Computing: A Vision For The Future Gaining a digital transformation edge through cognitive technologies

Transcription

1 Computing: A Vision For The Future Gaining a digital transformation edge through cognitive technologies A cognitive business is a thinking business! William Carbone williamcarbone@sk.ibm.com Bratislava,

2 William leads Cognitive Solutions for IBM in CEE. William is among the most exceptional IBMers appointed with the rare distinction of IBM Academy of Technology member. Top 100 technical leaders providing the direction of IBM with innovation that matters. William is also the Chairman of the Technical Experts Council for Slovakia and Czech Republic, focusing on innovation, patenting, research and state-of-the-art technologies and fostering the technical eminence of young talents/experts in the region. William Carbone Cognitive Solutions and Watson Leader Continuous Innovation Advocate Chairman of TEC CZ SK 2

3

4 Alan Turing English mathematician, computer scientist, logician, cryptanalyst, philosopher, and theoretical biologist. Turing was highly influential in the development of theoretical computer science, providing a formalization of the concepts of algorithm and computation with the Turing machine, which can be considered a model of a general-purpose computer. Turing is widely considered to be the father of theoretical computer science and artificial intelligence!

5

6 A (brief) history of computing by William Carbone

7 Biases Amero-Euro centric Computer Science centric Google centric I have taken a Computer science centric approach, focusing on things that Computer scientists themselves find important.

8 Counting is hard The Human Brain Abacus Numerals Ancient Origins

9 The 1700 s and 1800 s Computing as a job Moved beyond governmental in a big way Industries now need large pools of computing power Scientific inquiry requires more brainpower and number crunching Inventions Pascal s wheel Slide rules Napeir s bones Jacquard s loom programmable!

10 Babbage and Lovelace Charles Babbage Math professor at Trinity College in Cambridge Difference engine Analytical engine Mill and store (CPU and memory) Ada Augusta, Countess of Lovelace Amazing mathematician, helped Babbage first programmer

11 Hollerith and the Census U.S. needed help with the 1890 census Dr. Herman Hollerith, statistician and inventor was hired to help Took punch cards from the Jacquard loom and turned it into a punch card database! Cut down the census tabulation by 6 years (from 8 to 2) saving millions Founds company that would become IBM Production of punch-card machines and mechanical calculators

12 Electricity and Binary Konrad Zuse Civil engineer you can say I was too lazy to calculate so I invented the computer Created the Z1 using binary and electrical circuits Drafted into German military for WWII, but was soon hired to build the Z2 Saw the use of vacuum tubes for faster computing, but calculated it would take too long to implement.

13 Learning to love the Bombe Alan Turing Hired by England to crack codes set by the enigma machine (the bombe) Electrical machine using logical operators to brute force a solution to enigma settings Turing machines Turing test and AI

14 Artillery and vacuum tubes ENIAC (Electronic Numerical Integrator And Computer) Artillery and bombing tables took too long Military hired Dr. Presper Eckert and Dr. John Mauchly for a solution Began in 1943, announced in 1946, cost $500,000, weighed roughly 30 tons, required 18k vacuum tubes! Was thought impossible, too unreliable Programmed by wire

15 Transistors and the UNIVAC Transistors came about from research at AT&T s Bell Labs and was the work of Berdeen, Brattain, and Shockley was a smaller, faster, safer, cheaper and more reliable version of the vacuum tube 1950 s census is taking too long, the census needs help again Hires the makers of the ENIAC to take advantage of the transistor. The result is the UNIVAC I, which predicts the 1952 presidential election, shocking all with Eisenhower s victory

16 Languages! With the success of the UNIVAC and other large computers, more people are taking advantage of them. Programming these computers is tough stuff either it s binary or assembly coding FORTRAN (Formula Translation) (John Backus, 1954) comes about the help mathematicians. One of the first high level languages COBOL (Common Business-oriented Language) ( Grace Hopper 1959) comes about to help businesses program.

