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Building Smart Apps for the Future

Femi TAIWO
August 24, 2017

Building Smart Apps for the Future

What are Smart Apps? What makes an app "Smart"? Why are they useful? What tools can I use? How do I get started?
Gave this presentation at the ISDEV Hackathon (https://isdev2017.eventbrite.com)

Femi TAIWO

August 24, 2017
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  1. Smart Apps for the Future ❖ What is a “Smart

    App”? ❖ Examples Around Us ❖ Why build Smart Apps ❖ Getting Started ❖ Conversational Experiences ❖ Resources & Tools
  2. ❖ Manage information ❖ Learn from information ❖ Learn from

    interaction ➢ User ➢ With the physical world What is a “Smart App”?
  3. Provide Actionable Information ❖ Gather Tremendous Amount of Data ❖

    Crunch with Machine Learning ❖ Mix with Predictive Analysis Why is it Smart?
  4. Relates based on any data, including - Personal - Sensor

    - Location data - Events Smart Apps are Contextual
  5. Go to the user with smart recommendations of what to

    do and when, without being asked Anticipate user behaviors and deliver actionable and individualized outcomes. Smart Apps are Pro-active
  6. They continually learn from interactions to become even more relevant

    and valuable Smart Apps Are Living & Breathing
  7. Examples of Smart Apps ❖ Google Maps ❖ Google Photos

    ❖ Facebook News Feed ❖ Netflix ❖ Uber ❖ Personal Assistants
  8. ❖ Users get a more compelling, more prescriptive user experience

    ❖ Support & Enable Key User/Business Decisions ❖ IoT Market To Reach $267B By 2020 Why
  9. ❖ Mining Medical Records for Better Healthcare ❖ Detecting Patterns

    ❖ Personalized Treatment Plans Case Study - Why for Healthcare
  10. Getting Started with Building Smart Apps Start with 3 Key

    Questions - What is the experience you want to deliver? - What kind of data/dataset will provide the information that will drive it? - How will you deliver the information/response?
  11. What are “Conversational Experiences”? They give users new ways to

    interact with your product, service or app by building engaging voice and text-based conversational apps
  12. Conversation Experiences Chatbots They use machine learning to understand what

    users are saying. Extracting: - Context - Entities - Intent
  13. Google Cloud Platform Products Compute Compute Engine App Engine Container

    Engine Container Registry Cloud Functions Networking Cloud Virtual Network Cloud Load Balancing Cloud CDN Cloud Interconnect Cloud DNS Big Data BigQuery Cloud Dataflow Cloud Dataproc Cloud Datalab Cloud Pub/Sub Genomics Storage and Databases Cloud Storage Cloud Bigtable Cloud Datastore Cloud SQL Cloud Spanner Identity & Security Cloud IAM Cloud Resource Manager Cloud Security Scanner Cloud Platform Security BeyondCorp Data Loss Prevention Identity-Aware Proxy Security Key Enforcement Persistent Disk Machine Learning Cloud Machine Learning Cloud Vision API Cloud Speech API Cloud Natural Language API Cloud Translation API Cloud Jobs API Networking
  14. Key Products Cloud Natural Language API Extract information about people,

    places, events and much more, mentioned from text. https://cloud.google.com/natural-language/ TensorFlow Open source software library for machine learning across a range of tasks. https://www.tensorflow.org
  15. Key Products Cloud Vision API Extract information from images, classifies

    and detects individual objects and faces within images, and finds and reads printed words contained within images. https://cloud.google.com/vision/ Cloud Machine Learning Enables you to easily build machine learning models that work on any type of data, of any size https://cloud.google.com/ml-engine/
  16. Every application that is being developed today has to be

    an intelligent app; this is not a recommendation but a necessity.
  17. “Within five years, all major business decisions will be enhanced

    by cognitive (analytic) technologies” - Ginni Rometty (CEO of IBM)