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

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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!