADVERSARIAL SEARCH Santiago Ontañón so367@drexel.edu Recall: Problem Solving Idea: represent the problem we want to solve as: State space Actions Goal check Cost function

More information

Adversarial Search. Human-aware Robotics. 2018/01/25 Chapter 5 in R&N 3rd Ø Announcement: Slides for this lecture are here:

Adversarial Search. Human-aware Robotics. 2018/01/25 Chapter 5 in R&N 3rd Ø Announcement: Slides for this lecture are here: Adversarial Search 2018/01/25 Chapter 5 in R&N 3rd Ø Announcement: q Slides for this lecture are here: http://www.public.asu.edu/~yzhan442/teaching/cse471/lectures/adversarial.pdf Slides are largely based

More information

THE DEEP WATERS OF DEEP LEARNING

THE DEEP WATERS OF DEEP LEARNING THE DEEP WATERS OF DEEP LEARNING THE CURRENT AND FUTURE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE PUBLISHING INDUSTRY. BY AND FRANKFURTER BUCHMESSE 2/6 Given the ever increasing number of publishers exploring

More information

COMP219: COMP219: Artificial Intelligence Artificial Intelligence Dr. Annabel Latham Lecture 12: Game Playing Overview Games and Search

COMP219: COMP219: Artificial Intelligence Artificial Intelligence Dr. Annabel Latham Lecture 12: Game Playing Overview Games and Search COMP19: Artificial Intelligence COMP19: Artificial Intelligence Dr. Annabel Latham Room.05 Ashton Building Department of Computer Science University of Liverpool Lecture 1: Game Playing 1 Overview Last

More information

A.I. and Translation. iflytek Research : Gao Jianqing

A.I. and Translation. iflytek Research : Gao Jianqing A.I. and Translation iflytek Research : Gao Jianqing 11-2017 1. Introduction of iflytek and A.I. 2. Application of A.I. in Translation Company Overview Founded in 1999 A leading IT Enterprise in China

More information

Overview: Emerging Technologies and Issues

Overview: Emerging Technologies and Issues Overview: Emerging Technologies and Issues Marie Sicat Introduction to the Course on Digital Commerce and Emerging Technologies DiploFoundation, UNCTAD, CUTS, ITC, GIP UNCTAD E-commerce Week (18 April

More information

Game Playing. Philipp Koehn. 29 September 2015

Game Playing. Philipp Koehn. 29 September 2015 Game Playing Philipp Koehn 29 September 2015 Outline 1 Games Perfect play minimax decisions α β pruning Resource limits and approximate evaluation Games of chance Games of imperfect information 2 games

More information

AI powering Corporate Communications

AI powering Corporate Communications AI powering Corporate Communications Media Analysis & Insights December 2018 HUMANS MEET AI Artificial intelligence (AI) is the ability of computers to understand certain aspects of the natural world,

More information

What is Artificial Intelligence? Alternate Definitions (Russell + Norvig) Human intelligence

What is Artificial Intelligence? Alternate Definitions (Russell + Norvig) Human intelligence CSE 3401: Intro to Artificial Intelligence & Logic Programming Introduction Required Readings: Russell & Norvig Chapters 1 & 2. Lecture slides adapted from those of Fahiem Bacchus. What is AI? What is

More information

6. Games. COMP9414/ 9814/ 3411: Artificial Intelligence. Outline. Mechanical Turk. Origins. origins. motivation. minimax search

6. Games. COMP9414/ 9814/ 3411: Artificial Intelligence. Outline. Mechanical Turk. Origins. origins. motivation. minimax search COMP9414/9814/3411 16s1 Games 1 COMP9414/ 9814/ 3411: Artificial Intelligence 6. Games Outline origins motivation Russell & Norvig, Chapter 5. minimax search resource limits and heuristic evaluation α-β

More information

The potential of Artificial Intelligence in academic research at a Digital University

The potential of Artificial Intelligence in academic research at a Digital University Alexander Rossmann, Alfred Zimmermann (eds.): Digital Enterprise Computing 2017 Lecture Notes in Informatics (LNI), Gesellschaft für Informatik, Bonn 2017 61 The potential of Artificial Intelligence in

