COMMON IBM Technology leadership and IT futures


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  • IBM's record-breaking 2011 patent output features many interesting and important inventions, such as: ·           U.S. Patent #8,019,992: Method for granting user privileges in electronic commerce security domains – This patented invention helps IBM WebSphere Commerce software customers reduce administration and resource costs by providing a flexible authentication and authorization mechanism across multiple online stores. The capability enables shoppers and administrators to have access to individual online stores or seamlessly access multiple online stores managed by the same company. It also is a key feature in enabling multiple companies to run on a single instance of WebSphere Commerce. Patent #8,019,992 was issued to IBM inventors Victor Chan, Darshanand Khusial, Lev Mirlas and Wesley Philip. ·           U.S. Patent #8,037,000: Systems and methods for automated interpretation of analytic procedures – This invention describes a method for dynamically constructing natural language explanations of analytic results using templates defined by domain experts. Patent #8,037,000 was issued to IBM inventors Robert Delmonico, Tamir Klinger, Bonnie Ray, Padmanabhan Santhanam and Clay Williams.   ·           U.S. Patent #8,005,773: System and method for cortical simulation – This patented invention describes a method for developing a computerized brain simulation system that can mimic the cognitive systems and function of the cortex of the brain. IBM has fabricated working prototypes of experimental computer chips designed to emulate the brain’s abilities for perception, action and cognition. Patent #8,005,773 was issued to IBM inventors Dharmendra Modha and Rajagopal Ananthanarayanan. ·           U.S. Patent #7,882,219: Deploying analytic functions – This patented invention empowers users to design and implement highly-sophisticated, streaming analytics on massive disparate data sources. The advanced algorithm described in patent #7,882,219 enables IBM Tivoli Network Performance Manager software to efficiently perform sophisticated analytics in near real-time. Patent #7,882,219 was issued to IBM inventors Alexander Pikovsky, David Pennell, Robert McKeown and Colin Putney. For more information about IBM's patent and innovation leadership, please visit:
  • We have about 3,195 employees worldwide between the 8 labs. 1945 - IBM'S FIRST RESEARCH LAB. IBM's first research facility, the Watson Scientific Computing Laboratory, opened in a renovated fraternity house near Columbia University in Manhattan. In 1961, IBM moved its research headquarters to the T.J. Watson Research Center in Yorktown Heights, New York. Today, IBM Research operates Laboratories in the United States, Switzerland, Israel, Japan, China and India. The Watson Research Center is located in Westchester County, New York (both the Watson site and the Hawthorne site) and in Cambridge, Massachusetts. Approximately 1843 employees work between these 3 sites. The research focuses primarily on physical and computer sciences, semiconductors, systems technology, mathematics and information services, applications & solutions. The Almaden Research Center (ARC) in California was dedicated in 1986 & is our focal point for storage, database, and data-related research. About 438 of our employees work there. Almaden is just a short ride from IBM's development labs in San Jose and Santa Teresa. Our laboratory in Zurich, Switzerland (ZRL) , founded in 1956 , has about 210 employees and is noted for its Nobel prizes in 2 areas: superconductivity and scanning tunneling microscopy. It is the focus for our research into communications technology. The token ring communications protocol was invented and developed here--an important innovation and the entree to expanding our business. Recently, Zurich made key contributions to our ATM technology. The Austin Research Lab (ARL), in Texas , was launched in Sept '95 seeking to break new ground in the field of microprocessors - and demonstrate new kinds of interactivity between Research and IBM's development teams. Focus areas include: high performance/low power VLSI design and tools, power aware systems and exploratory architectures, and simulation tools modeling for IBM large systems. Austin has about 50 employees. The IBM Tokyo Research Laboratory (TRL) was established in 1982. Researchers at TRL are active in analytics and optimization, software engineering, middleware, system software, security and compliance, electronical and optical packaging technology, engineering and technology services, text mining and speech technology, and accessibility technology. TRL has about 190 employees. Over 400 individuals work at the IBM Haifa Labs (HRL) ; 25 percent of the technical staff have doctorate degrees in computer science, electrical engineering, mathematics, or related fields. Employees are actively involved in teaching at Israeli higher education institutions and supervising post-graduate theses. Many employees have received IBM awards for achievements and excellence. Since it first opened as the IBM Scientific Center in 1972 , the IBM Research Lab in Haifa (HRL) has conducted decades of research that has been vital to IBM’s success. R&D projects are being executed today by HRL for IBM labs in the USA, Canada, and Europe, in areas such as storage systems, verification technologies, multimedia, active management, information retrieval, programming environments, optimization technologies, and life sciences. " 1995 - China Research Laboratory (CRL) opened in Beijing. The event symbolized IBM's commitment to ushering in a new age of shared technology and partnership for the development of China. China has about 132 employees. CRL is located in Shangdi, in the northwest of Beijing. CRL has been growing steadily and it currently has over 100 technical staff members. Researchers at CRL are active in multi-modal interactions such as voice and visual, intelligent information management, pervasive computing, e-business technologies and Service computing. The IBM India Research Laboratory (IRL) was established in 1998 in Delhi, India. Researchers in IRL work in the areas of distributed computing, software engineering, information management, pervasive computing, bioinfomatics, speech recognition for Indian languages and autonomic computing, among others. About 95 employees work here. Regular Employee count updated 1/27/05 – info from Tim Geraghty
