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The Modern Columbian Exchange: Biovision 2012 Presentation
The document outlines the concept of the modern Columbian exchange as a manifestation of globalization that introduces challenges, particularly in managing complex interconnections of technology, lifestyles, and diseases. It emphasizes the importance of leveraging human intelligence and big data to tackle these complexities, proposing new strategies for data utilization and real-time decision-making. The authors call for immediate action to transform available data into actionable knowledge to enhance community well-being and scientific advancements.
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The Modern Columbian Exchange: Biovision 2012 Presentation
- 1. The Modern ColumbianExchange New Threats Require New Thought and Action Susan Bennett, B.Sc. Systems Design Engineering, Francois Sauer, M.D., M.B.A., M.S. Systems Analysis, Ronald E. LaPorte, Ph.D., Professor of Epidemiology, University of Pittsburgh, Mihwa Cha, M.S. Mathematics © 2012 CrossInnovation, LLC 1
- 2. Agenda • What isThe Modern Columbian Exchange? • Why does it matter? • Why Human Intelligence? – Our limitations – Our strengths • What are the Big Data Opportunities? – What does this mean for transforming repositories of information? • The Time is NOW…. © 2012 CrossInnovation, LLC 2
- 3. What is theModern Columbian Exchange? …It is our current interconnected world. Globalization introduces new challenges in: • Technology • Ways of Thinking • Lifestyles • Animals • Plants • Diseases © 2012 CrossInnovation, LLC 3
- 4. What is TheModern Columbian Exchange? These challenges, characterized by complexity and Big Data, threaten our physical, mental and social well-being. BUT!!! This crisis also offers a great opportunity to leverage human intelligence using “Big Data” to better manage our circumstance CrossInnovation.NET, LLC Confidential 4
- 5. Why Human Intelligence? …because it is our best resource to tame complexity although we have limitations…. • Experience-dependent Categorization / Functional Fixedness • Cognitive Bias • Working Memory • Lineal thinking BUT “…every move we make that constrains complexity also blocks off opportunity”. (Stafford Beer, 1979) CrossInnovation.NET, LLC Confidential 5
- 6. What is BigData? • Volume • Variety • Variability • Speed © 2012 CrossInnovation, LLC 6
- 7. Signs and Symptoms– Limitations in: • The use of all the data, information and knowledge available • The distribution of the decisions within the organization to benefit from big data • The speed to which new evidences question the current paradigm • The capability to embrace and respond JIT to the complexity of our circumstance • The use of collective wisdom to select actions that are “ecological” in the long term Exploitation of Big Data © 2012 CrossInnovation, LLC 7
- 8. How can weharvest the potential of Big Data? How can human intelligence be effectively leveraged to develop new knowledge within a context of Big Data? How does this impact the design and pragmatic use of data and information repositories for the development of sciences and our world community? © 2012 CrossInnovation, LLC 8
- 9. Big Data: AForce to Be Harnessed © 2012 CrossInnovation, LLC 9
- 10. Real-time Access toBig Data…. • Empowering the Scientific Community to: – Quickly identify the sources of the pandemic – Harvest accumulated experience from previous pandemics • Using Associative Memories to ingest data from clinics, people, industry sources, Internet, Social Media, etc. and learn about what is connected with what, who is connected whom, where, when, how and how much • Using Reasoning methodologies (classification, trending, nearest neighbour analysis) to understand patterns, possible causes-and-effects © 2012 CrossInnovation, LLC 10
- 11. Real-time Access toBig Data…. • Empowering the Scientific Community to: – Assess recommended courses of actions • Using Associative Memories to assess potential consequences (anticipate) – Monitor the impact of courses of action (outcomes) • Using Associative Memories to monitor impacts of courses of action – Learn • Associating situation-action- outcome and relative effectiveness across various population groups and specifics related to demographic and clinical data © 2012 CrossInnovation, LLC 11
- 12. Transforming Repositories • Time-sensitiveinformation and knowledge: – Compare/contrast with similar materials that are more recent • Discoverability: – Associative Memories for Classification or Nearest-Neighbor analysis reasoning (what is ‘similar’ or ‘analogous’ to this item?) – Episodes, trends • Feedback: – Wiki’s and the discoverability of feedback © 2012 CrossInnovation, LLC 12
- 13. Big Data fromAccumulation to Action • The Scientific Supercourse is a concrete manifestation of the abundance of data, information and knowledge available. • The challenge is how to harvest its great value moving from a static paradigm of “accumulated information” to a dynamic paradigm of “actionable knowledge for a specific purpose”! “Science advances by overthrowing an existing paradigm, or at least substantially expanding or modifying it. Thus there is a certain constructive sub-versiveness built into the scientific enterprise, as a new generation of scientists makes its own contribution.” - Dr. Ismail Serageldin © 2012 CrossInnovation, LLC 13
- 14. The Time is“Now” Human Human Information Human System Sense Making – What Was System System Connected with What? Observe What Is? Criteria & Standards Decide Measure Speed = Orient Reasoning Act Lower Cost Monitor /Learn Entity Analytics + Control Anticipating Level of Integration Decide Passive Active Cooperative © 2012 CrossInnovation, LLC 14
