Amid growing doubt that technology can be a positive force, it’s more important than ever to make sure that we, the AI community, act ethically. There are already several existing AI ethics codes that corporations and governments have published.
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Nitin pushed the limits of his software engineering skills to build important products, but he knew he needed to learn more. After taking the Deep Learning Specialization, he specifically applied to jobs that would allow him to transition from web performance to machine learning engineer.
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Or Cohen's deep background in physics gave him the theoretical foundation to dive into machine learning. Now he's prototyping new models at Lyft to boost the accuracy and efficiency of the ridesharing marketplace.
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Daniel Barbosa Machine Learning Engineer @ Eko Health How did you get started in AI? I’ve been involved in technology for over 20 years, first as a systems administrator and then as a DevOps Engineer....
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Andrew Ng and Vice Minister of Digital Economy Jehudi Castro sit down during a Pie & AI meetup event in Bogotá, Colombia on September 26, 2019. They discuss the future of AI in the global...
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Andrew Ng and Helmuth Trefftz sit down during a Pie & AI meetup in Medellín, Colombia on August 22, 2019. Andrew explains why deeplearning.ai, Landing AI, and AI Fund chose to open their first international...
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Omoju Miller's path to machine learning is anything but straightforward. She first discovered computer science more than twenty years ago as an undergrad at University of Memphis and never looked back.
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In eras of technological disruption, leadership matters. Andrew Ng speaks about the progress of AI, how to accelerate AI adoption, and what’s around the corner for AI at Amazon re:MARS 2019 in Las Vegas,...
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To celebrate the launch of the final course in the deeplearning.ai TensorFlow Specialization, we hosted our third Pie & AI meetup at Google’s headquarters in Sunnyvale! Andrew was joined by TensorFlow Specialization instructor Laurence Moroney,...
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Bryan Catanzaro began his career designing microprocessors. Now he leads a team of 40 researchers pushing the boundaries of deep learning at Nvidia.
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In my line of work--recommending items to users and ranking the items in their searches--the objective is almost impossible to define because the perfect recommendation or ranking does not exist.
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Younes is both Masters student and Lecturer at Stanford University. Rather than cutting-edge research, Younes focuses on AI education. He has developed content for the most popular Machine Learning and Deep Learning courses in the world...
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Andrew Ng and MIT Tech Review’s Senior AI Editor Will Knight close out EmTech Digital on March 26, 2019 in San Francisco. Andrew reflects on how his own experiences leading the Google Brain team and...
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Location: San Francisco, California Age: 33 Education: B.Sc. in Computer Science and Mathematics, 2009, University of Ljubljana, PhD in Computer Science, 2014, Cornell University Years in industry: 5 Favorite movie: Event Horizon (1997) Favorite machine learning researcher: Thorsten...
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How did you first get started in AI? I’ve always loved mathematics. When I was a teenager, I was what I call a semi-professional internet poker player. This left three profound marks on my...
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Abi See made the transition from pure math to deep learning. Now she aims to turn computers into storytellers.
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Working at IDEO has let me work on a wide range of problems: I’ve used clustering and dimensionality reduction to create a prototype that communicates health data while encouraging empathy and engagement. I’ve run traffic simulations to assess the size of delivery markets and prototyped animated, interactive explanations inspired by those simulations. I’ve built internal React web-apps for collecting data and texting customers.
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How is an Applied Scientist different from a Machine Learning Engineer? We went to straight to the source and interviewed Microsoft Applied Scientist Matineh Shaker about how she got here, what she's working on, and how she keeps learning.
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What does a Machine Learning Engineer actually do all day? Meet MLE Dillon Laird, and hear about what he's working on at Landing AI, what tech stack he uses, and how he keeps up on the latest research and news.
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When I look at the work that I do in AI, frankly a lot of it is dirty work. It’s downloading that dataset, cleaning that dataset, plotting a learning curve and trying to figure out...
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