17 ERMA and MICr 1955, Bank of America announces its latest project with the Stanford Research Institute: ERMA the Electronic Record Method of Accounting Seeks to revolutionize the banking industry with raw computing power ERMA comes equipped with MICR (Magnetic Ink Character Recognition) allows computers to read checks and changes the consumer experience forever.

18 Integrated circuits and the space race The Tyranny of Numbers Seeking to miniaturize transistors, Jock Kilby and Robert Noyce separately come upon the Integrated circuit Combines transistors, resistors, capacitors, and all the wiring onto a single chip of semiconductor material Smaller, safer, faster, more reliable, easier to make, but more expensive Wasn t until the manned mission to the moon that they were put into use on a large scale (1960ish)

19 Mice and folders Much like computer programming, computer interfaces are designed for and by a specialized group. All interaction is either physical or text. A wider group of individuals were using computers (they were getting smaller and more prevalent), they required a very specific skill sets to use. Machine interaction becomes a field of study Doug Engelbart invents mouse, uses it in conjunction with one of the first GUI s (1964) Not the first interactive tool, but one that stuck around along with the office metaphor (files, folders, projects, desktops)

20 The internet and global thermonuclear war 1969 ARPAnet, links computers with a standard protocol for the flow of information. Started with 4 university computers, grew quickly in both size and structure Innovations included: , telnet (remote computing), and FTP (file transfer protocol). As it became larger, became unsafe for strictly military applications (MILnet) Spawned Local Area Networks (LAN s) NSFnet (National Science Foundation network) starts as a LAN, branches out to connect other LAN s (1986), starts to replace ARPAnet (closed 1990) for universities, evolves into the current internet.

21 Ramming speed! And microprocessors The integrated circuit improves processing speed so much that memory speed (especially for nonsequential memory) becomes an issue. In 1970, Intel comes out with the first Dynamic Random Access Memory (DRAM) RAM had been around since 1947, this makes it smaller and faster, mass marketed Fredrico Faggin at Intel designs the first microprocessor, thus completing all of the hardware components necessary for the personal computer

22 Smalltalk and objects 1960 s and 70 s saw the rise of many new programming languages including BASIC, C (what comes after B), Pascal, and Smalltalk Smalltalk is one of the most influential object oriented languages, based on the ideas of encapsulation, message passing, and modular programming. Revolutionized how computer programs were written.

23 Donald Knuth Often called the Father of Computer Science As a child he won an anagram competition for Ziegler's Giant Bar, finding over 4,500 words that could be made out of those letters (2,000 more than the judges of the competition had found) Barely chose physics over music as a major at Case Institute of Technology Wrote: The Art of Computer Programming a guide to programming algorithms and their analysis that helped set computer science apart form other disciplines.

24

25 26

26 IBM Research Definition of AI Artificial Intelligence (AI) has a long history at IBM Research, dating back to the 1950s. By AI we mean anything that makes machines act more intelligently. Our work includes basic and applied research in machine learning, deep question answering, search and planning, knowledge representation, and cognitive architectures International Business Machines Corporation

27 Famous applications of AI at IBM Deep Blue Watson In 1997, the IBM chess-playing computer named Deep Blue beat World Chess Champion Garry In 2011, the IBM Jeopardy!-playing computer named Watson beat Ken Jennings and Brad Rutter in a grand 1997 Kasparov in a sixgame match. challenge. champion 2011

28 Augmented Intelligence Augmented Intelligence Human Intelligence AI Solution

29 Ethical Challenges AI, like most other technology tools, is most effective when it is used to extend the natural capabilities of humans instead of replacing them. That means that AI and humans are best when they work together and can trust each other. - Rob High, CTO IBM Watson Among the many ethical issues are: Trust Privacy 2018 International Business Machines Corporation

30 Cognitive /ˈkɒɡ.nə.tɪv/ Connected with thinking or conscious mental processes

31 Cognitive Computing Artificial Intelligence Machine Learning

32 33 DATA

33 Disruption is upon us. The biggest taxi company owns no cars. The largest accommodation company owns no real estate. The largest retailer carries no inventory. The biggest media company owns no content.