  • In the 1980’s data enterprise data was housed in the glass house, and accessed by a few thousand ‘knowledge workers’. Growth of data and access demand was predictable and limited by the number of employees. In the 1990’s we saw distributed computing grow up, and access to enterprise data was required by all employees, and even suppliers and customers. Workload became less predictable and more event driven. In this decade, web data access has become common practice, and data creation or access is a worldwide, non-stop process. Mobile devices have become pervasive. We are creating larger data objects, including video, high resolution medical images, data warehouses, and digital archives. Some workloads can be widely unpredictable. We expect the next generation to build a network of sensors, cameras, and control systems – an internet of things that control everything from power distribution and traffic flow, to outpatient monitoring, theft prevention, and classroom instruction. There could easily be a trillion devices collecting data, accessing it, or taking action to improve daily life, ----- In computing , the Internet of Things (also known as the Internet of Objects ) refers to the networked interconnection of everyday objects. [1] It is generally imagined as a self-configuring wireless network of sensors whose purpose would be to interconnect all things. [1] The concept is attributed to the original Auto-ID Center , founded in 1999 and based at the time in MIT [2] [3] . Although the idea is simple, its application is difficult. If all objects in the world were equipped with minuscule identifying devices, daily life on our planet could undergo a transformation. Such a system could greatly reduce the chances of a company running out of stock or wasting products, as all involved parties will know exactly what products are required and consumed. Mislaid items and physical theft would be affected by the fact that the location of an item would be known at all times. If all objects of daily life, from tubs of yoghurt to airplanes, were equipped with radio tags, they could be identified and managed by computers in the same way humans can. [ clarification needed ] [4] [5] The next generation of Internet applications ( IPv6 protocol) would be able to identify more objects than IPv4 , which is currently in use. This system would therefore be able to instantaneously identify any kind of object. [6] The Internet of objects would encode 50 to 100 trillion objects, and be able to follow the movement of those objects. Every human being [ where ? ] is surrounded by 1,000 to 5,000 objects. [7] Alcatel-Lucent touchatag [8] service and Violet's Mirror gadget provide a pragmatic consumer oriented approach to the Internet of Things by which a developer can link real world items to the online world using RFID tags and QR Codes .
  • Michael Nelson, Georgetown university, former IBMer Internet strategy. --- 50 bio devices connected by 2020 By 2015 every new car build will have an internet connection Personal sensors (blood pressure, heart rhythm) Large structure integruty (bridges, roads) Weather/climate sensors Tsunami tracking Pollution sensors Real time traffic conditions Home automation and security Power metering Security services  AutoBot car appliance (locking/unlocking doors, windows, communicate location, speed, location limits, service, messaging if accident)  Running shoes (Nike), Alzheimer tracking shoes Wildlife tracking
  • Phase change memory (PC-RAM) is a very active research area. Phase-change memory (also known as PCM, PRAM, and Chalcogenide RAM) is a type of non-volatile computer memory. PRAM uses the unique behavior of chalcogenide glass, which can be "switched" between two states, crystalline and amorphous, with the application of heat. PC-RAM is one of a number of new memory technologies that are attempting to compete in the non-volatile role with the almost universal Flash memory, which has a number of practical problems these replacements hope to address. The crystalline and amorphous states of chalcogenide glass have dramatically different electrical resistivity values, and this forms the basis by which data is stored. The amorphous, high resistance state is used to represent a binary 0, and the crystalline, low resistance state represents a 1. Chalcogenide is the same material utilized in re-writable optical media (such as CD-RW and DVD-RW). In those instances, the material's optical properties are manipulated, rather than its electrical resistivity, as chalcogenide's refractive index also changes with the state of the material. The work shown here was presented by IBM and partners Macronix and Qimonda (spun off from Infineon) in December 2006 at the IEEE-IEDM (Institute of Electrical and Electronics Engineers – International Electron Device Meeting) . A new PCM memory cell using a Germanium Antimony-based alloy (GeSb) has demonstrated switching over 500 times faster than flash, using less than ½ the power, and at extreme density. This is an early look at a potential future NVRAM technology. ---------------------------------------------------- IBM Group Claims Phase-Change Breakthroughs / By Colleen Taylor / Electronic News, 12/11/2006 Scientists from IBM, Macronix and Qimonda today announced joint research results that they said pave the way for phase-change memory, a new type of non-volatile computer memory the researchers claim is set to succeed flash memory. The researchers, who first teamed up for phase-change research in May of 2005, said they have designed, built and demonstrated a prototype phase-change memory device that switched more than 500 times faster than flash while using less than one-half the power to write data into a cell. The device's cross-section is a minuscule 3nm-by-20nm in size, far smaller than flash can be built today, according to the scientists. "These results dramatically demonstrate that phase-change memory has a very bright future," Dr. T. C. Chen, VP of science and technology at IBM Research, said in a statement. "Many expect flash memory to encounter significant scaling limitations in the near future. Today we unveil a new phase-change memory material that has high performance even in an extremely small volume." The researchers said the new material is a "complex semiconductor alloy" created at IBM's Almaden Research Center in San Jose, Calif. The material's phase is set by the amplitude and duration of an electrical pulse that heats the material. When heated to a temperature just above melting, the alloy's energized atoms move around into random arrangements. Suddenly stopping the electrical pulse freezes the atoms into a random, amorphous phase. Turning the pulse off more gradually, over about 10 nanoseconds, allows enough time for the atoms to rearrange themselves back into the well-ordered crystalline phase they "prefer," according to the scientists. The new memory material is a germanium-antimony alloy (GeSb) to which small amounts of other elements have been added to enhance its properties, the researchers said. A patent has been filed covering the composition of the new material.