More information

The future of work. Nav Singh Managing Partner, Boston McKinsey & Company

The future of work. Nav Singh Managing Partner, Boston McKinsey & Company The future of work Nav Singh Managing Partner, Boston Since the Industrial Revolution, innovation has fueled economic growth Estimated global GDP per capita, $ 100,000 1st Industrial Revolution 2 nd Industrial

More information

A Roadmap for Connected & Autonomous Vehicles. David Skipp Ford Motor Company

A Roadmap for Connected & Autonomous Vehicles. David Skipp Ford Motor Company A Roadmap for Connected & Autonomous Vehicles David Skipp Ford Motor Company ! Why does an Autonomous Vehicle need a roadmap? Where might the roadmap take us? What should we focus on next? Why does an

More information

THE AI REVOLUTION. How Artificial Intelligence is Redefining Marketing Automation

THE AI REVOLUTION. How Artificial Intelligence is Redefining Marketing Automation THE AI REVOLUTION How Artificial Intelligence is Redefining Marketing Automation The implications of Artificial Intelligence for modern day marketers The shift from Marketing Automation to Intelligent

More information

3 rd December AI at arago. The Impact of Intelligent Automation on the Blue Chip Economy

3 rd December AI at arago. The Impact of Intelligent Automation on the Blue Chip Economy Hans-Christian AI AT ARAGO Chris Boos @boosc 3 rd December 2015 AI at arago The Impact of Intelligent Automation on the Blue Chip Economy From Industry to Technology AI at arago AI AT ARAGO The Economic

More information

Embedding Artificial Intelligence into Our Lives

Embedding Artificial Intelligence into Our Lives Embedding Artificial Intelligence into Our Lives Michael Thompson, Synopsys D&R IP-SOC DAYS Santa Clara April 2018 1 Agenda Introduction What AI is and is Not Where AI is being used Rapid Advance of AI

More information

Computer Go: from the Beginnings to AlphaGo. Martin Müller, University of Alberta

Computer Go: from the Beginnings to AlphaGo. Martin Müller, University of Alberta Computer Go: from the Beginnings to AlphaGo Martin Müller, University of Alberta 2017 Outline of the Talk Game of Go Short history - Computer Go from the beginnings to AlphaGo The science behind AlphaGo

More information

Lessons learned & Future of FeedMAP

Lessons learned & Future of FeedMAP Lessons learned & Future of FeedMAP Final Workshop 6.10.2008 Trento, Italy Hans-Ulrich Otto Tele Atlas NV Lessons learned - FeedMAP in-vehicle client Positional accuracy of GPS receivers differs up to

More information

Random Administrivia. In CMC 306 on Monday for LISP lab

Random Administrivia. In CMC 306 on Monday for LISP lab Random Administrivia In CMC 306 on Monday for LISP lab Artificial Intelligence: Introduction What IS artificial intelligence? Examples of intelligent behavior: Definitions of AI There are as many definitions

More information

Jeff Bezos, CEO and Founder Amazon

Jeff Bezos, CEO and Founder Amazon Jeff Bezos, CEO and Founder Amazon Artificial Intelligence and Machine Learning... will empower and improve every business, every government organization, every philanthropy there is not an institution

More information

Outline. Introduction to AI. Artificial Intelligence. What is an AI? What is an AI? Agents Environments

Outline. Introduction to AI. Artificial Intelligence. What is an AI? What is an AI? Agents Environments Outline Introduction to AI ECE457 Applied Artificial Intelligence Fall 2007 Lecture #1 What is an AI? Russell & Norvig, chapter 1 Agents s Russell & Norvig, chapter 2 ECE457 Applied Artificial Intelligence

More information

Foundations of Artificial Intelligence

Foundations of Artificial Intelligence Foundations of Artificial Intelligence 6. Board Games Search Strategies for Games, Games with Chance, State of the Art Joschka Boedecker and Wolfram Burgard and Bernhard Nebel Albert-Ludwigs-Universität

More information

CMSC 372 Artificial Intelligence. Fall Administrivia

CMSC 372 Artificial Intelligence. Fall Administrivia CMSC 372 Artificial Intelligence Fall 2017 Administrivia Instructor: Deepak Kumar Lectures: Mon& Wed 10:10a to 11:30a Labs: Fridays 10:10a to 11:30a Pre requisites: CMSC B206 or H106 and CMSC B231 or permission

