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.
Kind and helpful Machine Learning through UX research
29:05Meet 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. Resources: Visual Blocks for ML: https://goo.gle/3OfanzO Tone Transfer: https://goo.gle/3On9xku PAIR Guidebook: https://goo.gle/3Mx4Gff Machine Learning and UX (MLUX) Meetup Resource: https://goo.gle/mluxresources What is Machine Learning + UX?: https://goo.gle/42KWHB3 Stanford d.school on Designing Machine Learning: https://goo.gle/3OeRaOJ TensorFlow website → https://goo.gle/3BwLZSN Michelle Carney Links Twitter: https://goo.gle/3WfxMDc Linkedin: https://goo.gle/432u0PG Machine Learning and UX (MLUX) Meetup Resources: https://goo.gle/mluxresources What is MLUX?: https://goo.gle/42KWHB3 MLUX twitter (@mluxeetup): https://goo.gle/436wGMo MLUX meetup (you can see all of our past talks here!): https://goo.gle/41QpMts MLUX youtube (all of our past recordings!): https://goo.gle/42Ipt5a MLUX linkedin company page: https://goo.gle/45c5oWM 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 d.school on Designing Machine Learning.
How to think about and build AI responsibly
27:16There 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! Resources: AI Principles: https://goo.gle/3VrCpJP Responsible AI practices: https://goo.gle/41XVeqI 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. #AI #ML
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Building an inclusive community in the field of Machine Learning
32:44Meet 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. Resources: WiML → https://goo.gle/3GRW939 WiML Blog post → https://goo.gle/3GS19Fi Watch all the WiML 2022 sessions → https://goo.gle/3Ld11mb Favorite book: The Adventures of Women in Tech: How We Got Here and Why We Stay → https://goo.gle/3UM5sHV Simple ML for Sheets → https://goo.gle/3mMhN29 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. #AI #ML
The secret sauce to creating amazing ML experiences for developers
30:45From 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 → https://goo.gle/3oaXxr7 Resources: Website: https://goo.gle/3GFCWlc Company: Infinite Red: https://goo.gle/3KWDzcW Title: CIO – Chief Innovation Officer Social Twitter: @GantLaborde Medium: https://goo.gle/3ZYmFig GitHub: https://goo.gle/3KUqsJb LinkedIn: https://goo.gle/3muSUrC Books: TensorFlow.js Book: https://amzn.to/3GzR9QK All Books: https://goo.gle/3zR1zYq Stuff Gant has made: Harry Potter-inspired AR Sorting Hat: https://goo.gle/3MAn0ED Enjoying the Show: https://goo.gle/3Uw2zL0 Time Warp Scan https://goo.gle/43vahZQ NSFW JS: https://goo.gle/406OFQN AI Trainable Tic Tac Toe: https://goo.gle/3MA5ErH Rock Paper Scissors: https://goo.gle/3o7r70O TensorFlow.js - RGB channels to Red-Green Color Blind: https://goo.gle/3KAFfYd 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. #AI #ML
Rocks, data science, and breaking into Machine Learning
23:59Meet 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! Resources: Building Machine Learning Pipelines → https://goo.gle/3nLBpDI Software Engineering for Data Scientists → https://goo.gle/3Kz3F5u TensorFlow Meets → https://goo.gle/43a8yZN Twitter →https://goo.gle/3m8b0zq LinkedIn →https://goo.gle/3ZJmd7o 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. #AI #ML
Machine Learning on the web
The language of Machine Learning
29:01Meet 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: https://goo.gle/3TENTJk Learn more about Sharon’s courses here: Build Basic Generative Adversarial Networks (GANs) → https://goo.gle/3lr3AqU Build Better Generative Adversarial Networks (GANs) → https://goo.gle/3JAPgUA Apply Generative Adversarial Networks (GANs) → https://goo.gle/3ZdaoWK CS236G Generative Adversarial Networks (GANs) → https://goo.gle/3TCVhEX 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. #AI #ML
What it means to be a person of AI
28:13Meet 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 → https://goo.gle/TF-dev-certificate Watch the AI for Anyone YouTube video series → https://goo.gle/AIfAnyone All of the cool apps and products we mentioned can be found here → https://goo.gle/3JORHEB Powered by TensorFlow: Air Cognizer predicts air quality with machine learning → https://goo.gle/3JhUaWt #AI #ML
People of AI podcast coming soon!
1:00Join 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!