I spoke last week at the National Intergovernmental Audit Forum, a meeting attended by U.S. federal, state, and local government auditors. (Apparently some of the organizers had taken AI for Everyone.)

Over the weekend, my family celebrated my grandfather’s 102nd birthday on Zoom. We dialed in from Hong Kong (my grandfather), the U.S. (myself), the UK, Singapore, and New Zealand.

I received a copy of Why We Sleep: Unlocking the Power of Sleep and Dreams as a Christmas gift — back in the pre-Covid era — and finished it last weekend. This book by Matthew Walker, director of UC Berkeley’s sleep and neuroimaging lab...

Last week, I wrote about the U.S. Immigration and Customs Enforcement (ICE) policy that would have forced international students to leave the country if their university went fully online to manage the risk of Covid-19.

I am appalled by the policy, announced on Monday by U.S. Immigrations and Customs Enforcement (ICE), that international students in the country on an F-1 visa must leave if their school goes fully online to cope with Covid-19.

We know that biased data leads to biased machine learning. But does the problem go beyond that? A few colleagues asked about this after a heated exchange on Twitter between Yann LeCun and Timnit Gebru (see “Image Resolution in Black and White” below).

I was dismayed on Monday to read that the U.S. is suspending the H1-B visa program at least through the end of the year. This effort to discourage immigration can only bring distress to workers from other countries and harm to the U.S.

I’m thrilled to announce our new Natural Language Processing Specialization! Courses 1 and 2 are available on Coursera. We expect to release Courses 3 and 4 soon.

Last week, I wrote about the diversity problem in AI and why we need to fix it. I asked you to tell us about your experiences as a Black person in AI or share the names of Black colleagues you admire.

Like many of you, I’m deeply saddened by the events of the past week. I’m horrified by the senseless violence perpetrated against Black communities and appalled by the persistent racial injustice of our society. It’s long past time to right these terrible wrongs.

I’m proud to announce that we held the 100th Pie & AI last Friday. Pie & AI is our meetup series that brings together members of the AI community worldwide for education, conversation, and a slice of pie.

I recently received an email from one of you who lives far from the major AI hubs, saying, “I feel like I’m all alone.” I want to tell you all: Even if it sometimes feels like you’re facing the challenges of work and life in isolation, you are not alone!

Inflection points in society create opportunities. The rise of online video was an inflection point that enabled scalable online education. The rise of the GPS-enabled smartphones similarly enabled Uber, Lyft, Airbnb, and many other services.

There has been a lot of excitement about the idea of using deep learning to diagnose diabetic retinopathy: That is by taking a photo of the retina and using AI to detect signs of disease.

In an earlier letter, I wrote about the challenge of robustness: A learning algorithm that performs well on test data often doesn’t work well in a practical production environment because the real world turns out to be different than the test set.