  • Anisotropy is the property of being directionally dependent, as opposed to isotropy , which means homogeneity in all directions. It can be defined as a difference in a physical property (absorbance, refractive index, density, etc.) for some material when measured along different axes. Atomic computing Nanotech breakthroughs pave the way for the ultra-small If an 80GB iPod can store up to 100 hours of video, imagine the possibility of a similar device able to hold 30,000 feature length films.  IBM has taken a couple of steps in that direction with results featured in two research papers being published in the same issue of Science ; a rare occurrence that highlights the significance of these breakthroughs. Building on IBM's rich nanotech past Research continues to break new ground with two major scientific achievements that could permanently alter the way computing works. The first paper focuses on our milestone in understanding atomic magnetism, bringing single-atom data storage closer to reality.  The second paper sheds light on single-molecule switching, which could lead to molecular computers.  What does this mean?  It means that storing enormous amounts of information on a single atom and the idea of a computer comprised of just a few molecules is no longer just the stuff of science fiction. While this type of work still falls squarely in the realm of exploratory science, it will enable scientists at IBM and elsewhere to continue moving forward in the field of nanotechnology – the exploration of building structures and devices out of ultra-tiny components as small as a few atoms or molecules.  Such devices might be used as future computer chips, storage devices, sensors and for applications nobody has imagined yet. "One of the beauties of doing exploratory science is that by researching one area, you sometimes stumble upon other areas of major significance," said Gerhard Meyer, senior researcher in the nanoscale science group at the IBM Zurich lab, commenting on the discovery of two hydrogen atoms inside a naphthalocyanine molecule that can do switching.  "Although the discovery of this breakthrough was accidental, it may prove to be significant for building the computers of the future." The most exciting phrase to hear in science, the one that heralds new discoveries, is not 'Eureka!', but 'That's funny...'  - Isaac Asimov This "accidental" discovery happened while the Research team had been screening various molecules for their suitability in molecular switches, the tests were not to observe switching, but rather to examine molecular vibrations and how those would affect devices operating at the atomic level.  During those tests, the team observed results that were intriguing for switching at the molecular scale, and they shifted their focus from studying vibrations to studying switching, leading to this breakthrough. How does it work? In the first report out of the Almaden Research Lab, the scientists describe major progress in probing a property called magnetic anisotropy in individual atoms. This fundamental measurement has important technological consequences because it determines an atom’s ability to store information.  Previously, nobody had been able to measure the magnetic anisotropy of a single atom. With further work it may be possible to build structures consisting of small clusters of atoms, or even individual atoms, which could reliably store magnetic information. Perhaps more importantly, the breakthrough could lead to new kinds of structures and devices that are so small they could be applied to entirely new fields and disciplines beyond traditional computing. In the second report, out of the Zurich Research Lab, the scientists unveiled the first single-molecule switch that can operate flawlessly without disrupting the molecule's outer frame -- a significant step toward building computing elements at the molecular scale that are vastly smaller, faster and use less energy than today's computer chips and memory devices. In addition to switching within a single molecule, the researchers also demonstrated that atoms inside one molecule can be used to switch atoms in an adjacent molecule, representing a rudimentary logic element.  This is possible partly because the molecular framework is not disturbed. Fe-N-Cu (Ferrum-Nitrogen-Copper)
  • It could begin to replace flash memory in three to five years. His idea is to stand billions of ultrafine wire loops around the edge of a silicon chip — hence the name racetrack — and use electric current to slide infinitesimally small magnets up and down along each of the wires to be read and written as digital ones and zeros. His research group is able to slide the tiny magnets along notched nanowires at speeds greater than 100 meters a second. Since the tiny magnetic domains have to travel only submolecular distances, it is possible to read and write magnetic regions with different polarization as quickly as a single nanosecond — far faster than existing storage technologies.
  • Der US-Konzern IBM entdeckt Elektroautos als aussichtsreiches Geschäftsfeld. Nach einem Bericht der Businessweek will Big Blue seine Kräfte bündeln, um leistungsfähige Batterien für Autos zu entwickeln. An dem Projekt sollen sich fünf Forschungseinrichtungen beteiligen, darunter die Universität von Kalifornien in Berkeley. Ziel von IBM und seinen Partnern ist es demnach, eine Batterietechnik zu entwickeln, die Elektroautos mit einer Ladung 300 bis 500 Meilen weit bringt, das entspricht etwa 500 bis 800 Kilometer. Aus heutiger Sicht sind das utopische Werte, selbst lithiumbasierte Akkumulatoren für derartige Strecken wären extrem schwer und teuer. Viele Experten gehen derzeit davon aus, dass Lithium-Traktionsbatterien bei Großserienproduktion für etwa 750 Euro pro kWh zu produzieren wären, mittelfristig erscheinen etwa 300 Euro realistisch. Ausgehend von einer gängigen Faustregel, dass 100 Kilometer Fahrstrecke bei einem Mittelklasseauto etwa 15 kWh erfordern, wären zum Beispiel für 500 Kilometer 75 kWh notwendig. Aus heutiger Sicht wäre eine Lithium-Antriebsbatterie demnach praktisch unerschwinglich. Laut Bericht bevorzugt IBM eine "radikal andere Batterietechnologie", wie IBM-Forschungschef Chandrasekhar "Spike" Narayan zitiert wird. Das Konsortium setzt demnach auf Lithium-Sauerstoff-Batterien anstelle der "potenziell entflammbaren Lithium-Ionen-Batterien". Die neuen Batterien sollen fünf- bis zehnmal so viel Energie speichern können als Lithium-Ionen-Batterien. Das Entwicklungsteam mit rund 40 Mitarbeitern wird von Winfried W. Wilcke geleitet, der an IBMs Almaden Research Center für Nanotechnologie-Projekte zuständig ist. Sein Team hatte bei der Suche nach neuen technischen Ansätzen herausgefunden, dass die Kombination aus Lithium und Sauerstoff den größten Erfolg verspricht. Bei dieser Technik könne sehr viel mehr Energie untergebracht werden, weil der Sauerstoff bei Bedarf der Umgebungluft entzogen werde, anstatt fester Bestandteil der Batterie zu sein. Ähnliches hatte bereits die schottische Universität von St. Andrews berichtet , deren Forscher ebenfalls ein zehnfache Steigerung der Kapazität von Batterien für möglich halten. Serienanwendung frühestens 2014 .
