Last week, DeepLearning.AI invited a group of learners to our Palo Alto office’s courtyard. We had a good time chatting about paths into AI, career trajectories, applications people were working on, and challenges they were facing.

Russian troops have invaded Ukraine, and the terrifying prospect of a war in Europe weighs on my mind. My heart goes out to all the civilians affected, and I hope we won’t see the loss of life, liberty, or property that many people fear.

We just launched a Data-Centric AI Resource Hub to help you improve the performance of AI systems by systematically engineering the underlying data. It offers new articles by Nvidia director of machine learning research...

I tested positive for Covid on Monday and mentioned this on social media. I’m grateful to the many people who wished me well. Reading your messages made me feel better. My unscientific feeling is that they helped clear my nose a bit!

I’m writing this in Orlando, Florida, where I just spoke at the A3 Business Forum, a group that works to advance industrial automation through AI, robotics, and other tools. This was my first large conference since the pandemic started...

If you want to build a career in AI, it’s no longer necessary to be located in one of a few tech hubs such as Silicon Valley or Beijing. Tech hubs are emerging in many parts of the world, and cities large and small offer opportunities both for local talent and companies worldwide.

How to Learn Machine Learning | How to Gain Practical Experience | How to Overcome Societal Obstacles | How to Get a Job in AI | How to Keep Up in a Changing Field

AI continues to create numerous exciting career opportunities, and I know that many of you aim to develop a career in the field. While taking online courses in technical topics is an important step, being an AI professional requires more than technical skills.

One rule I try to live by is to not surprise my collaborators. During a project, for example, a deadline may slip, or a customer may drop out.

As we approach the end of the year, many of us consider setting goals for next year. I wrote about setting learning goals in a previous letter. In this one, I’d like to share a framework that I’ve found useful: process goals versus outcome goals.

As we approach the end of 2021, you may be winding down work and gearing up for the winter holiday. I’m looking forward to taking a break from work and hope you are too.

We just wrapped up the Data-Centric AI Workshop at the NeurIPS 2021 conference. It was packed with information about how to engineer data for AI systems.

Should we be optimistic or pessimistic about the prospects for ethical AI? I meet people who are encouraged by the progress we’ve made toward making AI more responsible and free of bias.

I’ve seen many new technologies go through a predictable process on their journey from idea to large scale adoption. First, a handful of experts apply their ideas intuitively.

I’m grateful to the AI community for the friendships it has brought me and the benefits it has brought to billions of people.