34

35 Source:

36 This disruption is fueled by three forces. T h e p r o l i f e r a t i o n o f d i f f e r e n t t y p e s o f d a t a. T h e a b i l i t y t o b u i l d b u s i n e s s i n c o d e w i t h t h e A P I e c o n o m y. T h e p o w e r f u l c a p a b i l i t i e s a n d o u t c o m e s b r o u g h t o n b y c o g n i t i v e c o m p u t i n g.

37 Oil & Gas 80,000 sensors in a facility produce 15 petabytes of data Public Safety 520 terabytes of data are produced by New York City's surveillance cameras each day Energy & Utilities 680m+ smart meters will produce 280 petabytes of data by 2017 Healthcare The equivalent of 300 million books of health related data is produced per human in a lifetime

38 More devices are creating more information. 1,200,000 80, ,000,000 5,000,000 l i n e s o f c o d e i n a s m a r t p h o n e l i n e s o f c o d e i n a p a c e m a k e r l i n e s o f c o d e i n a n e w c a r l i n e s o f c o d e i n s m a r t a p p l i a n c e

39 Three capabilities differentiate cognitive systems from traditional programmed computing systems Understanding Cognitive systems understand like humans do. Reasoning They reason. They understand underlying ideas and concepts. They form hypothesis. They infer and extract concepts. Learning They never stop learning getting more valuable with time. Advancing with each new piece of information, interaction, and outcome. They develop expertise.. allowing them to interact with humans.

40

41 42

42 Gender Generation Income Level Age Education Costal vs Inland Marital status Location Legal status Sector Family Size ZIPcode Competitors Loyalty & Card Activity City Lifestyle Revenue Size Life Stages Industry Image source: 43

43 Subscriptions Gender Age Date on Site Following Generation Followers Income Level Wish List Eductation Size of Network Costal vs Inland Likes Marital status Time/Day log in Check-ins Location App usage duration Sector ZIPcode Number of Apps on Device Loyalty & Card Activity Deposits/Withdrawals Photos liked Lifestyle Videos Viewed Device Usage Life Stages Purchase History Legal status Number of Hashtags used Family Size Frequency of Search History of Hashtags Competitors Search Strings entered City Sequence of visits Revenue Size Time spent on site Industry Time spent on page Image source: 44

44 Size of Network Income Level Life Stages Sentiment Subscriptions Affective Status Euphemisms Hedonism ZIPcode Extroversion Deposits/Withdrawals Costal vs Inland Location App usage duration Sector Lifestyle Gender Wish List Age Check-ins Face Recognition Date on Site Number of Apps on Device Device Usage Openess Tone Question Analysis Loyalty & Card Activity Photos liked Videos Viewed Image source: Colloquialism Purchase History Following Generation Dialog Likes Family Size History of Hashtags Marital status Competitors Followers Eductation Linguistics Legal status Number of Hashtags used Self-transcendent Time spent on site City Language Modeling Reasoning Strategies Search Strings entered Sequence of visits Revenue Size Time spent on page Intent Phonemes Time/Day log in Image Tags Frequency of Search Latent Semantic Analysis Industry Ontology Analysis 45

45 Compassion Intuition Design Value Judgments Common Sense 46

46 Compassion Intuition Design Value Judgments Common Sense Deep Learning Discovery Large-scale math Fact checking 47

47 48 Human + Machine

48 New Information Technology challenge is now about the possibility to expand our WISDOM options Watson Toward a Precise Decision Making to reduce the wasteful spend as well as the risk in every industry