  • Cancer: This "directive" is reflected in the extraordinary number of blood vessels often found feeding cancerous growths. Fortunately these blood vessels are different than normal ones; they tend to have holes and gaps in the vessel walls that aren't found in normal blood vessels. Since these rouge blood vessels feed directly into cancerous cells taking advantage of their leaky nature could be yet another way to attack the growths. Surgery At Rice University, a flesh welder is used to fuse two pieces of chicken meat into a single piece. The two pieces of chicken are placed together touching. A greenish liquid containing gold-coated nanoshells is dribbled along the seam. An infrared laser is traced along the seam, causing the two sides to weld together. This could solve the difficulties and blood leaks caused when the surgeon tries to restitch the arteries that have been cut during a kidney or heart transplant. The flesh welder could weld the artery perfectly. [17] Neuro-electronic interfaces Neuro-electronic interfacing is a visionary goal dealing with the construction of nanodevices that will permit computers to be joined and linked to the nervous system. This idea requires the building of a molecular structure that will permit control and detection of nerve impulses by an external computer. The computers will be able to interpret, register, and respond to signals the body gives off when it feels sensations. The demand for such structures is huge because many diseases involve the decay of the nervous system (ALS and multiple sclerosis). Also, many injuries and accidents may impair the nervous system resulting in dysfunctional systems and paraplegia. If computers could control the nervous system through neuro-electronic interface, problems that impair the system could be controlled so that effects of diseases and injuries could be overcome. Cell repair: Cell repair will utilize the same tasks that living systems already prove possible. Access to cells is possible because biologists can insert needles into cells without killing them. Thus, molecular machines are capable of entering the cell. Also, all specific biochemical interactions show that molecular systems can recognize other molecules by touch, build or rebuild every molecule in a cell, and can disassemble damaged molecules. Finally, cells that replicate prove that molecular systems can assemble every system found in a cell. Therefore, since nature has demonstrated the basic operations needed to perform molecular-level cell repair, in the future, nanomachine based systems will be built that are able to enter cells, sense differences from healthy ones and make modifications to the structure.
  • Global Technology Outlook 2010 Nobelprize winners of ETH: 21 (either studied or taught). Die Fakten könnten deutlicher kaum sein: Bis heute wurden 21 Nobelpreise an Forscher vergeben, die mit der ETH Zürich in Verbindung standen oder stehen. Einige von ihnen waren zum Zeitpunkt der Preisverleihung aktive Professoren, andere emeritiert. Eine dritte Gruppe hat an der ETH studiert. Nobelpreisträger der ETH 1901 Physik Wilhelm Konrad Röntgen 1913 Chemie Alfred Werner 1915 Chemie Richard Willstätter 1918 Chemie Fritz Haber 1920 Physik Charles-Edouard Guillaume 1921 Physik Albert Einstein 1936 Chemie Peter Debye 1938 Chemie Richard Kuhn 1939 Chemie Leopold Ruzicka 1943 Physik Otto Stern 1945 Physik Wolfgang Pauli 1950 Medizin Tadeusz Reichstein 1952 Physik Felix Bloch 1953 Chemie Hermann Staudinger 1975 Chemie Vladimir Prelog 1978 Medizin Werner Arber 1986 Physik Heinrich Rohrer 1987 Physik Georg Bednorz/ Alexander Müller 1991 Chemie Richard Ernst 2002 Chemie Kurt Wüthrich
  • Designing a computer that can process and understand natural language. IBM is working to build a computing system that can understand and answer complex questions with enough precision and speed to compete against some of the best Jeopardy! contestants out there. This challenge is much more than a game. Jeopardy! demands knowledge of a broad range of topics including history, literature, politics, film, pop culture and science. What's more, Jeopardy! clues involve irony, riddles, analyzing subtle meaning and other complexities at which humans excel and computers traditionally do not. This, along with the speed at which contestants have to answer, makes Jeopardy! an enormous challenge for computing systems. Code-named "Watson" after IBM founder Thomas J. Watson, the IBM computing system is designed to rival the human mind's ability to understand the actual meaning behind words, distinguish between relevant and irrelevant content, and ultimately, demonstrate confidence to deliver precise final answers. Known as a Question Answering (QA) system among computer scientists, Watson has been under development for more than three years. According to Dr. David Ferrucci, leader of the project team, "The confidence processing ability is key to winning at Jeopardy! and is critical to implementing useful business applications of Question Answering." Watson will also incorporate massively parallel analytical capabilities and, just like human competitors, Watson will not be connected to the Internet, or have any other outside assistance.
  • U of Melbourne currently has two frames of BG/P each of which has peak performance of 13.9 TFLOPS for a total of 27.8 TFLOPS. It's only modest in size in terms of supercomputers but the plan is to go to 4 frames of BG/Q in 2012 which will deliver a total of 800 TFLOPS. 
