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.

I spoke on Tuesday at Coursera’s annual conference. It was the company’s most well-attended conference yet, and the first to be held online. Higher education is in for turbulent times.

This week’s issue of The Batch is all about medical applications of AI. Amid the current pandemic, the marriage of AI and medicine is more urgent than ever. My father is a practicing doctor, and I grew up seeing firsthand how the right...

Last week, I asked readers to tell me what they’re doing to address the Covid-19 pandemic. Many of you wrote to say you’re taking actions such as shopping for neighbors, making masks, and creating posters that promote Covid-safe practices...

In the earlier weeks of Covid-19, I didn’t want to contribute noise, so that experts in infectious disease could be heard. But now the situation has worsened. I spoke yesterday with Eric Topol, a cardiologist at Scripps Institute and author of Deep...

When I was younger, I was not a fan of working from home. Too many distractions! So I worked a lot in coffee shops. They turned out to be convenient places to talk to strangers and ask for feedback about products I was working on...

The unfolding Covid-19 crisis calls for individuals and organizations to step up and contribute to the common good. I believe that the tech community has an important role to play in slowing the progress of the virus and shortening the time...

The Covid-19 pandemic is a tragedy that demands urgent and humane response. It’s also pushing us toward new ways of gathering and sharing information — and that may be a faint silver lining that might grow brighter over time.

In addition to creating tremendous value, AI is creating tremendous concentrations of power. Our community is wrestling with what constitutes fair use of that power.

I chatted recently with MIT researcher Lex Fridman on his Artificial Intelligence podcast, where we discussed our experiences teaching deep learning. It was the most fun I’ve had in an interview lately, and you can watch the video here.

Nearly a decade ago, I got excited by self-taught learning and unsupervised feature learning — ways to learn features from unlabeled data that afterward can be used in a supervised task.

A student once asked me, “Can an AI ever love?”Since the early days of AI, people have wondered whether AI can ever be conscious or feel emotions. Even though an artificial general intelligence may be centuries away, these are important questions.

Many of us apply labels to ourselves that shape our identity. Some say, “I’m a sports fan,” and this attitude motivates behaviors such as cheering for the home team. Others identify themselves as introverts, extroverts, vegetarians, gamers...

I just finished reading BJ Fogg’s new book, Tiny Habits: The Small Changes That Change Everything. Fogg explains that the best way to build a new habit is to start small and succeed, rather than starting too big and giving up.