Shortly after Pi day (3/14), I announced our Pie & AI series of meetups. We held them in Seattle in March and London in April. We just hosted our third Pie & AI meetup to celebrate the launch of the final course in the deeplearning.ai TensorFlow Specialization.

I recently met an engineer at a large travel agency who had built a fun ML project for sending guests greetings. This was one of the company’s first forays into ML. The project did not generate any revenue, and their managers discouraged them from doing more work on ML.

My stash of new blank notebooks just arrived in the mail. I have a weakness for stationery. I always feel that if only I had the perfect pen and notebook, I might have better ideas.

If you wonder how often I take online courses myself, the answer is: Quite often. I have a longstanding interest in AI for healthcare.

As we were working on the latest course of the deeplearning.ai TensorFlow Specialization, instructor Laurence Moroney messaged me his LSTM-generated poetry, created by learning from a database of roughly 100 Irish song lyrics.

AI is still compute-hungry. With supervised learning algorithms and emerging approaches to self-supervised and unsupervised learning, we are nowhere near satisfying this hunger.

Last Friday, I attended the International Conference on Machine Learning. I spoke at the AI and Climate Change workshop on projects we’re doing to model methane emissions and on wind turbines. John Platt gave an overview of climate issues.

I spoke last week at re:MARS, Amazon's conference focusing on machine learning, automation, robotics, and space. I heard great talks from Jeff Bezos, Kate Darling, Ken Goldberg, Marc Raibert, and others.

Healthcare is one of many sectors being transformed by AI. I have a personal interest in it, since my father worked on machine learning for diagnosis of liver diseases almost 40 years ago. It’s thanks partly to this work that I learned about AI from an early age.

In March, I announced our Pie & AI series of meetups. Since then, we've held events in Seattle and London, two growing centers of AI talent. It’s inspiring to see AI develop around the world and not just in Silicon Valley and Beijing.

So many people who are just starting out in machine learning are doing amazing work. With online education, open source software, and open publications, it takes less time than ever to go from 0 to 100 in ML.

I’ve been thinking a lot about "small data." If you have an image classification problem and 1,000,000 images, then dozens of teams around the world can build a good classifier.

A first for my three-month-old daughter Nova: an outing to the park. As my mother and I watched her staring at a tree. I realized what a novel experience it must be to see a tree close-up for the first time.

On Monday, I delivered a keynote via teleconference for Dubai's AI Everything conference. It was inspiring to see so many governments, businesses, and social enterprises coming together to talk about AI.

I spent my birthday last week thinking about how AI can be used to address one of humanity's most pressing problems: climate change.