49 Cognitive systems forge a new partnership between man and machine. H u m a n s e x c e l a t : Common Sense Morals Imagination Compassion Abstraction Dilemmas Dreaming Generalization C o g n i t i ve S y s t e m s e x c e l a t : Locating Knowledge Pattern Identification Natural Language Machine Learning Eliminate Bias Endless Capacity

50 The price of not knowing IBM Corporation 51

51 The Journey to Wisdom Data Knowledge Information Wisdom Source:

52 Main Technology Shift Automating the World Understanding the World Program Knowledge Workers H-Factor Train Learning Workers

53 WISDOM Digitalization Mobile Social BIG DATA Analytics Data Science Cloud Computing DATA Technology Information Knowledge Technology is not only supporting every kind of private and public organizations, it is becoming part of them

54 What is the Goal of Digital Cognitive Systems? Artificial Intelligence = Machine Intelligence The Goal! Augmented Intelligence = Human Intelligence + Machine Intelligence Star Trek: Mr Data An individual smart machine VS Iron Man: Tony Stark & Jarvis Man and machine co-operation Capability to use language with machines for coordinating and reasoning for better outcomes. Increases human intelligence by use and not diminish it.

55 56

56

57 As the Watson technology evolves and deepens, so are the ways it s being put to work in the world. 20 Industries 45 Countries 50,000 Students in Melbourne 80K Developers building with Watson 500+ Partners Powered by Watson 1.1M Patients at Bumrungrad 8 Languages Learned by Watson 200 Universities offering Watson courses 5.5M Citizens in Singapore 5 8

58 Cognitive systems rely on collections of data and information: Data, information, and expertise create the foundation. Examples include: Analyst reports tweets Wire tap transcripts Battlefield docs s Texts Forensic reports Newspapers Blogs Wiki Court rulings International crime database Stolen vehicle data Missing persons data 5 9

59 and then leverage Watson APIs to apply cognitive capabilities. Compare and Comply 50 underlying technologies Entity Extraction Sentiment Analysis Emotion Analysis (Beta) Keyword Extraction Concept Tagging Taxonomy Classification Author Extraction Language Detection Text Extraction Microformats Parsing Feed Detection Linked Data Support Concept Expansion Concept Insights Dialog Document Conversion Language Translation Natural Language Classifier Personality insights Relationship Extraction Retrieve and Rank Tone Analyzer Emotive Speech to Text Text to Speech Face Detection Image Link Extraction Image Tagging Text Detection Visual Insights Visual Recognition AlchemyData News Tradeoff Analytics Natural Language Classifier Tone Analyzer 6 0

60 IBM Cloud Catalog Compute Containers Networking Storage AI Analytics Databases Developer Tools Integration Internet of Things Security and Identity Starter Kits Web and Mobile Web and Application Public Private Dedicated 2018 International Business Machines Corporation

61

62

63 IBM Cloud Computing Computing as a Service Software as a Service Platform as a Service Infrastructure as a Service Public Private Hybrid

64 IBM AI Cloud Products International Business Machines Corporation

65 2018 International Business Machines Corporation

66

67 2018 International Business Machines Corporation

68 IBM Solutions by Industry International Business Machines Corporation

69 AI and Design Thinking F.A.I.R. DT and AI as a means of Expanding Human Intelligence Observe Reflect Make 2018 International Business Machines Corporation

70 AI and Design Thinking DT and AI as a means of Expanding Human Intelligence 2018 International Business Machines Corporation Source:

71 What are your next steps to becoming a cognitive professional? 2018 International Business Machines Corporation

72 Badges Your fast track to cognitive computing International Business Machines Corporation

73 74 Welcome to the Cognitive Era

74 Thank you! William Carbone Cognitive Solutions and Watson Leader Chairman of TEC CZ SK IBM Academy of Technology Member 76

75 Useful links: Watson Academy: Cognitive Class (old Big Data Analytics University): IBM Cloud (Bluemix) documentation: IBM Watson Assistant: IBM Watson APIs: 77