  • The challenges of big data are recently showing themselves to be not only of size/scale, but of speed. Our work in this area focuses on both the ‘very big’ and the ‘very fast’ areas of analytics and information management. Merging real-time analytics with deep analytics Meaning from text at record volumes and speed Write optimized massive scale analytics with few lines of code Super fast indexing of thousands of facets for advanced data discovery Hardware optimized and packaged as an appliance
  • If you consider our work with Watson from a roadmap point of view, we think of the evolution of this program in three phases. The first phase is focused on the research and demonstration of the technology. From there, we shift our attention to the commercial application potential. This is that same winner’s cloud comparison, but in this case the information being learned by Watson is a wide set of medical journals, educational documents, etc. And in looking toward the more exploratory side of our plans, our plans consider the possibilities that come from applying additional technologies that in their own right are in the midst of a surge in innovation.
  • Cognitive Computing - With Darpa funding, IBM and university researchers have been developing a computer chip that mimics the processes of the human brain. "IBM’s so-called cognitive computing chips could one day simulate and emulate the brain’s ability to sense, perceive, interact and recognize--all tasks that humans can currently do much better than computers can," reports Dean Takahashi at VentureBeat. The brain-like processors with integrated memory don’t operate fast at all, sending data at a mere 10 hertz, or far slower than the 5 gigahertz computer processors of today. But the human brain does an awful lot of work in parallel, sending signals out in all directions and getting the brain’s neurons to work simultaneously. Because the brain has more than 10 billion neuron and 10 trillion connections (synapses) between those neurons, that amounts to an enormous amount of computing power. Mind-controlled prosthetic limbs - Darpa isn't the only one working on this, but they're making major headway designing prosthetics that connect to the human brain. Unlike other robotic prosthetics, Darpa's limb would require an implant in the human brain that would allow the arm or leg to move the limb by simply thinking about it. The brain has more than 10 billion neuron and 10 trillion connections (synapses) between those neurons . IBM wants to build a computer with 10 billion neurons and 100 trillion synapses, Modha said (2020?). That’s as powerful than the human brain. The complete system will consume one kilowatt of power and will occupy less than two liters of volume (the size of our brains), Modha predicts. "SyNAPSE" (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) Synapse is funded with a $21 million grant from DARPA, and it involve six IBM labs, four universities (Cornell, the University of Wisconsin, University of California at Merced, and Columbia) and a number of government researchers.
  • On August 18 th 2011 we announced the first computing cores that combines digital “neurons” and on-chip “synapses” in working silicon. This radical new compute core demonstrates synaptic plasticity, the foundation of learning and memory. With no set programming, these cores mimic the event-driven, parallel processing abilities found in the brain while using orders of magnitude less power and space than today’s computers. IBM developed the first custom cognitive computing cores that bring together digital spiking neurons with ultra-dense, on-chip, crossbar synapses and event-driven communication.
  • Human Brain: 10 bio Neurons, 10 trio Synapses, IBM intends to build: 10 bio Neurons, 100 trio Synapses,
  • Functional illiterates in USA: 15%. (In Italy 1.1%, Hungary 0.6%) --------------------------------- 30% of high school graduates never read another book for the rest of their lives. 42% of college graduates never read another book after college. 70% of U.S. adults have not been in a bookstore in the last five years. 80% of U.S. families did not buy or read a book last year. ------ 5 innovations in 2-5 years: . Solar cells on windows, building surfaces, sidewalks, etc.. five times energy captured, 100 times thinner than silizium cells.  . Cell phone pointing to building, shop/sale. (Empire State 1931, 381m, 102 floors) . Doctor health check with sensors, genetic map for $200 . Phone call to anyone with any language speech translation . Nano carbon tubes for water filtration . 3D Internet, shopping, education, trip to China ---- mmWave technology: IBM and MediaTek. For example, you could upload a 2 hour HDTV video (25 GB) in 12.5 seconds with the new technology versus 25 minutes using current Wi-Fi technology. (1200 times: 64Gb). 2-6 gb/sec. 2010 Research paper talks about 7 Ghz bandwidth and 40-100 times WLAN throughput. 1 DVD (4.7 GB) in 15 seconds. HDTV Full requires approx. 2.1 Gbps.
  • Supercomputing Roadmap In the next 20 years, the growth of compute power will correspond to hundreds of millions of years of evolution. Deep Blue had the compute power (8 TF in 1997) of a lizard brain. ASCI Red Option at 1TF, ASCI Red at 3 TF, ASCI Blue Pacific at 4TF, ASCI White at 12TF, ASCI Q at 30TF, ASCI Purple at 100TF. BG/L at 360 TF, BG/P at 1 petaflop. By 2014 or 2015, a supercomputer (in 2020 for "PCs") will have the compute power of a human brain. While it is difficult to compare brain operations to computer operations (various types of estimates are used, such as the density of retinal cells extrapolated up to the volume of the brain). It is clear the computers of the future will have enormous capabilities, the uses for which we have only just begun to explore. Special purpose machines, chess, molecular chemistry computations, protein folding are just the beginning to touch the possibilities Current applications: Simulations of nuclear explosions (ASCI) Life Sciences: e.g. classical molecular dynamics of protein folding and lipids; human genome mapping Weather/Climate Forecasting Fundamental science, mathematical problems---e.g. ab initio quantum molecular dynamics Simulation of galaxies Car crash simulations More applications will emerge as supercomputing capability becomes available. IBM has recently announced Center for Business Optimization (as part of BCS) to couple deep computing capability with analytics to solve very complex business optimization problems for clients.
  • Exponential growth: How many rice corns needed to duplicate on every field of chess board: 18 trillion How often fold paper to reach the moon: 42 times.  
