Woman doing a push-up

The Best Way to Build a New Habit

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.
Illustration of a person with a face recognition system on the face

The Problem With the EU’s Moratorium on Face Recognition

Last week brought reports that the European Union is considering a three- to five-year moratorium on face recognition in public places. Face recognition is a problematic technology with significant potential for misuse, and I celebrate the...
Lifelike video imagery of virtual people made by NEON

Recommended Educational Resources

One of the best gifts a friend gave me last year was recommending a book that I subsequently read and loved. She didn’t even have to buy it for me!
Some results from AI Career Pathways report

Building Your AI Career: A Report by Workera

Many accomplished students and newly minted AI engineers ask me: How can I advance my career? Companies in many industries are building AI teams, but it may not be obvious how to join one of them.
Andrew Ng with his grandfather

The Key to Longevity

Happy New Year!Every winter holiday, I pursue a learning goal around a new topic. In between visits with family, I end up reading a lot.
Illustration of Christmas gifts

Setting Learning Goals

We here at deeplearning.ai wish you a wonderful holiday season. As you consider your New Year’s resolutions and set goals for 2020, consider not just what you want to do, but what you want to learn...
Andrew Ng and other speakers at the NeurIPS 2019 conference

NeurIPS Grows Up

I’ve been reflecting on the NeurIPS 2019 conference, which ended on Saturday. It’s always a wonderful event, but this year I found it a bittersweet experience. Bitter because the conference has grown so much that we no longer focus on...
Pie & AI event on AI ethics

AI Ethics Must Be Actionable

I’ve been thinking about AI and ethics. With the techlash and an erosion of trust in technology as a positive force, it’s more important than ever that we make sure the AI community acts ethically.
Andrew Ng holding a sweatshirt that says "Trust the robot"

Building Trustworthy AI

Recently I wrote about major reasons why AI projects fail, such as small data, robustness, and change management. Given that some AI systems don't work, users and customers sometimes rightly wonder whether they should trust an AI system.
Illustration of a robotic pigeon and a "happy thanksgiving" message from DeepLearning.AI

AI Topics for Dinner-Table Discussion

I’ll be spending Thanksgiving with Nova and watching her taste turkey for the first time. To those of you who celebrate Thanksgiving, I hope you spend time with loved ones, reflect on what you are thankful for, and discuss some very important...
Road sign with the text "new way"

Why AI Projects Fail, Part 5: Change Management

My last two letters explored robustness and small data as common reasons why AI projects fail. In the final letter of this three-part series, I’d like to discuss change management.
Charts with data explaining how ML works with data distribution

Why AI Projects Fail, Part 4: Small Data

In this series exploring why machine learning projects fail, let’s examine the challenge of “small data.” Given 1 million labeled images, many teams can build a good classifier using open source.
Diagram showing what's needed to build a machine learning product

Why AI Projects Fail, Part 3: Robustness

Building AI systems is hard. Despite all the hype, AI engineers struggle with difficult problems every day. For the next few weeks, I’ll explore some of the major challenges. Today’s topic: The challenge of building AI systems that are robust to real-world conditions.
Illustration of a ghost

Why AI Projects Fail, Part 2: Uncommon Pitfalls

Welcome to the Halloween edition of The Batch! I promised last week to share some common reasons for AI project failures. But first, let’s start with some of the least common reasons.
Pie & AI and IASI AI cupcakes

Why AI Projects Fail

I’ve heard this conversation in multiple companies: Machine learning engineer: Look how well I did on the test set! Business owner: But your ML system doesn’t work. This sucks! Machine learning engineer: But look how well I did on the test set!

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