- 15. The Time is“Now” (cont’d) • Associating data and information in real-time • Providing pattern recognition across structured and unstructured data • Supporting human learning • Finding relevant small data in Big Data • Scaling in a way that facilitates the connections across massive networks. ….making humans more human, enabling decision makers to use the good of The Modern Columbian Exchange to manage its complexities. © 2012 CrossInnovation, LLC 15
- 16. THANK YOU! © 2012 CrossInnovation, LLC 16
- 17. APPENDIX SLIDES © 2012 CrossInnovation, LLC 17
- 18. Hard problems solvedby Saffron • Unification of diverse data – Symbol vectors stored with matrices, beyond graphs • Unification of semantics and statistics – Statistical metrics as well as semantic sets • Automatic, incremental, nonlinear learning – No parameters, no batch-fitting, no knowledge engineering • Exploitation of nonlinear and nonfunctional patterns – No abstracting reductionism to rules or functional models • Finding the relevant small data in Big Data – Real-time nearest-neighbor reasoning, when the central limit fails • Scalability to massive network of networks – Localities, partitions, and compressions: Smaller is also faster CrossInnovation.NET, LLC Confidential © 2012 Saffron Technology, Inc. All rights reserved. 18
- 19. Memory Physics: Smalland Local is Fast • Compared to a database, a Compared to Tables and Graphs memory-base responds to • Pre-joined No Table Joins queries faster and faster as data • Pre-counted No Table Scans grows larger*. – *As the number of observations • Pre-ordered No Sort Joins exceeds the number of • Colocal No Pointer Chasing attributes, which is a common property of real world observations. • Therefore, evolution selected for brains to be memory-bases, not databases. Some “Proofs in the Pudding” • 10B associative triples in Global 100 operations using 48 cores on 2 servers • Near-linear scalability of ingestion (0.87 slope) tested from 1 to 100 cores • Distributed cluster installation and management tested to 64 server nodes • Semantic expansion of 2X at recent customer, world-record 20 bytes/triple CrossInnovation.NET, LLC Confidential © 2012 Saffron Technology, Inc. All rights reserved. 19
- 20. What’s the Solution? • Real-time decision support: Pre-joined, pre-scanned, real- time decision support for complex, high dimensional vector problems: Sense Making > Reasoning > Prediction • Democratized: business analysts don’t require consistent IT intervention for statistical models • Learning: transactional updates and predictive models, human in the loop: Situation > Action > Outcome © 2012 CrossInnovation, LLC and Saffron Technology, Inc. All rights reserved. 20
- 21. Expansive Application Valueof Memory Reasoning Connections – knowing who / what is related to whom / what, and returns entity ranking based on connectivity frequencies and context Network – seeing how entities in a list (a set) are connected; returns connectivity or bipartite graph of given entity set Analogies – knowing who / what is similar to whom / what, and returns nearest neighbor based on information of features & relationships Classifications – Making experience-based, adaptive decisions; returns class rank based on nearest neighbor or hetero-associative match Trends – Associations that have the most change of timeframe; returns connections based on a temporal change metric Episodes – Historical attribute patterns and timeframes; recalls co-associated entities with repeating timeframes CrossInnovation.NET, LLC Confidential © 2012 Saffron Technology, Inc. All rights reserved. 21
- 22. Use Cases: NationalSecurity Who is related to whom? Associative Targeting for SF/SOF 500,000X faster to read everything Who is similar to whom? Alias Detection in Foreign Intel Agency 1 “Super human” 93% accuracy Database 1 Database 2 Agency 2 What have we done before? Experience-based ISR Tasking Knowledge over change of taskers CrossInnovation.NET, LLC Confidential © 2012 Saffron Technology, Inc. All rights reserved. 22
- 23. Use Cases: Logistics/ Supply Chain What/Who/Where Are Parts Like Me? Where else do we use this Part or a Similar Part? Have We Seen This Before? Where, When, Who, Why? How did it turn out? Where Else Might This Happen? What other vehicles look like this problem? How Does this Affect Us? Real time Associative analysis of Incoming Information – web, email, documents, etc. Global Risk/Threat Classification 23 CrossInnovation.NET, LLC Confidential © 2012 Saffron Technology, Inc. All rights reserved. 23
- 24. What is TheModern Columbian Exchange? “Health is a state of complete physical, mental and social well- being and not merely the absence of disease or infirmity”. WHO …the development and sharing of Sciences becomes critical for the prevention, surveillance, and containment of the negative consequences of these outcomes – which threaten health, freedom, stability and prosperity. This new situational awareness creates significant considerations and investments for governments and commercial enterprises. © 2012 CrossInnovation, LLC 24
Editor's Notes
- #4 Technology: How is China displacing Germany and US in solar technology?Ways of Thinking: How is the nuclear tragedy in Japan transforming in France and Germany the public perception about the safety of nuclear plants?Lifestyles: How expectations about the role of the women in society are define in different cultures?Animals: How are pitons invading the Everglades in Florida?Plants: How are perceived GM seeds as a solution or a threat by different communities?Diseases: How was Sars quickly distributed around the world?
