People of AI

By Google

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Subscribers: 4
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Episodes: 9


People of AI is a podcast showcasing inspiring people with interesting stories in the world of Artificial Intelligence (AI) and its subset, Machine Learning (ML). The podcast will interview leaders, practitioners, researchers and learners in the field of AI/ML and invite them to share their stories, what they are building, lessons learned along the way, and excitement for the AI/ML industry.

Episode Date
Kind and helpful Machine Learning through UX research

Meet Michelle Carney, a Machine Learning User Experience Researcher at Google. Join us as we learn how her careers in music, neuroscience, teaching, and machine learning have informed her ability to understand how people use Machine Learning tools, and provide better feedback to help make these tools more useful, helpful, kind, and inclusive of all types of user experiences. 



Visual Blocks for ML: 

Tone Transfer: 

PAIR Guidebook: 

Machine Learning and UX (MLUX) Meetup Resource: 
What is Machine Learning + UX?: 

Stanford on Designing Machine Learning: 

TensorFlow website → 


Michelle Carney Links




Machine Learning and UX (MLUX) Meetup Resources:
What is MLUX?:
MLUX twitter (@mluxeetup):
MLUX meetup (you can see all of our past talks here!): MLUX youtube (all of our past recordings!):
MLUX linkedin company page: 


Guest bio: 

Michelle Carney is a Computational Neuroscientist turned User Experience (UX) Researcher, whose practice focuses on the intersection of Data Science and UX. Currently a Senior UX Researcher on Google’s Tensorflow Team, Michelle's projects focus on combining Machine Learning and UX. Her work includes Magenta’s latest Tone Transfer project and People + AI Research team. Outside of work, Michelle organizes the Machine Learning and UX Meetup, and teaches at the Stanford on Designing Machine Learning.

May 18, 2023
How to think about and build AI responsibly

There is a whole team at Google dedicated to designing AI best practices. They are committed to making progress in the responsible development of AI and share reliable, effective user-centered research, tools, datasets, and other resources with users. Meet one of the members of the team, Christina Greer, as she shares the in’s and out’s of working in the field of Responsible AI and how her personal experience and values make her a key player in this space!


AI Principles: 

Responsible AI practices:

Guest bio:
Christina Greer is a software engineer at Google Research. A veteran of a variety of efforts across the company including ads, data processing pipelines, and Google Assistant, she joined Google Research in 2018 to focus on bias and fairness in ML. Since then, she has built both teams and software to support measuring and mitigating ML models for bias, and consults with products across Google to support building safer products that work for everyone. In her spare time, Christina is a creative writer and a mom of 2 great kids. 



May 04, 2023
Building an inclusive community in the field of Machine Learning

Meet Joana Carrasqueira as she talks about her amazing ability to grow community in the field of machine learning. Join us as we hear about her extraordinary journey from the non-profit sector to business and most recently into tech and how she leverages her superpower of bringing people together and fostering a culture of belonging.


WiML → 

WiML Blog post → 

Watch all the WiML 2022 sessions → 

Favorite book: The Adventures of Women in Tech: How We Got Here and Why We Stay 

Simple ML for Sheets → 


Guest bio: 

Joana Carrasqueira is the Developer Relations Lead at Google for the TensorFlow Community. She is committed to fostering healthy open source communities and to enable developers to solve impactful problems at scale. Prior to Google, she worked on innovation consulting for Forbes top 500 and served as Education Manager at the International Pharmaceutical Federation, working closely with WHO, UNESCO and the United Nations. Joana holds an MBA from IE Business School and a Master in Pharmaceutical Sciences.




Apr 20, 2023
The secret sauce to creating amazing ML experiences for developers

From developing programs on a Pentium computer as a kid and programming in Visual Basic 6 to becoming a leader in software development for Machine Learning on the Web, join us as we learn about Gant’s journey to where he is today. And the secret sauce to all this? Gant’s creativity and curiosity that he mixes into his work, creating fun and amazing experiences for developers around the world. 


Learn more about how to be a Google Developer Expert → 




Company: Infinite Red: 

Title: CIO – Chief Innovation Officer



Twitter: @GantLaborde 






TensorFlow.js Book: 

All Books: 


Stuff Gant has made: 

Harry Potter-inspired AR Sorting Hat: 

Enjoying the Show: 

Time Warp Scan 


AI Trainable Tic Tac Toe:   

Rock Paper Scissors: 

TensorFlow.js - RGB channels to Red-Green Color Blind: 


Guest bio: 

Gant Laborde is the owner of Infinite Red and author of the popular O’Reilly book, “Learning TensorFlow.js”. By day he is a mentor, adjunct professor and award-winning speaker. For 20 years, he has been involved in software development, and is recognized as a Google Developer Expert in Web and Machine Learning. By night he is known as an “open sourcerer”, aspiring future mad scientist, illustrator and appears as an avatar in his latest children’s book, dedicated to his daughter and wife.