More information

ARTIFICIAL INTELLIGENCE

ARTIFICIAL INTELLIGENCE BABEŞ-BOLYAI UNIVERSITY Faculty of Computer Science and Mathematics ARTIFICIAL INTELLIGENCE Introduction Summary Short questions about AI History of AI Applications of AI 2 Short questions about AI What

More information

Success Stories of Deep RL. David Silver

Success Stories of Deep RL. David Silver Success Stories of Deep RL David Silver Reinforcement Learning (RL) RL is a general-purpose framework for decision-making An agent selects actions Its actions influence its future observations Success

More information

No. Crt Topic Titlte Topic Description Competence Area

No. Crt Topic Titlte Topic Description Competence Area No. Crt Topic Titlte Topic Description Competence Area Real-time intersection manager according to current traffic. Vehicles will transmit their planned route to the central intersection manager, outside

More information

Foundations of Artificial Intelligence

Foundations of Artificial Intelligence Foundations of Artificial Intelligence 6. Board Games Search Strategies for Games, Games with Chance, State of the Art Joschka Boedecker and Wolfram Burgard and Frank Hutter and Bernhard Nebel Albert-Ludwigs-Universität

More information

Quick work: Memory allocation

Quick work: Memory allocation Quick work: Memory allocation The OS is using a fixed partition algorithm. Processes place requests to the OS in the following sequence: P1=15 KB, P2=5 KB, P3=30 KB Draw the memory map at the end, if each

More information

The 2018 Publishing Landscape: Technological Horizons. Lyndsey Dixon Editorial Director, APAC Journals Taylor & Francis Group

The 2018 Publishing Landscape: Technological Horizons. Lyndsey Dixon Editorial Director, APAC Journals Taylor & Francis Group The 2018 Publishing Landscape: Technological Horizons Lyndsey Dixon Editorial Director, APAC Journals Taylor & Francis Group Today Waves of innovation Publishing advancements through innovation Artificial

More information

Game playing. Outline

Game playing. Outline Game playing Chapter 6, Sections 1 8 CS 480 Outline Perfect play Resource limits α β pruning Games of chance Games of imperfect information Games vs. search problems Unpredictable opponent solution is

More information

The game of Bridge: a challenge for ILP

The game of Bridge: a challenge for ILP The game of Bridge: a challenge for ILP S. Legras, C. Rouveirol, V. Ventos Véronique Ventos LRI Univ Paris-Saclay vventos@nukk.ai 1 Games 2 Interest of games for AI Excellent field of experimentation Problems

More information

Where does Design add Value in a Tech Start-up? DMI Boston Conference Sept 28th, 2015

Where does Design add Value in a Tech Start-up? DMI Boston Conference Sept 28th, 2015 Where does Design add Value in a Tech Start-up? DMI Boston Conference Sept 28th, 2015 gulayozkan.com @gulayozkan GEDS is a design and innovation studio that uses design-driven methods to connect organizations

More information

Artificial Intelligence. Shobhanjana Kalita Dept. of Computer Science & Engineering Tezpur University

Artificial Intelligence. Shobhanjana Kalita Dept. of Computer Science & Engineering Tezpur University Artificial Intelligence Shobhanjana Kalita Dept. of Computer Science & Engineering Tezpur University What is AI? What is Intelligence? The ability to acquire and apply knowledge and skills (definition

More information

AI in Business Enterprises

AI in Business Enterprises AI in Business Enterprises Are Humans Rational? Rini Palitmittam 10 th October 2017 Image Courtesy: Google Images Founders of Modern Artificial Intelligence Image Courtesy: Google Images Founders of Modern

More information

CPS 570: Artificial Intelligence Two-player, zero-sum, perfect-information Games

CPS 570: Artificial Intelligence Two-player, zero-sum, perfect-information Games CPS 57: Artificial Intelligence Two-player, zero-sum, perfect-information Games Instructor: Vincent Conitzer Game playing Rich tradition of creating game-playing programs in AI Many similarities to search

More information

Dr George Gillespie. CEO HORIBA MIRA Ltd. Sponsors

Dr George Gillespie. CEO HORIBA MIRA Ltd. Sponsors Dr George Gillespie CEO HORIBA MIRA Ltd Sponsors Intelligent Connected Vehicle Roadmap George Gillespie September 2017 www.automotivecouncil.co.uk ICV Roadmap built on Travellers Needs study plus extensive