- #5 “Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity”. WHOIncreased connectivity between humans, humans and machines and between machines create a web a relationships that generate counterintuitive behaviors and turning points enable through feedback loops and delays existing within the system .Now Big Data can leverage Natural human intelligence to manage and tame this interconnectedness! Big Data are the fuel of the Idea economy. Today we are just starting to extract their energy and value.The harvesting of the energy and value of “Big Data” poses societal challenges such as: (McKinsey, 2011): A 40% projected growth in global data generated per year;5% growth in global IT spending140,000-190,000 “data scientists” needed.
- #6 On the other hand Human Intelligence has three very unique attributes:Creative imagination leveraged by the values of sciences described by Dr Ismail SerageldinCommon sense leveraged by experience andWisdom and ethic leveraged by the listening of our inner voice“Science sans conscience n’estqueruine de l’ame” PasteurThere is a key distinction between the finding of sciences that are grounded in observed facts and the application of these scientific findings which are grounded in the intention of the decision maker. This intention is what manifests the wisdom and ethic of the decision maker.“Between the scalpel of a surgeon and the knife of an assassin there is just a difference of intention”.
- #7 Big Data can help to respond in an accurate and timely way to prevent loss of life, and lifestyle, including property, possessions, health, and community. Especially when resolving a new threat. Traditional databases are challenged to effectively and efficiently extract the value of Big Data. The leverage the value of Big Data today we want to be able to:Associate information in real-time: Define and support complex, high dimensionality problems – immediately understandingwhat is connected with what, when, where, how and how much;Recognize pattern integrating structured and unstructured data: Quickly adapt to the complexity of the situation and the life-impacting concerns. We want decision support systems that can learn in real time;Support team work:Bridging multiple experts across multiple domains to share information and learning is critical for timely coordinated success;Find relevant small data in Big DataThe occurrence of ‘one’ can be significant for understanding. The real-time nearest neighbor reasoning is a powerful approach to leverage human intelligence;Scalability to massive network of networksWhen dealing with coordination across multiple regions or countries, scalability becomes a key concern.
- #8 Signs and Symptoms demonstrating the limitations in the current use of Big DataThe decision making process is not visible just as the root of a tree, although we know the root system underground supports the health of the branches that are visible. The effectiveness and efficiency of our decision making can be expanded with the exploitation of big data just as a tree with healthy root system can better access available nutrients to manifest to the fullest its essence.
- #9 To harvest the value of Big Data and transform the static paradigm of “accumulated Information” into a dynamic paradigm of “actionable knowledge for a specific purpose”,we want to answer these two questions.Today we witness a metamorphosis of what our explicit knowledge now is:Multimedia “including text, voice, image, video, virtual reality” instead of written in stone or in a book.Dynamic instead of static.Systemic instead of a simple lineal cause and effect relationship.Specific “we speak about actionable knowledge” within a specific context instead of generic “how to”.
- #10 Christopher Columbus in 1492 didn’t just sail the ocean blue. He launched an ecological revolution. The same Vint Cerf, the recognized intellectual father of the Internet, started a knowledge revolution including its impact through social media.Until 200 years ago, because the amount of knowledge was limited, the analysis and synthesis of it was straightforward and accomplished without much use of tools. Now that the amount of knowledge is many orders of magnitude larger than what we can assimilate and memorize, it becomes a requirement for effective decision making to use tools in order to select relevant information, and tools to help analyze and synthesizing the information. When people were using oars, they were at the mercy of the wind. Square sail technology appeared around 1200 B.C. It was very good for downwind sailing, acting similar to a parachute. Triangular fore-and-aft sails made their earliest appearance in 3 A.D. and essentially harvested the wind with the same principle as lift for airplanes. They improved upwind sailing ability and speed. Christopher Columbus combined technologies providing speed and maneuverability. Today associative memories enable us to ingest data with no need to predefine the question we want to answer and use different reasoning methods to extract in real time relevant “actionable knowledge”.
- #13 There are several proven and tested technologies that can address these challenges. One technology which we observe to be especially relevant is based on Associative Memories. In this approach, similar to how the human brain works, a ‘memory’ is created for every entity. There may be a memory of a given expert, a memory for a given procedure, etc. In Associative Memories, each observation is recorded with its context – what is the connection of this memory with other memories, in what context, and how many times was this observed? This forms then the basis of a true, real-time knowledge–store against which a variety of reasoning methodologies can be performed. This technology represents a significant opportunity to harvest and tame the power of “Big Data” in a way that is coherent with human cognition.
- #15 We propose that the platform of the future will leverage the advancement of sciences and technology, speeding the cycle of observing, orienting/learning, deciding, and acting