  • COMMON IBM Technology leadership and IT futures

    1. 1. IBM Technology Leadership and IT Futures Common Europe Congress Vienna, Austria June 9-12, 2012Wolfgang Singer, Honorary Member of IBM IT-Specialist 1
    2. 2. Intellectual Property and Standards USPTO Top 10 Patentees – 2011 IBM has the patent leadership for the 19th consecutive year. Hundreds of patents donated.22 IBM Patent Leadership © 2012 IBM Corporation
    3. 3. IBM Systems and Technology Group IBM Research Worldwide Yorktown Rüschlikon Almaden Beijing I Austin Tokyo Haifa Delhi3 © 2012 IBM Corporation
    4. 4. And …Coping with Scale T • In data Internet of Things • In numbers of producers • In numbers of consumers G Internet, Web 2.0 Distributed Computing M Data Center K 1980 1990 2000 20104 © 2009 IBM Corporation
    5. 5. The Internet of Things Cars HomesAppliances CellphonesSensors Consumer electronics Everything
    6. 6. We Have 3 or 4 Years If we make the right choices:  The Internet continues to grow  Bandwidth explodes  Wireless everwhere  10x, 100x more applications  Internet of Things > Invisible Computing If we blow it:  Internet becomes Cable TV  Innovation shuts down
    7. 7. Internet Conclusions The Internet Revolution is less than 15% complete The Internet Revolution will be as disruptive as the printing press, but:  Much faster  Totally global  More unpredictable (incl. Cybercrimes)  Privacy vs. openness
    8. 8. IBM Systems and Technology GroupStorage Class Memory (SCM)  Phase-Change Non-volatile Memory: Drastic reduction in cost/GB by development of novel low cost materials (e.g. Germanium- Antimony-Telluride chips) Joint research of IBM, Macronix & Qimonda  Compared to RAM Non-volatile small % of DRAM cost  Compared to HDD No moving parts => High reliability Significantly higher performance (50-1000x) I Much lower power consumption Small form factor Small premium in cost  Compared to Flash memory >500 times faster SiOx >10000 times more endurance Pt (for XSEM) 5nm 3nm GeSb SiO2 Half the power consumption SiOx layer Extreme density – PCM cell is nanotechnology: 3nm-by-20nm in size TiN 10nm GeSb layer TiN 100n SiO2 m First usable chip: 2011, enterprise systems: 2012/2013, complete disk replacement: 2020?8 © 2012 IBM Corporation
    9. 9. IBM Research Atomic Scale Magnetism  Magnetic anisotropy determines whether an atom’s magnetic orientation is stable over time.  Previous measurements of magnetic anisotropy have required averaging over millions of atoms.  A scanning tunneling microscope was used to measure the magnetic anisotropy of a Fe single atom. N N Cu Cu  Expect to control and read the magnetic Cu orientation of a single atom for storing of information.CNBC video © 2012 IBM Corporation 9
    10. 10. IBM Systems and Technology Group Racetrack Digital Storage • Data stored in magnetic domain walls • Billions of nanowires used on silicon chip • 100 times more storage than on disk or flash • Much faster than existing storage  Read and write in a nanosecond I • Introduction in 4-6 years Stuart Parkin, inventor of GMR read heads. Nobel price for GMR for Peter Gruenberg (D) and Albert Fert (F) 2007.1010 © 2012 IBM Corporation
    11. 11. Electric vehicles in a distributed and integrated market using sustainable energy and open networks Neue Batterie Technologien im Vormarsch Source:SonntagsZeitung25 October 20091111 © 2012 IBM Corporation
    12. 12. Electric vehicles in a distributed and integrated market using sustainable energy and open networks Batterie Gewichtsunterschiede1212 © 2012 IBM Corporation
    13. 13. IBM Research Electric Power Grid in Bornholm13 © 2011 IBM Corporation
    14. 14. 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 ACM Distinguished Dissertation Award 2010 Best Paper Award – IACR Crypto 2010 Privacy Enhancing Technology Award 2009 Privacy Innovation Award from the Intl. Association of Privacy Professionals1414 © 2012 IBM Corporation
    15. 15. IBM Research - Zurich Nano-World – Scale of Things Things Natural 10-2 m 1 cm Things Manmade 10 mm Head of a Pin 1-2 mm 1,000,000 nanometers 10-3 m = 1 millimeter (mm) Ant ~ 5 mm Micro-Electromechanical Microwave (MEMS) Devices Dust Mite 10 -100 μm wide 200 μm 10-4 m 0.1 mm 100 μm Mikro-Welt Human Hair Fly Ash ~ 60-120 μm wide ~ 10-20μm 10-5 m 0.01 mm 10 μm Pollen Grain Infrared Red Blood Red Blood Cell Zone Plate x-ray “Lens” Cells Outer ring spacing ~35 nm (~7-8 μm) 1,000 nanometers 10-6 m Today CMOS Gate Length Visible = 1 micrometer (μm) Gate Length ~35 nm 10-7 m 0.1 μm 100 nm Elektrodes for Ultraviolet Carbon Self-assembled, Nature- Nanotubes Nano- Welt 10-8 m 0.01 μm inspired structure Virus 10 nm Many 10s of nm25-100 nm diameter ATP synthase ~10 nm diameter Corral diameter 14 nm 10-9 m 1 nanometer (nm) Carbon buckyball Soft x-ray ~1 nm diameter Carbon Nanotube ~1.3 nm diameter Silicon Quantum corral of 48 iron atoms 15 DNA Atoms Walter Riess 10-10 m 0.1 nm on copper surface positioned one Office of Basic Energy Sciences © 2012 Science, U.S. DOE IBM Corporation Office of ~2-1/2 nm diameter diameter 0.115 nm at a time with an STM tip Version 05-26-06, pmd
    16. 16. IBM Research - ZurichNanotechnology – Everywhere Laser Etching Regenerative Scratch resistive Medicine Lacquer Nano-Pore Photovoltaics DNA Self-cleaning paints DNA Sequencing and Textiles Filtration und purification16 © 2012 IBM Corporation
