Gerri Martin-Flickinger began her career at Chevron in 1985, doing AI work in a research mode.
“I went to Chevron, the oil energy company. Spent my early years there and did some really cool AI work while I was there”
Person
Gerri Martin-Flickinger
1 episodes · 17 quoted claims
Martin-Flickinger built a neural net in the Lisp language as her senior project at Washington State University.
“my senior project with a neural net that was built in Lisp, which is nobody even remembers what that is anymore.”
Martin-Flickinger became the first chief information officer of McAfee in the late 1990s.
“I became the 1st CIO for McAfee in the late 90s, when McAfee was still quite small but grew quite large.”
McAfee antivirus customers received monthly updates of new virus signatures, making it work like a subscription business.
“you would buy your antivirus software, but then you would get these payloads every month that would be the new virus signatures to keep protecting your machine.”
Martin-Flickinger spent about ten years at Adobe as CIO, helping move its products to a cloud subscription business.
“became the CIO for Adobe and was at Adobe for about ten years. And part of the team who migrated their product offerings into the cloud”
Martin-Flickinger joined Starbucks as its first chief technology officer about six years before the interview.
“joined Starbucks a little over six years ago as their first chief technology officer”
Starbucks uses the name Deep Brew for a broad set of AI projects across the company.
“we have a moniker, Deep Brew, which stands for a broad section of AI projects underway across the company.”
Martin-Flickinger says credit card companies have used embedded AI and machine learning for fraud detection for a long time.
“Your credit card companies have had it probably longer than you even realize for fraud detection.”
Starbucks uses machine learning models to build store labor schedules, unnoticed by store managers.
“doing models for labor scheduling.”
Starbucks drive-through digital displays are driven by personalization models using inputs like buying patterns, region, weather and stock.
“when you pull into a drive-through where they have a digital display, those experiences are being driven from models that are based on lots of different inputs.”
Lattes are made on demand from components such as espresso and milk, which complicates inventory-aware promotion.
“lattes are manufactured in the moment at a store, and they're made of component parts.”
Martin-Flickinger said Starbucks's scale of stores worldwide, each a small business, drew her to the company.
“I was intrigued by the scale, and the scale is interesting when you think about Starbucks.”
Martin-Flickinger cited a store in Oklahoma on a dial-up line as an example of Starbucks's infrastructure challenge.
“When you've got a store in the middle of Oklahoma on a dial-up line, that's a whole different thing to manage.”
After joining, Martin-Flickinger spent her first few weeks working in Starbucks stores to learn the business.
“I spent my 1st few weeks in a store learning about how people make lattes.”
About 90 days after joining, Martin-Flickinger renamed Starbucks's IT department Starbucks Technology.
“90 days after I joined, changed the name of IT to Starbucks technology. Never use the word IT again.”
The Starbucks Technology tagline is 'talented technologists delivering today, leading into the future'.
“Super simple, talented technologists delivering today, leading into the future Starbucks technology, that's it.”
Martin-Flickinger said Starbucks operates over 30,000 stores worldwide (the transcript renders this as '30 zero').
“Cause today there's over 30 zero stores around the world”