Oracle Analytics Summit 2018 Istanbul

Oracle Analytics Summit is held in Istanbul on 2018 Mar, 07. I have been attending this summit since 2016. I mostly enjoy to attend Oracle’s events. This summit is typical of them! Name of the activity is transformed from Big Data and Analytics to Analytics and New Technologies in this year. I’ll summarize the notes of impressing keynotes.

Handling analytics like Einstein’s view of science

Michael Connaughton: AI Strategy

Data gives us feedback, and feedback gives us progress
Why now? Because everything is connected. IOT, Cloud and Big Data.

Samina Rizwan: Rise of ML

In 2016, our expectations are that 100% of customers would move to cloud. In 2018, expectations are changing. Now, we think that cloud and new technologies (Blockchain, AI and IOT) will accelerate the next disruption.
Cloud provides democratization for AI and algorithms!
Highlighting Geoffrey Moore’s quote. AI is from Venus, ML is from Mars. This metaphor is really interesting. The question is that is Mars or Venus closer to the Earth? Actually, the answer is that it depends on time. Even though, these two planets are closest neighbors of Earth, they orbits around the sun move at different speed. But she intend to define ML as more scale-able. AI seeks to understand the world whereas ML just seeks to simulate it.

We also define adaptive intelligence where ML meets AI.

Hale Korkmaz: Age of Intelligence Revolution

MIT AI lab founded in 1959. We just put it on our agenda
Robots are alive. They even have a citizenship
New data sources, computing paradigm and AI reveal data lakes
No matter the structure of data source anymore
Runnable on any kind of workflow (batch or real time)

Pelin Ozbozkurt: AI Age

In 1950, we argue that can machines think argument raised by Turing. In 1980, the arguments is transformed to can machines understand. This is Chinese Room Argument raised by John Searle. Now, we argue that can machines think and understand like human

chinese-room-argument — Chinese room argument representation. Man in the middle doesn’t have to know Chinese.

Data feeds AI, and AI produces data. Produced data feeds AI again. That is a infinite loop.
Short term economic value will come from Deep Learning.
We have been talking fraud detection is almost 20 years. But now, we can do it better. This is like Einstein’s memory. A student asks Einstein that aren’t these the same questions as last year’s psychics exam and Einstein responds him that yes but this year answers are different. The question might be still fraud detection but answer is different. Answer was random forest for yesterday, but today answer is absolutely deep learning.

einstein-same-question — Einstein’s dialog with his student about science

Previously, AI enabled process begins with human and ends with ML. Now, it should begin with ML, and end with human. In this way, biases behaviors would be minimized.