Page 4 - summer of ai

4 DATA & ANALYTICS
SUMMER OF AI JULY 2019
Analytics
Artificial Intelligence
Learn from Experts
Learn from Data
Learn from Simulations
Expert Systems
Rote Learning
Connectionist Computing
Statistical Computing
Symbolic Computing
Analogy Based AI
Reinforcement Learning
Evolutionary/ Nature Inspired Computing
Standard Neural Networks
Deep Neural Networks
nfidential and Proprietary
Stacked Auto- Encoders
Recurrent Neural Networks
Convolutional Neural Networks
Co
Overview
Framework for learning
Customers make smarter decisions when they go beyond logistic regression and extract meaningful insights from data with the latest AI technologies
Christopher Yasko likes to talk about the cool applications of how artificial intelligence (AI) and machine learning (ML) are used in the industry. He winces whenever somone asks, “if the lab is experimenting with self-driving cars,” a sign of his
When Chris delivers this statement, he pauses. Whether the pause is for dramatic effect or to draw in the audience, he gets a similar reaction from the audience: “So, what do you guys at Equifax do with AI if you’re not doing self-driving cars?” Chris smiles, and proudly states: “Our focus in the lab is inventing explainable AI, using ML for data perfection, and creating novel AI-powered tools.”
If you have ever listened to science text books on tape, then you can imagine Chris’ inspired tone to teach his audience: “We organize artificial intelligence in a framework around the way machines mimic human intelligence: Learn from Experts, Learn from Data, and Learn from Simulations.”
aversion to viewing AI as another popular trend.
Whether on a call with investors or in front of an auditorium full of other data scientists, Chris draws rhetorical bright boundaries because he views Equifax’s investment in AI as an opportunity to provide more consumers access to credit: “Nope, we are not doing any AI research on self-driving cars... “