- Cloud computing & big data for service innovation & learning
Cloud computing & big data for service innovation & learning
Cloud Computing and Big Data for Service Innovations & Learning Up till now, most of the adoption of cloud computing focusses on the automation and consolidation of traditional IT services. As such, the gains are confined to the uniformity of control, cost reduction and better governance. Recent adoption of the cloud has gradually moved into tactical and even strategic levels thereby demonstrating a high level of gains for using the cloud for business transformations and innovations. Such benefits include dynamism in business model compositions and speed and ease in orchestrating service innovations in the cloud. This talk will shed light on how massive and rapid accumulation of data in the cloud can support human-machine cooperative problem solving and re-define the landscape of Open Innovation and Connectionist Learning via a Knowledge Cloud.
<ul><li> 1. Cloud Computing & Big Data for Service Innovation & LearningProfessor Eric TsuiKnowledge Management & Innovation Research CentreThe Hong Kong Polytechnic University </li></ul>
<p> 2. Services as % of GDP in OECD countries 3. Co-creation of value Dynamic Capabilities Enabling Vs Disruptive Open Business Models Customer Experience => Efficiency, Integration & TransformationSome key concepts in Service InnovationProfessor Ian Miles, MBSProfessor Eng Chew, UTS 4. Customers to co-design in a process DELL Computers & Taggerbags 5. Definition of Cloud Computing 6. 1.On-demand & self- service2.Broad network access3.Resource pooling (location independent)4.Rapid elasticity5.Agility6.Measured service (& mostly postpay)Characteristics of the Cloud 7. Fulfillment By Amazon (FBA) (Replay video at http://amazingsellingmachine.com/how-to-scale/) 8. SAPs The SUPPLY UNCHAINED Cloud? 9. Microsofts Azure cloud helps winning the Formula 1 race? 10. A cloud connects computers, data and people at a massive scale 11. A cloud connects computers, data and people at a massive scale 12. 1.Machine to Machine2.People to Machine3.People to PeopleThree types of connections in a cloud 13. 70 billions connections & 1/3 of consumer digital content in the cloud by 2020 & 2016 respectivelyIn July 2012, there were 955m users in FacebookIn 2012, about 2.5 exabytes are created every day and is expected to double every 40 months. An exabyte is 10,000 times of a petabyte (approx 20 million filing cabinets) 14. The Knowledge Cloud 15. Think Outside The BoxThe Cloud as some massively scaleable backend resources with low upfront costsIntelligent Knowledge Centre with massive data, problem solving skills (processors & humans), & dynamic computational powerThe Cloud is Disruptive 16. Human-machine cooperative problem solving 17. PolymathoOnline discussions about mathematical problemsGenBankoWorlds online repository of genetic dataGalaxyZooo200,000 online volunteers to help astronomers classify galaxy imagesHarnessing Wisdom of the Crowd 18. Any spiral? Which direction? 19. Amazon Mechanical Turk 20. Recaptcha (Human-assisted inexact matching) 21. Replay Webinar at http://webvideo.polyu.edu.hk/p99237461/ 22. CDC detection of an epidemic outbreakAirline ticket pricesOrange car is least defectiveMail to teenager promoting maternity productsAmazon's recommendation engineMatch-fixing in Sumo wrestlingSocial Network Analysis for VulnerabilityUPS Fleet MaintenanceReCaptchasGoogle translationRe-discovery of the English languageHealth & Credit check (by banks & insurers)Big Data applications & cases 23. Speed of making decision more important that causal reasoning (Knowing WHAT first; knowing WHY later)Trade "exactness" for "approximate" to support fast decision makingTo improve the performance of your algorithm, try feeding it with lots more data (instead of modifying the program)Re-wiring our brain (impact of Big Data & IoT) 24. HKPolyUX MOOC on KM & Big Data (to be launched in Aug 2015)</p>