IBM Technology Focus for the Next 10 Years

IBM Technology Focus for the Next 10 Years ADLUG Annual Meeting, Florence, Italy September 19 -21, 2012 Wolfgang Singer, Honorary Member of IBM IT-Specialist Community Singerw 2@gmail. com © 2012 International Business Machines Corporation

Intellectual Property and Standards USPTO Top 10 Patentees – 2011 IBM has the patent leadership for the 19 th consecutive year. Hundreds of patents donated. 2 IBM Patent Leadership © 2012 IBM Corporation

IBM Research: The World is Our Lab Dublin China Zurich Almaden Watson Haifa India Tokyo Austin Brazil Melbourne IBM Research labs Labs added since 2010 Other IBM Research presence © 2012 International Business Machines Corporation 3

Leading IBM: Eras of computing Computer Intelligence Cognitive Systems Era Programmable Systems Era Tabulating

Four Technologies that Will Change the World Cognitive Computing Compute+ Natural Language+ Analytics § “Synapse” devices Deep Q&A Computers BIG/Fast Data § § Exa / zettabytes Milli / microseconds Unstructured Noisy Data Exascale (Datacenter-in-a-box) § Massive parallelism § Flexible system optimization Workload Optimized Systems Nano Devices Nano Systems Power 7 chip (Systems-on-a-chip) § DNA Transistor § Nano Medicine 1 Trillion Devices 1 Billion Transistors 5 © 2012 IBM Corporation

From Nano Devices to Nano Systems Cognitive Computing Compute+ Natural Language+ Analytics § “Synapse” devices BIG/Fast Data Deep Q&A Computers § § Exa / zettabytes Milli / microseconds Unstructured Noisy Data Exascale (Datacenter-in-a-box) § Massive parallelism § Flexible system optimization Workload Optimized Systems Power 7 chip Nano Devices 1 Trillion Devices Nano Systems (Systems-on-a-chip) § DNA Transistor § Nano Medicine 1 Billion Transistors 6 © 2012 IBM Corporation

IBM Research - Zurich Nanotechnology – Everywhere Laser Etching Scratch resistive Lacquer Regenerative Medicine Nano-Pore Photovoltaics DNA Self-cleaning paints and Textiles DNA Sequencing Filtration und purification wri@zurich. ibm. com © 2012 IBM Corporation

Medicine at the Nanoscale DNA Transistor § Fast, cost-effective method to use genetic info in healthcare § DNA strands pass through ‘nanopore’ § Electric sensor reads genetic information Anti-bacterial Nanoparticles § Detects and destroys antibioticresistant bacteria § Fights infectious diseases § Biodegradable 8 13 © 2012 IBM Corporation

From Petascale to Exascale Cognitive Computing Compute+ Natural Language+ Analytics § “Synapse” devices BIG/Fast Data Deep Q&A Computers § § Exa / zettabytes Milli / microseconds Unstructured Noisy Data Exascale (Datacenter-in-a-box) § Massive parallelism § Flexible system optimization Workload Optimized Systems Power 7 chip Nano Devices Nano Systems (Systems-on-a-chip) § DNA Transistor § Nano Medicine 1 Trillion Devices 1 Billion Transistors 9 © 2012 IBM Corporation

Exascale Computing A billion calculations in a billionth of a second Overall Performance = 1000 X 1 Peta. Flop 72 BG/P Racks Performance / watt = 135 X Performance / $ = 1000 X Footprint = <2% Referenced to one-petaflop system CPU Software Phase Change Memory Silicon Photonics 3 D The Next Ten Years 1 Peta. Flop = 1/3 rack 2009 10 2019 15 © 2012 IBM Corporation

Progress in the Programmable Systems Era Scale up Scale out Scale in © 2012

A new paradigm for fast systems Switching Storage Memory Scale In Processor © 2012

Natural Disaster Prediction and Response Deep Thunder § 24 - to 48 -hour forecasts § 1 - 2 km resolution § 3 hours to 3 days lead time § Weather data coupled with analytics 13 17 © 2012 IBM Corporation

From Big Data to Big Analytics Cognitive Computing Compute+ Natural Language+ Analytics § “Synapse” devices BIG/Fast Data § Exa / zettabytes § Milli / microseconds § Unstructured § Noisy Deep Q&A Computers Data Exascale (Datacenter-in-a-box) § Massive parallelism § Flexible system optimization Workload Optimized Systems Power 7 chip Nano Devices Nano Systems (Systems-on-a-chip) § DNA Transistor § Nano Medicine 1 Trillion Devices 1 Billion Transistors © 2012 IBM Corporation 14

Big Data – Very Big and Very Fast § Merging real-time analytics with deep analytics § Meaning from text at record volumes and speed § Massive scale analytics with minimal code § Super fast indexing of thousands of facets § Optimized and integrated system Homeland Security 600 k records per second 50 billion per day 1 -2 milliseconds per decision 320 terabytes for Deep Analytics Telco Promotions 100 k records per second, 8 billion per day 10 milliseconds per decision 270 terabytes for Deep Analytics IBM Deep. QA 100 s of gigabytes for Deep Analytics 3 seconds per decision 15 © 2012 IBM Corporation

