[2019 oracle code one] code one keynote

For more blog posts, see The Oracle Code One table of contents



Data Science at the Intersection of Emerging Technologies – Krik Borne

  • 30% of revenue comes from ML algorithm (recommendations)
  • Can build new products by combining emerging technologies
  • combinatorial explosion – level above exponential growth
  • Types of discovery – class discovery, correlation or causality, outlier/anomaly/novelty/surprise discovery, association/link discovery
  • Levels of analytics – Descriptive (hindsight), diagnostic (oversight), predictive (foresight), prescriptive (insight), cognitive (360 view)
  • Machine learning = mathematical algorithms that learn from experience
  • Data mining = application of ML algorithms to data
  • AI = apply ML to actions
  • Data science = application of scientific method to discovery and more
  • Analytics = products of ML and data science
  • Power of AI is augmenting what humans can do
  • 4D printing in future – change shape in real time – https://www.sculpteo.com/blog/2017/10/25/4d-printing-a-technology-coming-from-the-future/

A golden age for developers – Greg Pavlik

  • Modern apps are
    • intelligent (use M to suggest and predict))
    • cloud native
    • agile
  • Examples
    • Detect disease up to level of individual plants
    • Go thru resumes and identify best fit jobs. Career progression [both of these are scary!]
  • Cycle: data exploration, build/train model, deploy model, manage model, repeat
  • Model is only as good as the data. The data changes over time.

Fighting Diabetes with Technology – Todd Sharp

  • Traditional Monitoring
    • Monitor blood sugar throughout day. Typically done with glucose monitor with finger prink 6-12 times a day.
    • Count carbs at every meal/snack
    • Formular determines insulin needs
    • Administer insulin at every meal/snack/bedtime
  • Technology helps
    • Continuous glucose monitoring – sensor/monitor below skin. Communicate by Bluetooth/in cloud
    • Insulin pumps. Constant and on demand insulin provided below skin. Again work with smart phone and in cloud
    • Expensive
  • Missing link is counting carbs and calculating insulin
  • Created an app
    • Full mode includes insulin calculation.
    • Quick mode to just count carbs
    • Formula based on meal/time of day
    • Enter data by a picture or voice. Have to weigh portion – uses Bluetooth scale
    • Can handle raw food (apple) or packaged food (graham cracker sticks)
    • Glucose meter pairs with app via Bluetooth as well to get current value
    • With all of this, can calculate number of insulin units for meal
  • Tech
    • Progressive web app
    • Microservices
    • Oracle Cloud
    • Autonomous DB
    • Serverless
    • Micronaut
    • Materialized view
    • ML – test/train data sets

Autonomous Database for Developers – Maria Colgan

  • Many types of database (relational, graph, etc)
  • No DBA support needed
  • Showed wizard to create database. Serverless is an option
  • Automatically identifies and adds missing indexes after confirms they will improve performance
  • Elastic scaling
  • Can clone database with a wizard (with or without data)

My take

Parts of this were interesting. Others felt more like a commercial. I liked the diabetes story. The whole thing captured my attention. It felt like it didn’t fit with the others though. I also noticed a lot of people leaving immediately after Todd’s talk. So it looks like a lot of people came specifically for that. I left before the end of the Autonomous Database section. At the two hour mark of the keynote, I needed to get up!

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