    17. 17. IBM SYMPOSIUM Worlds Smallest 3D Map • Achievement of Rüschlikon Lab in April 2010 • World Image in 3D in 22x11 micrometers • Created in 2 minutes, 23 seconds • on polymer and molecular glas • 1000 of these 3D images on one grain of salt Potential future nano-transistor - 50 nm thin 3D video - no leak - much less power needed1717 © 2003 IBM Corporation
    18. 18. New Nano-Technology Researchcenter IBM Rüschlikon and ETH Zürich  1000 m2 cleanroom facilities  “Noise-free” laboratories  $30 million in equipment  Opened in May 2011 Binning Rohrer Nanotechnology Center © 2012 IBM Corporation 18
    19. 19. IBM Research IBM Jeopardy Challenge • Jeopardy Quizshow in the US • Capability to answer questions in natural language • 4 years research project • Human contestants were the two top Jeopardy winners ---- • 90 P570 systems • DeepQA with 2880 processors • 16 TB of memory • No Internet connection allowed • 200 mio pages scanned in • Price money: Winner: $1 mio, 2nd: $300K, 3rd: $200 Contestants give 50%, IBM 100% to charity19 video © 2012 IBM Corporation Potential Real Life Usage:
    20. 20. How Watson Works  Unlike Internet search engines, which only point users to documents that contain answers, Watson delivers an actual answer.  Watson is not connected to the internet - like a human, it delivers its answers from the resource of data in its "brain“.  Watson uses the same buzzer used by the human contestants. When the Jeopardy! host reads the clue, Watson must "buzz in" in competition with the humans.  Watson calculates a list of possible answers, and then selects the best one based on its level of “confidence” that it is correct., © 2012 IBM Corporation 11:15
    21. 21. IBM Research Some of the Jeopardy Questions Bram Stoker video21 © 2012 IBM Corporation
    22. 22. The Practical Applications of Watson "If we can teach a computer to play Jeopardy!, what could it mean for science, finance, healthcare and business? By drastically advancing the field of automatic question answering, the Watson projects ultimate success will be measured by what it means for society." Medicine: The computer could diagnose rare diseases based on a particular set of symptoms. The computer could hold every medical paper ever produced, and the steps of every known medical procedure. Enterprise: Knowledge Management and Business Intelligence Customer support (Helpdesk): After being programmed with every possible customer care issue, the computer could serve as a virtual call center, providing verbal answers to customers in real time. Instead of "Google it", it will be "ask Watson" in the future. (Craig Rhinehart)Source: © 2012 IBM Corporation 11:15
    23. 23. Four Technologies that Will Change the World Cognitive Computing Compute+  “Synapse” devices Natural Language+ Analytics Deep Q&A BIG/Fast Data  Exa / zettabytes Computers  Milli / microseconds  Unstructured  Noisy Data Exascale (Datacenter-in-a-box)  Massive parallelism  Flexible system optimizationWorkloadOptimized Systems Nano Systems (Systems-on-a-chip)  DNA Transistor  Nano Medicine Power7 chip Nano 1 Trillion Devices Devices 1 Billion Transistors © 2012 IBM Corporation23
    24. 24. From Nano Devices to Nano Systems Cognitive Computing Compute+  “Synapse” devices Natural Language+ Analytics Deep Q&A BIG/Fast Data  Exa / zettabytes Computers  Milli / microseconds  Unstructured  Noisy Data Exascale (Datacenter-in-a-box)  Massive parallelism  Flexible system optimizationWorkloadOptimized Systems Nano Systems (Systems-on-a-chip)  DNA Transistor Power7 chip  Nano Medicine 1Trillion Nano Devices Devices 1Billion Transistors © 2012 IBM Corporation24
    25. 25. Why IBM Invests in Nanotechnology: Accelerating Advances in Information Technology IE+12 Integrated Nanotechnology$1000 Buys: Computations per second Circuit IE+9 Discrete Transistor IE+6 Vacuum Tube IE+3 Electro- Mechanical Mechanical IE+0 IE-3 IE-5 1900 1920 1940 1960 1980 2000 2020 Source: Kurzweil 1999 – Moravec 1998 25 © 2012 IBM Corporation
    26. 26. 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 antibiotic- resistant bacteria  Fights infectious diseases  Biodegradable 13 © 2012 IBM Corporation26
    27. 27. From Petascale to Exascale Cognitive Computing Compute+  “Synapse” devices Natural Language+ Analytics Deep Q&A BIG/Fast Data  Exa / zettabytes Computers  Milli / microseconds  Unstructured  Noisy Data Exascale (Datacenter-in-a-box)  Massive parallelism  Flexible system optimizationWorkloadOptimized Systems Nano Systems (Systems-on-a-chip)  DNA Transistor  Nano Medicine Power7 chip Nano 1Trillion Devices Devices 1Billion Transistors © 2012 IBM Corporation27
    28. 28. Exascale ComputingA billion calculations in a billionth of a second Overall Performance = 1000X Performance / watt = 135X Performance / $ = 1000X 1 PetaFlop Footprint = <2% 72 BG/P Racks Referenced to one-petaflop system CPU Silicon Photonics Phase Change Memory 3D Software The Next Ten Years 1 PetaFlop = 1/3 rack 2009 201928 15 © 2012 IBM Corporation
    29. 29. Natural Disaster Prediction and ResponseDeep Thunder  24- to 48-hour forecasts  1 - 2 km resolution  3 hours to 3 days lead time  Weather data coupled with analytics © 2012 IBM Corporation29 17