Big Data: Why we must move to a new era of computing Uncertain data on the rise Dimensions of data growth Volume in Exabytes 9000 8000 Sensors & Devices 7000 6000 Social Media Terabytes to exabytes of existing data to process Streaming data, milliseconds to respond Volume Velocity 5000 4000 3000 2010 © 2012 International Business Machines Corporation Vo. IP Enterprise Data 2015 Structured, Variety unstructured, text, multimedia Veracity Uncertainty from inconsistency, ambiguities, etc. 16

Uncertainty arises from many sources Process Uncertainty Data Uncertainty Model Uncertainty Processes contain “randomness” Data input is uncertain All modeling is approximate Actual Spelling Intended Spelling Text Entry ? ? ? Uncertain travel times Fitting a curve to data GPS Uncertainty ? Testimony ? ? {Paris Airport} Ambiguity Semiconductor yield © 2012 International Business Machines Corporation Contaminated? Rumors {John Smith, Dallas} {John Smith, Kansas} Conflicting Data Forecasting a hurricane (www. noaa. gov) 17 17

From Programming to Systems that Learn Cognitive Computing § “Synapse” devices Compute+ Natural Language+ Analytics BIG/Fast Data Deep Q&A Computers § § Exa / zettabytes Milli / microseconds Unstructured Noisy Data Exascale (Datacenter-in-a-box) § Massive parallelism § Flexible system optimization Workload Optimized Systems Power 7 chip Nano Devices Nano Systems (Systems-on-a-chip) § DNA Transistor § Nano Medicine 1 Trillion Devices 1 Billion Transistors 18 © 2012 IBM Corporation

Cognitive Systems: A new era of computing Programmable Systems Era Cognitive Systems Era § Processor-centric § Fixed calculation § Scale up/out § Manual systems management § Data-centric § Statistical analytics § Scale in § Automated systems/ workload management © 2012 International Business Machines Corporation 19

Exploring the future of cognitive systems Applications Cognitive Systems Era Farreaching research Architectures Core

Fully Homomorphic Encryption § Fully homomorphic encryption is a privacy enabling technology § Allows encrypted user data to be processed without the server knowing the content § Results returned to authorized user for decryption § Privacy-enhanced cloud services Craig Gentry, a 35 -year-old IBM researcher, solved this 30 -year cryptographic problem 2010 2009 21 ACM Distinguished Dissertation Award Best Paper Award – IACR Crypto Privacy Enhancing Technology Award Privacy Innovation Award from the Intl. Association of Privacy Professionals

Cognitive Systems: Atomic storage Atomic limits of magnetic storage 96 iron atoms store one byte of data IBM Research explores the boundaries of science and technology © 2012 International Business Machines Corporation 22

Cognitive Systems: Quantum computing Extraordinary capabilities are expected…factoring a 3, 000 digit number 1040 faster than today Silicon chip with three qubits Superconducting qubits use established manufacturing techniques for silicon technology Potential for dramatic advances in cryptanalysis, database sorting, pharmaceutical research IBM is the world leader in this technology © 2012 International Business Machines Corporation http: //www. computerworld. com/s/article/9224670/IBM_touts_quantum_computing_breakthrough 23

Cognitive Systems: Applications Smarter Cities Social Business Human and knowledge capital analytics Optimize sales through insights about sellers, teams, deals, clients, and performance. Social / Demographic Economic Technological Environmental Sensor Networks Watson Feeder line Transmission line Electric car Intelligent building Automated meters Substation Millions of end points 100 K+ elements, 10 ms latency Multiple feedback time-scales © 2012 International Business Machines Corporation John Kelly: In 2014 Watson could be able to fit in your hand. . . tremendous opportunities await. 24

Taking Watson beyond Jeopardy! Understanding Specific Questions Interacting Question-In/Answer-Out Explaining Precise Answers & Accurate Confidences Learning Batch Training Process The type of murmur associated with this condition is harsh, systolic, and increases in intensity with Valsalva From specific questions to rich, incomplete problem scenarios (e. g. EHR) Evidence analysis and look-ahead, drive interactive dialog to refine answers and evidence Move from quality answers to quality answers and evidence Answers, Corrections, Judgements Input, Responses Entire Medical Record Dialog Responses, Learning Questions Refined Answers, Follow-up Questions Rich Problem Scenarios © 2012 International Business Machines Corporation Scale domain learning and adaptation rate and efficiency Interactive Dialog Teach Watson Comparative Evidence Profiles Continuous Training & Learning Process 25 25

Cognitive Systems: Sy. NAPSE § “Neuron” and “synapse”-like computing model § Systems learn through analytics / experience § Advantages: Ultra energy-efficient, flexible, learning Wiring diagram – monkey brain © 2012 International Business Machines Corporation ‘True North’ Learning Pong Character ID 26