IBM Briefing Hva med 2017?

Transcription

1 IBM Briefing Hva med 2017? DnD Februar 2017 Stein F. Andresen

2 The recent evolution of the GTO: It s all about Data Cloud Mobile Social Internet of Things Volume Velocity Variety Veracity Confluence of Social, Mobile, Cloud, Big Data, and Analytics Systems of Insight Data Transforming Industries

3 The recent evolution of the GTO: It s all about Data Cloud Mobile Social Data Internet of Things Volume Velocity Variety Veracity Confluence of Social, Mobile, Cloud, Big Data, and Analytics Systems of Insight Data Transforming Industries Data will disrupt entire industries

4 The recent evolution of the GTO: It s all about Data Cloud Mobile Social Data Internet of Things Volume Velocity Variety Veracity Confluence of Social, Mobile, Cloud, Big Data, and Analytics Systems of Insight Data Transforming Industries Data will disrupt entire industries

5 Global Technology Outlook: Recent Themes and Impact

6 Trend: Value in IT Industry is Shifting Automating the World Understanding the World Moore s Law Graph Analytics Genomics Social Networks Security Healthcare Education Internet of Things Machine Learning Video, Speech Analytics Object recognition Complex video analytics Multi-model analytics

7 Application Groupings Business Imperatives Characterized by: Availability Data requirements Performance Skills Rate of change / Stability Systems of Engagement (Human interactions) Systems of Record (Business transactions) Systems of Insight Drive every decision Fuel every interaction Power every process Systems of Automation (Machine interactions) Hybrid Cloud Open Source Security Cognitive

8 Analytics Capabilities Are Arrayed Along A Spectrum Pick The Right Tool For The Job i2 Watson Analytics Descriptive Discovery and Exploration. Cognos Watson Explorer Diagnostic Reporting Analysis, Content Analytics SPSS Modeller Predictive Uncover likely behavior or system actions that will occur CPLEX Watson Developer Cloud Prescriptive Determine a set of alternative actions / decisions given a complex set of objectives, requirements, and constraints, to improve business performance Cognitive Systems learn and interact naturally with people to extend what humans and machines do on their own.

9 What does Cognitive Computing do? UNDERSTAND Streamed Sensors 1. Understands Big Data Text Structured Structure Context Meaning Images Videos ANALYZE Supervised learning (DETECT) 2. Mines and finds patterns Speech Sound Unsupervised learning (DISCOVER) REASON 3. Evaluates possible options Attributes LEARN 4. Learns and improves Train and learn Create problem statement ID similar problems Generate hypotheses Model Evaluate hypotheses Get feedback Present results Continuous Machine Learning Generate hypotheses Identify evidence Evidence Score hypotheses Score evidence

10 What can a Cognitive System do? ENGAGE 1. Engages in natural language Dialog Q&A Interaction Intent Advice Seamless Human-Machine Interaction Deeper Customer Insight Contextual Awareness Insight Customer Goals Preference Behaviour Sentiment Context EXPLORE 2. Explores Big Data Detect Patterns Discover Anomalies DISCOVER 3. Discovers new insights Insight (Applied Knowledge) Knowledge (Meaningful Information) Information (Organised Data) Data (Facts) DECIDE 4. Decides and acts Cognitive Analytics Answer Questions and Solve Problems Predict Outcomes Human Input Decide Decision Support Prescribe Next-Best-Actions Decision Automation Act How does IBM define cognitive? It s a solution that understands, reasons and learns, while interacting with humans.

11 Implications of New Workloads Noisy Unstructured Data Complexity Data Accurate Structured Reliable Resilient Task Complexity Deterministic Computation Stochastic

12 Questions?