    30. 30. From Big Data to Big Analytics Cognitive Computing Compute+  “Synapse” devices Natural Language+ Analytics BIG/Fast Data Deep Q&A  Exa / zettabytes Computers  Milli / microseconds  Unstructured  Noisy Data Exascale (Datacenter-in-a-box)  Massive parallelism  Flexible system optimizationWorkloadOptimized Systems Nano Systems (Systems-on-a-chip)  DNA Transistor  Nano Medicine Power7 chip Nano 1Trillion Devices Devices 1Billion Transistors © 2012 IBM Corporation30
    31. 31. 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 Homeland Security Super fast indexing of thousands of facets 600k records per second 50 billion per day Optimized and integrated system 1-2 milliseconds per decision 320 terabytes for Deep Analytics Telco Promotions 100k records per second, 6 billion per day 10 milliseconds per decision 270 terabytes for Deep Analytics IBM DeepQA 100s of gigabytes for Deep Analytics 3 seconds per decision31 © 2012 IBM Corporation
    32. 32. Smarter Traffic 250k GPS probes per second 630k segments per second 2 milliseconds per decision (4k vehicles) © 2012 IBM Corporation32
    33. 33. From Programming to Systems that Learn Compute+ Cognitive Computing Natural  “Synapse” devicesLanguage+ Analytics Deep Q&A BIG/Fast Data  Exa / zettabytes Computers  Milli / microseconds  Unstructured  Noisy Data Exascale (Datacenter-in-a-box)  Massive parallelism  Flexible system optimizationWorkloadOptimized Systems Nano Systems (Systems-on-a-chip)  DNA Transistor  Nano Medicine Power7 chip Nano 1Trillion Devices Devices 1Billion Transistors © 2012 IBM Corporation33
    34. 34. Watson – a Roadmap Research / Demo Commercialization Future Technologies Voice & Image Recognition Won Jeopardy! Query & Dialogue2007 – 2011 2011 – 2012 2012 – 2015 © 2012 IBM Corporation34 22
    35. 35. IBM Research IBM gets DARPA cognitive computing contract • Simulate the brains sensation, action, interaction, perception and cognition abilities • Supercomputing and nano-technology enable creation of simulated synapses • SyNAPSE project is only the first phase Read more: • Simulation of neurons with Optogenetics • Designer viruses and optical signals may take over functions in wound/stroke patients • Mind-controlled prosthetic limbs35 © 2012 IBM Corporation
    36. 36. Cognitive ComputingFirst chips and architecture for Learning Systems  Spatial navigation  Machine vision  Pattern recognition  Associative memory  45 nanometer  262k programmable synapses  256 neurons  65k learning synapses © 2012 IBM Corporation36
    37. 37. Cognitive Computing Neuroscience ComplexitySupercomputing Nanoelectronics Time © 2012 IBM Corporation37
    38. 38. IBM SYMPOSIUM Innovations for the Next Five Years  ‘Thin film’ solarcells on sidewalks, windows, paintings  Genetic map about health risks (based on DNA)  Intelligent co-driver • Improved navigation (augmented reality), distancecontrol, pay-as you drive  Cell phone extension of Internet • Camera object description • Shop information • Remote control of home equipment • ‘Spoken Web’  mmWave wireless communication  Multilingual phone communication  3D Internet3838 Template Documentation 06/20/12 © 2003 IBM Corporation
    39. 39. IBM Systems and Technology Group Supercomputing Roadmap System 64 Racks, 64x32x32 100000 Node Card Rack 32 Node Cards 32 Chips 4x4x2) Compute 16 compute, Card 0-2 IO cards 2 chips, 180/360 TF/s Chip 2processors 10000 1x2x1 2.8/5.6 TF/s 32 TB 90/180 GF/s 512 GB IBM 5.6/11.2 GF/s 16 GB BlueGene/P Teraflops 2.8/5.6 GF/s 1.0 GB 1000 4MB I IBM BlueGene/L® 100 IBM Deep Blue® 10 US Dept. Of Energy ASCI 1 1995 2000 2005 2010 2020 Source: ASCI Roadmap, IBM, Supercomputer Conf., 2004 Brain ops/sec: Kurzweil 1999, The Age of Spiritual Machines Moravec 1998, 39 39 © 2012 IBM Corporation
    40. 40. Ray Kurzweil Predictions Most of the predictions are based on exponential growth of technology (doubles approx. every year)  10 year iteration: 1000x, 20 year iteration: 1 mio fold Cell phones in comparison to MIT computer (in 1965) are today  1000 times more processing power  1 mio times smaller  1 mio times cheaper  1 bio times increase in price/performance Compute power that was 40 years ago in a building, is currently in a cell phone, will be in 25 years at the size of a red blood cell 40
    41. 41. Emerging nanotechnology will accelerate progress ofcost of solar panels and storage – fuel cells  Tipping point (cost per watt less than oil and coal) expected within 5 years  Progress on thermo-solar  Doubling time for watts from solar < 2 years  We are less than 10 doublings from meeting 100% of the world’s energy needs 41
    42. 42. 2030: An intimate merger  $1,000 of computation = 1,000 times the human brain  Reverse engineering of the human brain completed  Computers pass the Turing test  Nonbiological intelligence combines  the subtlety and pattern recognition strength of human intelligence, with  the speed, memory, and knowledge sharing of machine intelligence  Nonbiological intelligence will continue to grow exponentially whereas biological intelligence is effectively fixed 42
    43. 43. Ray Kurzweil Predictions (cont.) 2020: Computers have same processing power as humans. 2030: Brain is reverse engineered. Computers can communicate as humans and pass Turing test. Copy of the brain/knowledge can be stored. 2040: Virtual reality will become more exciting than reality. Human beings will be 1 mio times more capable.For more information visit: 43