More information

URI Imagine the Future

URI Imagine the Future URI 2035 Imagine the Future 1 Our hope Informative Stimulating Fun 2 We also hope to identify a path to continue the futures dialog at URI beyond the Summit second breakout 3 Outline Imagining the future

More information

Game playing. Chapter 6. Chapter 6 1

Game playing. Chapter 6. Chapter 6 1 Game playing Chapter 6 Chapter 6 1 Outline Games Perfect play minimax decisions α β pruning Resource limits and approximate evaluation Games of chance Games of imperfect information Chapter 6 2 Games vs.

More information

FORESIGHT METHOD HORIZONS. Module. Introduction to Foresight for Canada Beyond 150

FORESIGHT METHOD HORIZONS. Module. Introduction to Foresight for Canada Beyond 150 HORIZONS FORESIGHT METHOD for Canada Beyond 50 OVERVIEW Where are we in the process? What is Horizons approach to foresight? How do the foresight tools fit together for Canada Beyond 50? 2 A NEW MODEL

More information

THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN SPEECH RECOGNITION. A CS Approach By Uniphore Software Systems

THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN SPEECH RECOGNITION. A CS Approach By Uniphore Software Systems THE USE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN SPEECH RECOGNITION A CS Approach By Uniphore Software Systems Communicating with machines something that was near unthinkable in the past is today

More information

AUTOMATION ACROSS THE ENTERPRISE

AUTOMATION ACROSS THE ENTERPRISE AUTOMATION ACROSS THE ENTERPRISE WHAT WILL YOU LEARN? What is Ansible Tower How Ansible Tower Works Installing Ansible Tower Key Features WHAT IS ANSIBLE TOWER? Ansible Tower is a UI and RESTful API allowing

More information

Simulationbased Development of ADAS and Automated Driving with the Help of Machine Learning

Simulationbased Development of ADAS and Automated Driving with the Help of Machine Learning Simulationbased Development of ADAS and Automated Driving with the Help of Machine Learning Dr. Andreas Kuhn A N D A T A München, 2017-06-27 2 Fields of Competence Artificial Intelligence Data Mining Big

More information

For personal use only

For personal use only 30 June 2016 BrainChip Acquires French based Computer Vision Technology Company Spikenet Technology BrainChip Holdings Limited ( BrainChip ) is pleased to advise that it has signed a binding term sheet

More information

VSI Labs The Build Up of Automated Driving

VSI Labs The Build Up of Automated Driving VSI Labs The Build Up of Automated Driving October - 2017 Agenda Opening Remarks Introduction and Background Customers Solutions VSI Labs Some Industry Content Opening Remarks Automated vehicle systems

More information

CSE 473: Artificial Intelligence. Outline

CSE 473: Artificial Intelligence. Outline CSE 473: Artificial Intelligence Adversarial Search Dan Weld Based on slides from Dan Klein, Stuart Russell, Pieter Abbeel, Andrew Moore and Luke Zettlemoyer (best illustrations from ai.berkeley.edu) 1

More information

WorldSkills UK Construction Roundtable Report: The future of construction is manufacturing June 2018

WorldSkills UK Construction Roundtable Report: The future of construction is manufacturing June 2018 WorldSkills UK Construction Roundtable Report: The future of construction is manufacturing June 2018 Introduction This roundtable event was conceived out of a need to develop a future-facing perspective

More information

What is AI? AI is the reproduction of human reasoning and intelligent behavior by computational methods. an attempt of. Intelligent behavior Computer

What is AI? AI is the reproduction of human reasoning and intelligent behavior by computational methods. an attempt of. Intelligent behavior Computer What is AI? an attempt of AI is the reproduction of human reasoning and intelligent behavior by computational methods Intelligent behavior Computer Humans 1 What is AI? (R&N) Discipline that systematizes

More information

The Future Reinvented: Radical Energy Solutions

The Future Reinvented: Radical Energy Solutions The Future Reinvented: Radical Energy Solutions An Interactive Scenario & Storytelling Workshop 13 th June 2018 ENERGIZING FUTURES Sustainable Development and Energy in Transition Tampere, Finland Fast

More information