Transfer Learning and Self-taught Learning examples
Feb 19, 2020

The Batch: Chatbots Sue Telemarketers, Neural Nets See Around Corners, Police Read License Plates, Deep Learning Pioneers Speak

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. These ideas contributed only marginally to practical performance back then, but I’m pleased
A screenshot from The Wizard of Oz
Feb 12, 2020

The Batch: Hotter Dating Profiles, Pandas in Love, Compute for Coronavirus, Deepfake Detection, Self-Driving Cars Run Amok

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.
Glasses on a laptop. Pile of books and a cup in the back.
Feb 05, 2020

The Batch: Robot Warehouse Workers, Cities Under Surveillance, Chatbot Comedian, Automated Drug Design

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, athletes, scientists, and/or engineers.
Woman doing a push-up
Jan 29, 2020

The Batch: Fighting Coronavirus, Hunting Drug Dealers, Fixing Bugs, Regulating AI, Accelerating Text-to-Speech

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
Jan 22, 2020

The Batch: Algorithm Designs Living Machines, AI Interviews Job Applicants, Recommender Spreads Misinformation, Researchers

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 EU’s effort to...
Lifelike video imagery of virtual people made by NEON
Jan 15, 2020

The Batch: AI Steals CES, Hollywood Predicts Blockbusters, Washington Regulates AI, Neural Nets Study Math

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! The right information at the right time can have a powerful impact. It can alter the course of a project or even a career.
Some results from AI Career Pathways report
Jan 08, 2020

The Batch: Facebook Takes on Deepfakes, Google AI Battles Cancer, Researchers Fight ImageNet Bias, AI Grows Globally

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. Different companies organize their teams differently and...
Andrew Ng with his grandfather
Jan 01, 2020

Hopes for AI in 2020: Yann LeCun, Kai-Fu Lee, Anima Anandkumar, Richard Socher

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. About a decade ago, my holiday topic was pedagogy — I still remember lugging a heavy suitcase of books through the airport — and this...
Illustration of Christmas gifts
Dec 24, 2019

Biggest AI Stories of 2019: Driverless Cars Stall, Deepfakes Go Mainstream, Face Recognition Gets Banned

We here at 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: What courses do you want to take this year?
Andrew Ng and other speakers at the NeurIPS 2019 conference
Dec 18, 2019

The Batch: Companies Slipping on AI Goals, Self Training for Better Vision, Muppets and Models, China Vs US?, Only the Best

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 a handful of ideas.
Pie & AI event on AI ethics
Dec 11, 2019

The Batch: Amazon's Surveillance Network, AI That Gets the Facts Right, Deepfakes Get Regulated, Predicting Volcanic Eruptions

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"
Dec 04, 2019

The Batch: Google AI Explains Itself, Neural Net Fights Bias, AI Demoralizes Champions, Solar Power Heats Up

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
Nov 27, 2019

The Batch: Sony Goes AI, Intel's GPU Killers, Transformer Networks In Disguise, Malicious Models Fool Bias Detection

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 topics around the dinner table...
Road sign with the text "new way"
Nov 20, 2019

The Batch: Artificial Noses, Surveillance on Wheels, Unwelcome Researchers, Privacy Problems, Beyond Bounding Boxes

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. Change management isn’t an issue specific to AI, but given the technology’s disruptive nature...
Charts with data explaining how ML works with data distribution
Nov 13, 2019

The Batch: Self-Driving Cars That Can't See Pedestrians?! Evolutionary Algorithms, Fish Recognition, Fighting Fraud

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.

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