Apr 13, 2023
Rocks, data science, and breaking into Machine Learning

Meet Catherine Nelson, Principal Data Scientist at SAP Concur and author of the upcoming O’Reilly book “Software Engineering for Data Scientists”. Join us as we talk about Catherine's amazing career journey as she pivoted from geophysicist to working on setting the standard for building machine learning pipelines. According to Catherine, it all starts with how you prepare and train your data!  


Building Machine Learning Pipelines → 

Software Engineering for Data Scientists → 

TensorFlow Meets → 

Twitter → 

LinkedIn → 


Guest bio:

Catherine Nelson is a data scientist and author of the upcoming O’Reilly book “Software Engineering for Data Scientists”. She is a Principal Data Scientist at SAP Concur, where she explores innovative ways to deliver production machine learning applications which improve a business traveler’s experience. Her key focus areas range from ML explainability and model analysis to privacy-preserving ML. She is also co-author of the O'Reilly publication “Building Machine Learning Pipelines", and she is an organizer for Seattle PyLadies, supporting women who code in Python. In her previous career as a geophysicist she studied ancient volcanoes and explored for oil in Greenland. Catherine has a PhD in geophysics from Durham University and a Masters of Earth Sciences from Oxford University.


Apr 06, 2023
Machine Learning on the web

Meet Jason Mayes, the public face of Web ML at Google and host of Made With TensorFlow.js. Join us as we talk about Jason’s journey and mission to make machine learning easy, fun and accessible on the web and how getting into the field of machine learning has never been easier.   


Made With TensorFlow.js Playlist: 

Learn Web ML on Google Developers: 

Connect with Jason on LinkedIn: 

Connect with Jason on Twitter: 

Connect with Jason on Discord: 

Guest bio: 

Jason Mayes is the public face of Web ML at Google. He helps web engineers around the globe take their first steps with machine learning in JavaScript, pushing the boundaries of what's possible in web-based machine learning which has grown exponentially. He also combines his knowledge of the technical and creative worlds to develop innovative prototypes for Google's largest customers and internal teams with over 15 years experience working within web engineering and investigating emerging technologies.


#AI #ML #MadeWithTFJS #WebML

Mar 30, 2023
The language of Machine Learning

Meet Sharon Zhou, an adjunct faculty member at Stanford University and co-founder of Stealth Startup. Join us as we talk about the power and interconnectedness of language as we dive into generative AI models, stable diffusion, large language models, and learn how every problem – according to Sharon – is just a translation problem. 


Check out Sharon’s startup here: 


Learn more about Sharon’s courses here:

Build Basic Generative Adversarial Networks (GANs) → 

Build Better Generative Adversarial Networks (GANs) →  

Apply Generative Adversarial Networks (GANs) →

CS236G Generative Adversarial Networks (GANs) → 


Guest bio:
Sharon Zhou is currently an adjunct faculty member at Stanford University where she defended her PhD (in an impressive 3.5 years) on generative AI models, advised by Andrew Ng. She is also the co-founder of Stealth Startup, working on democratizing access and ease of use of AI by making it easier to program and customize large language models. She has a passion for teaching AI and is currently teaching 80,000 students about GANs, diffusion models and more on Coursera, and was an AI advisor to key AI policymakers in Washington D.C. Fun facts about Sharon: she was the first student in the history of Harvard University to major in Classics and Computer Science, and is featured in MIT Technology Review's 35 Under 35. To top that, she is also a poet.



Mar 23, 2023
What it means to be a person of AI

Meet your hosts, Ashley Oldacre and Laurence Moroney, as we uncover what it means to be a person of AI. We talk about personal and professional journeys, lessons learned along the way, and how to get started in Artificial intelligence and Machine Learning. We share resources to get started and where we see the field going.

Learn about the TensorFlow Certificate Program  →

Watch the AI for Anyone YouTube video series →

All of the cool apps and products we mentioned can be found here →

Powered by TensorFlow: Air Cognizer predicts air quality with machine learning →


Mar 16, 2023
People of AI podcast coming soon!

Join Ashley Oldacre, ML program manager at Google, and Laurence Moroney, ML Developer Advocate at Google, to hear the stories of some incredible people behind machine learning and artificial intelligence. Whether you’re just getting started in AI/ML, or looking to expand your established experience, these stories are for you. We hope you will tune in! 

Mar 08, 2023